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, our new user experience, is gaining momentum and driving significant impact for our customers. Customers are already efficiency, enhancing processes, improving , and .

Joule is now live across 35 solutions and will continue to meet our customers where they are: across the applications they use, with a firm understanding of their business context and data. That鈥檚 why in Q1 we are embedding Joule into more applications鈥攆rom 麻豆原创 Datasphere, where it can now execute tasks or explain specific functionalities, to 麻豆原创 Intelligent Clinical Supply Management, where users can use natural language to retrieve critical data and navigate to relevant applications.

Joule Agents, such as the Tender Analysis Agent, are boosting customer revenue growth by extracting critical requirements and flagging risks in complex documents. While project managers in 麻豆原创 S/4HANA Cloud Public Edition are saving time setting up projects with the new Project Setup Agent. Plus, there are many more agents to discover below.

Agents are becoming a key new user鈥攁nd enabler鈥攐f enterprise software, joining humans as the only other non-deterministic operators while simultaneously expanding enterprise software鈥檚 scope and usefulness. Our agents will continue to deliver trustworthy, repeatable, and auditable results every time.

We now have over 30 specialized agents and more than 2,500 Joule Skills. The agent-to-agent protocol means our agents work across 麻豆原创 and non-麻豆原创 systems. As the number of agents grows across both, 麻豆原创 AI Agent Hub already today provides customers with the essential infrastructure and guardrails to manage, govern, and discover agents in this new ecosystem.

Some highlights from Q1 2026:

• 麻豆原创 Joule for Consultants is a conversational AI solution that provides expert guidance on cloud transformations, drawing on 麻豆原创鈥檚 knowledge base. To improve trust and traceability, citations are now displayed in a dedicated side panel and can be grouped for clarity. Administrators can enable web search, allowing Joule to draw from public content while maintaining clear source attribution. For tailored answers to problems where the system may not have customer-specific documentation, consultants can now upload up to 10 PDF or text files directly into the chat. This is further enhanced by the inclusion of content from the 麻豆原创 Enterprise Architecture Reference Library, which provides more complete and accurate answers to complex queries. Get started here.
• 麻豆原创 Business AI for supply chain minimizes disruptions and simplifies planning. The Project Setup Agent allows project managers to rapidly establish new projects by drawing on data from past initiatives. 麻豆原创 Integrated Business Planning users can now generate complex formulas in Microsoft Excel with natural language. 麻豆原创 Digital Manufacturing can distill complex manufacturing issues into clear descriptions. Joule is also helping 麻豆原创 Integrated Product Development users create problem reports and requirement models with simple, natural-language commands. Explore more below.
• 麻豆原创 Business AI for finance offers greater efficiency and insight across critical processes. Joule now translates complex e-invoicing errors into plain language. The Dispute Resolution Agent automates root-cause analysis for invoice disputes, while payment advice processing significantly reduces document processing time. Unstructured data, such as PDFs, can now be automatically transformed into sales orders, and accountants can access natural language explanations for complex fixed asset calculations. Users can personalize their home page and easily understand system errors using natural language across 麻豆原创 S/4HANA Cloud Public Edition. Learn more below.
• 麻豆原创 Business AI for procurement and customer experience enhances the entire commercial journey with new capabilities. In procurement, automated statement of work (SOW) creation in 麻豆原创 Fieldglass reduces the time to define deliverables. The Catalog Optimization Agent means e-commerce managers can continuously improve product data quality. In retail, managers can get instant, conversational answers from Joule on order management data. There’s so much more to learn below.
• 麻豆原创 Business AI for IT and developers puts the latest tools and greater control directly into the hands of developers and data professionals. Joule is now generally available in 麻豆原创 Datasphere, enabling users to navigate the platform, get answers, and execute tasks using simple conversational language. The generative AI hub in AI Foundation continues to expand, offering developers access to the newest models, including OpenAI GPT 5.2, Gemini 3.0 Pro, Anthropic Claude Opus 4.6, and Claude Sonnet 4.6. Developers also gain greater power through enhancements such as advanced prompt optimization, metadata filtering, and declarative orchestration configurations in the prompt registry. Additionally, 麻豆原创 Document AI now offers more granular control with custom confidence thresholds and expanded document support. Dive into everything below.
• 麻豆原创 Business AI for industries delivers specialized intelligence to solve unique business challenges. Sales teams can accelerate their response process with the new Tender Analysis Agent, which automates the review of complex RFQ documents to improve win rates. Joule now works with 麻豆原创 Commodity Management to turn verbal or written negotiations directly into detailed draft deals. In life sciences, clinical supply professionals can use predictive analytics to reduce inventory waste costs, and Joule dramatically cuts information search time. 麻豆原创 Self-Billing Cockpit automates invoice data extraction from any format, significantly reducing manual processing time. Discover more for industries below.
• 麻豆原创 Business AI for business transformation management provides the critical insights needed to navigate and accelerate organizational change. Joule is now in 麻豆原创 Signavio, enabling natural-language searches that cut information discovery time. Business process model and notation simulations in 麻豆原创 Signavio provide clear, actionable summaries directly within process diagrams. Meanwhile, enterprise architects can leverage guidance in 麻豆原创 LeanIX to surface actionable insights directly from their architecture inventory, accelerating transformation execution and reducing the time to uncover them. Read more about transformation management below.

Joule

Joule, enhancements

User experience is improved by streamlining startup times and introducing cross-thread search functionality that lets end users find information across all conversation threads without manually checking individual histories. The document grounding capability has also seen a substantial upgrade, now supporting seamless integration with Google Drive.

To set up, see: , , and .

Furthermore, scalability has been greatly improved, as the system now supports up to 8,000 documents per pipeline, enabling large-scale data repositories to be processed and utilized efficiently.

For more information, see .

麻豆原创 Joule for Consultants, enhancements

Enhanced Citation Visibility
麻豆原创 Joule for Consultants has improved how citations are displayed for all identified sources returned by the product. Citations have been relocated to the right side in a dedicated panel for clearer visibility, and now also include public web search results when applicable (see below).

A new grouping feature has also been added, allowing citations to be grouped. This update provides users with a more transparent view of where information originates, strengthens trust, and improves traceability across all responses.

To see the sources and panel, click the sources button below each message; the panel will open on the right, showing all grouped sources.

Enable Web Search
Administrators can now enable/disable web search via the control panel for all assigned end users in 麻豆原创 Joule for Consultants.

When enabled, 麻豆原创 Joule for Consultants will consider public web content in its reasoning and cite relevant public sources in responses when they contribute to the answer. This enhancement gives organizations greater flexibility and transparency by enabling broader coverage of information while maintaining clear source citations for all sources used.

File Uploads in the Joule Message Input
End-users can now upload up to 10 files directly from the conversational message input box and reference them throughout the entire conversation.

Supported file types include PDF and TXT. Each file should be no more than 10 MB/600K characters; for PDFs, an approximation. A 100-page limit applies; if your file is larger, split it into multiple documents. Image files are currently not processed and will be ignored. We are working diligently to make this feature even more useful to end users. This enhancement enables richer, context-aware interactions by allowing you to incorporate your uploaded documents into its conversational responses throughout the session. Please be aware that the standard data privacy terms apply. See also the help documentation for additional information on the free user quota.

Content: 麻豆原创 Enterprise Architecture Reference Library
麻豆原创 Enterprise Architecture Reference Library data has been ingested and is now available for use in conversations. As more data is added, relevant portions may be included in 麻豆原创 Joule for Consultants鈥� responses, enabling more complete, accurate, and context-rich answers to user queries. Since 麻豆原创 Enterprise Architecture Reference Library content cannot be link-referenced, you won鈥檛 see the additional content listed under sources, even though it will be referenced.

Get started .

SECTION

麻豆原创 Business AI for supply chain

Project Setup Agent
Beta release

Project managers can now rapidly establish new projects by drawing on data from similar past initiatives. The agent bypasses complex interfaces and reduces reliance on the project management office (PMO) to facilitate the swift allocation of key resources needed to launch projects effectively. With a 10% reduction in project creation time, 16% faster resource allocation, and 30% less time spent reworking projects due to incorrect templates, teams can shift focus from operational coordination to improving project profitability and driving efficiency.

Get started .

麻豆原创 S/4HANA Cloud Private Edition, AI-assisted retrieval of equipment information in service management
General availability

Service managers using the AI-assisted retrieval feature in 麻豆原创 S/4HANA Cloud Private Edition gain a complete 360-degree view of customer equipment. The feature provides instant access to warranty information and a full history of service transactions, complemented by an AI summary and actionable recommendations. This allows service managers to more efficiently oversee service schedules, reduce potential downtime, and ensure customer equipment operates at peak performance.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted input recommendations for returns order creation
General availability

Returns clerks can accelerate the creation of customer returns with data field recommendations powered by historical data. This feature analyzes past return documents with similar process variants to automatically suggest the most common input values and return reasons, minimizing manual data entry and reducing errors. Organizations benefit from a one percent reduction in data management costs and a five percent decrease in business and operations analysis expenses, enabling returns teams to process orders more efficiently while maintaining accuracy.

Get started .

麻豆原创 Integrated Business Planning, AI-assisted MRO inventory analysis
General availability

Inventory planners get a new analytical assistant in the MRO inventory analysis feature for 麻豆原创 Integrated Business Planning. The feature accelerates root cause analysis by generating clear, natural-language summaries that explain the key drivers behind recommended safety stock and reorder points. By translating complex calculations into understandable insights, this capability enables planners to reduce time spent analyzing inventory runs by 30%, leading to faster adoption of outputs and ensuring that inventory parameters align with strategic business goals.

Get started .

麻豆原创 Integrated Business Planning, add-in for Microsoft Excel, AI-assisted planning
General availability

Supply chain planners can now simplify their work with a new AI-assisted planning add-in for Microsoft Excel. Instead of manually creating complex formulas or formatting rules, which often require technical expertise, they can simply describe their needs in natural language, and the system automatically generates the correct syntax. This intuitive way of interacting with the system removes technical barriers and improves a planner鈥檚 efficiency by 10%, freeing them to focus on strategic analysis rather than implementation details.

Get started .

麻豆原创 Integrated Business Planning, AI-assisted system security check
General availability

Supply chain planners and security analysts gain a robust way to assess system configurations against established security recommendations. The feature evaluates compliance states and provides clear guidance on required adjustments, helping administrators identify and address potential gaps while aligning configurations with 麻豆原创 best practices. Organizations can expect a 27% increase in compliance with hardening guidelines and a 32% reduction in the effort required to meet security recommendations. This feature strengthens the protection of sensitive data and reduces the risk of security breaches.

Get started .

麻豆原创 Integrated Product Development, AI-assisted problem report creation
General availability

Maintenance engineers can simplify the creation of formal problem reports by leveraging AI capabilities in 麻豆原创 Integrated Product Development. By describing an issue in their own words to Joule, it intelligently extracts key details like the problem name, tags, and priority, and then automatically generates a structured report. This streamlined process dramatically reduces manual data entry and ensures all reports are consistent and compliant with organizational standards, improving overall efficiency.

and get started .

麻豆原创 Integrated Product Development, AI-assisted requirements model creation
General availability

Requirements managers now have a more direct path to creating requirement models within 麻豆原创 Integrated Product Development by using natural language commands with Joule. This feature allows them to initiate new models, specify names, and apply templates in a single step, completely bypassing the need to navigate through complex folder structures. This streamlined approach provides a much faster starting point for new projects and empowers users to begin their work immediately without requiring deep knowledge of the repository layout.

Get started .

麻豆原创 Field Service Management, AI-assisted automated scheduling analytics
General availability

Field service dispatchers and consultants can now access clear, on-demand explanations of auto-scheduling results that demystify complex system logic. The new feature interprets scheduling reports and translates technical scoring details into business-friendly insights, explaining why specific technicians were assigned, why alternatives were passed over, and why certain activities remained unscheduled. This transparency drives a 12.5% increase in dispatcher productivity and a five percent reduction in erroneous resource allocations, strengthening trust in automated decisions while significantly reducing analysis time.

Get started .

麻豆原创 Digital Manufacturing, AI-assisted description enhancement
General availability

Quality managers documenting complex manufacturing issues can now generate clear, objective, and structured descriptions with minimal effort. 麻豆原创 Digital Manufacturing for issue resolution offers description generation that refines rough initial inputs, removes bias and subjective language, and produces balanced, factual problem statements. With support for multilingual translation and enhanced clarity, organizations can achieve up to five percent improvement in quality engineer efficiency during issue handling and up to 10% reduction in errors throughout the problem resolution process.

Get started .

麻豆原创 Business AI for finance

Dispute Resolution Agent (for 麻豆原创 S/4HANA Cloud Public Edition)
Beta release

When invoice disputes arise, accounts receivable specialists need to act quickly without sacrificing accuracy. 麻豆原创 S/4HANA Cloud Public Edition introduces an agent that automates root-cause analysis, scanning invoices, sales orders, delivery records, pricing agreements, and tax rules to identify the source of discrepancies. The agent detects incorrect charges and recommends compliant solutions, such as credit memo creation, enabling finance teams to resolve disputes faster, minimize manual investigation, and cultivate stronger vendor relationships through transparent, efficient processes.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted smart personalization of my home for applications
General availability

麻豆原创 S/4HANA Cloud Public Edition users can easily configure their home page with the most relevant applications through AI-assisted smart personalization. By describing their task in natural language, the system identifies the appropriate app, which can then be added to their home screen with a single click. This intuitive capability reduces the cost of personalizing the home page by 33%, shortens the learning curve for new users, and improves satisfaction by keeping frequently needed tools readily accessible.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted error explanation
General availability

When encountering system errors, 麻豆原创 S/4HANA Cloud Public Edition users can turn to a new feature that generates clear, natural language explanations and resolution recommendations. This capability transforms cryptic error messages into easy-to-understand guidance, helping users of all experience levels quickly rectify issues and continue with their work. By reducing error resolution time by five percent, organizations benefit from increased productivity, improved data quality, and shorter training cycles for new team members.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted sales order creation from unstructured data
General availability

Sales representatives benefit from a streamlined order creation process in 麻豆原创 S/4HANA Cloud Public Edition that handles unstructured data like PDF or image-based purchase orders. After uploading a file, 麻豆原创 Document AI automatically extracts the relevant information and proposes the data for a corresponding sales order request. This automation significantly reduces manual data entry, minimizes errors, and improves overall operational efficiency, allowing teams to process orders faster and enhance customer satisfaction.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted processing of payment advices with 麻豆原创 Document AI
General availability

Accounts receivable clerks can accelerate their workflow using the 麻豆原创 Document AI-powered payment advice processing feature in 麻豆原创 S/4HANA Cloud Public Edition. The system automatically extracts payment amounts, references, and currencies from diverse invoice formats across multiple languages, with a self-learning capability that continuously improves recognition accuracy. Organizations implementing this feature can reduce document processing time by 70%, cut template maintenance time by 83%, and decrease value loss from manual processing delays by 40%.

Get started .

麻豆原创 S/4HANA Cloud Private Edition, AI-assisted fixed asset key figures explanation
General availability

Asset accountants gain clarity on complex fixed asset calculations through a new AI feature in 麻豆原创 S/4HANA Cloud Private Edition. The feature generates natural-language explanations that detail the origins of displayed values and how figures such as depreciation are calculated; for example, illustrating the impact of mid-year acquisitions with specific depreciation keys. This transparency reduces the effort required to analyze asset values, enables faster responses to asset-related questions, and helps mitigate compliance risks.

Get started .

麻豆原创 S/4HANA Cloud Private Edition, AI-assisted settlement rule proposal for asset capitalization
General availability

Overhead and asset accountants can now streamline the complex process of creating settlement rules for investment measures, eliminating the traditionally time-consuming, error-prone manual configuration. The solution automatically determines receivers, calculates percentages, and proposes feasible rules based on contextual data and user-defined instruction profiles. Organizations reduce the effort required to create full settlement rules by 50% while simultaneously improving accuracy in asset capitalization and enhancing overall operational efficiency across their financial processes.

Get started .

麻豆原创 Document and Reporting Compliance for 麻豆原创 S/4HANA Cloud Private Edition, AI-assisted electronic document error handling
General availability

Tax accountants navigating the growing complexity of e-invoicing mandates across multiple countries gain an easy way to decode technical errors without wading through intricate XML or JSON formats. Joule, integrated with 麻豆原创 Document and Reporting Compliance, delivers plain-language explanations of electronic document errors, enabling faster root-cause identification and more efficient resolution. Organizations get an 80% reduction in time spent understanding and resolving errors, dropping from 150 minutes to approximately 30 minutes. This results in faster processing cycles, reduced penalty risks, and improved cash flow.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted error resolution for cost accounting
General availability

Operations managers in retail organizations can now access Joule via 麻豆原创 Order Management Services, enabling them to query order data and receive real-time, role-specific operational guidance across order processing, orchestration, sourcing, availability, returns, and fulfillment flows. Joule surfaces instant insights and recommended actions directly in the workflow, reducing the need to navigate multiple systems. This enables proactive intervention before issues escalate. The feature offers faster transaction access, improved responsiveness and accuracy, and lower operational risk, which support smarter, quicker decisions across the order lifecycle.

Get started .

麻豆原创 Business AI for spend management

Expense Report Validation Agent
General availability

Business travelers can enjoy a smarter, guided approach to expense report completion with an agent that proactively identifies missing items, prompts for necessary details, and clarifies confusing alerts throughout the submission process. By simplifying how users understand and resolve issues, the agent ensures accurate, policy-compliant reports with minimal effort required. This means a 30% reduction in time spent preparing and submitting reports, a 24% increase in first-pass approvals, and a noticeably improved employee experience that removes friction from the expense management process.

Get started .

Expense Pre-Submit Audit Agent
麻豆原创 Early Adopter Care

Expense report submitters can now catch receipt accuracy issues and policy breaches before hitting the submit button, avoiding the frustration of rejected reports and delayed reimbursements. This agent automatically reviews expenses during creation, surfacing compliance problems and offering smart suggestions for quick corrections. The agent uses a non-blocking design that keeps users in control of final decisions. Organizations benefit from a 10% decrease in sent-back expense reports, reduced rework for travelers, managers, and auditors alike, and a noticeably smoother reimbursement process that enhances the overall employee experience.

Get started .

Expense Automation Agent
麻豆原创 Early Adopter Care

Employees burdened by the administrative chore of creating expense reports can now delegate the heavy lifting to a Joule Agent. This agent automatically builds expense reports by aggregating transactions, populating custom fields based on contextual details and user history, and preparing everything for a quick review before submission. The outcome is up to 30%鈥� reduction in time on task for auto-generated expense reports. This offers a modern expense management experience that slashes manual data entry, accelerates the submission process, and frees employees to focus on high-value work rather than paperwork.

See the demo .

Concur Expense, AI-assisted configuration for audit rules
General availability

Expense administrators responsible for managing complex audit rule setups can now interact with their configuration environment in plain language, eliminating the need for deep technical expertise or tedious manual adjustments. This AI-assisted feature enables admins to search existing rules, create new ones, and receive real-time explanations simply by asking questions like “What rules apply to meals in France?”, delivering clear, actionable guidance instantly. The outcome is a 40% reduction in audit rule configuration effort, fewer support tickets, and empowered administrators who work with greater independence, accuracy, and confidence in maintaining compliance logic.

Get started .

Policy Navigator
麻豆原创 Early Adopter Care

Business travelers seeking quick answers to company travel and expense policies no longer need to sift through lengthy documents or wait for admin responses. Policy navigator in Joule allows employees to ask questions in natural language and receive clear, contextual guidance grounded in approved policies, whether planning a trip, in the middle of a journey, or completing an expense report. The result is in-the-moment policy clarity that prevents non-compliant spend before it happens, reduces support tickets, and empowers travelers to make confident, compliant decisions without disrupting their workflow.

Get started .

麻豆原创 Business AI for procurement

麻豆原创 Fieldglass Services Procurement, AI-assisted SOW deliverables creation
General availability

Procurement specialists can accelerate the development of their statements of work using the deliverables feature in 麻豆原创 Fieldglass Services Procurement. The feature analyzes the defined project scope and automatically generates precise, relevant deliverables that ensure tight alignment between buyer expectations and supplier commitments. By adopting this capability, organizations can reduce the time required to manually create SOW deliverables by 70% and cut the risk of poor outcomes by 50%, while fostering stronger collaboration during the negotiation process.

Get started .

麻豆原创 Business AI for customer experience

Catalog Optimization Agent
General availability

E-commerce product managers tasked with maintaining large 麻豆原创 Commerce Cloud catalogs gain an always-on agent that continuously reviews product descriptions, attributes, and translations against company quality standards. This agent pinpoints merchandising gaps and delivers actionable recommendations to enhance catalog accuracy, ensure consistency across languages, and improve product discoverability. The business impact is a 70% reduction in time to translate catalog data, 65% less time spent adding descriptions per asset, and a five percent reduction in data quality costs, all of which contribute to higher conversion rates and a more agile merchandising operation.

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麻豆原创 Revenue Growth Management, AI-assisted trade promotion creation
General availability

Key account managers in consumer industries can benefit from a streamlined, single-view promotion-creation experience in which simply naming a promotion automatically populates key fields. Drawing on master data, historical promotions, and learned preferences specific to each retailer, the system suggests dates, types, durations, and sell-in periods, then continuously refines its recommendations based on user edits over time. The impact is a 75% reduction in promotion setup time, 30% fewer data-entry errors and rework, and increasingly personalized suggestions that eliminate repetitive manual effort across promotion cycles.

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麻豆原创 Business AI for IT and developers

Joule Studio code editor and Joule Studio CLI

Building on the transformative capabilities of Joule studio low-code, 麻豆原创 is expanding the Joule studio family with two powerful new offerings designed to meet developers exactly where they work: Joule Studio code editor, a Visual Studio Code IDE extension, and Joule Studio CLI, a versatile command-line interface. Together, these tools deliver a unified, AI-assisted development experience that spans the full spectrum of development personas and preferences on Joule.

• Joule Studio code editor brings the intelligence of Joule directly into Visual Studio Code, the world’s most popular development environment, empowering pro-code developers with AI-guided scaffolding, contextual code generation, intelligent recommendations, and seamless integration with Joule, all without leaving their preferred IDE. 
• Joule Studio CLI extends this same power to the terminal, enabling developers and DevOps teams to automate project creation, manage configurations, execute deployments, and orchestrate CI/CD workflows through scriptable, command-line commands鈥攊deal for headless environments, automation pipelines, and teams that value speed and precision at the command line.

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Joule with 麻豆原创 Datasphere
General availability

Data professionals working within 麻豆原创 Datasphere can now accomplish informational, navigational, and transactional tasks through natural conversation with Joule. Whether asking how to use specific functionalities, retrieving details about a 麻豆原创 Datasphere instance, or switching system settings like language preferences, users receive instant answers with direct references to product documentation. Joule can even execute tasks directly from the conversation without requiring interaction with the standard interface. This direct execution reduces reliance on internal IT support and enables faster, more intuitive navigation throughout the platform.

Get started .

麻豆原创 Document AI, enhancements

Document level confidence
Customers now set confidence ranges for fields in the Schemas feature. When customers edit field settings, they can define their own thresholds for low, medium, and high confidence. These custom settings are reflected in the extraction results displayed for the relevant fields on the document details screen. See and .

Expanded Transportation Management
Customers can now use the Transports feature to export and import channels and workflows. See .

New schemas: business partner + delivery note for WM
The service plans embedded edition and premium edition now also support the standard document type, business partner document. See the list of supported document types in . Get started with 麻豆原创 Document AI, and .

Generative AI Hub in AI Foundation, enhancements

Metadata
Customers can now manage metadata for documents, collections, and chunks created with the Vector API to enable advanced filtering and organization of their content. For more information, see .

Retrieval API
Customers can merge and rank search results across multiple data repositories using the Retrieval API’s post-processing capabilities. For more information, see .

Prompt optimizations
Custom metrics are supported in prompt optimizations, enabling customers to define and optimize prompts based on their specific evaluation criteria. Only LLM-as-a-judge metrics with numerical or Boolean output types can be used in optimization tasks.For more information, see and . Customers can provide separate test and train datasets for prompt optimization. For more information, see .

Prompt registry
The prompt registry now enables customers to create and manage orchestration configurations declaratively, allowing them to version and track complex AI workflows alongside their prompts for better governance and reproducibility.For more information, see .

Secrets
Customers can now enter generic secrets using a form instead of JSON. The form appears in the Add Generic Secret dialog when you activate document grounding. A dropdown menu lets them choose the type of document repository. Depending on their selection, the remaining fields adjust dynamically, allowing them to complete the data. Some fields are already prefilled.If they prefer working directly with JSON, switch to the code view by clicking the 顒� icon. For more information, see .

New models available
New models are supported, including OpenAI GPT 5.2, Gemini 3.0 Pro, Perplexity Deep Research, and Anthropic Claude Opus 4.6.For more information on new and deprecated models, .

麻豆原创 Joule for Developers, ABAP AI capabilities, enhancements

New ABAP AI capabilities mean developers can expect a 20% reduction in time and effort to write ABAP/JAVA code, 25% reduction in time and effort to test ABAP/JAVA code, and 4.4% faster time to realized value.

This quarter, developers can now easily generate ABAP Unit tests for:

• Public, protected, and private methods of global ABAP classes
• Public methods of local classes within global class pools

See .

In addition, the documentation chat allows developers to interact with documentation on the 麻豆原创 Help Portal, providing context-aware answers and links to relevant documentation. This capability enhances productivity by offering quick access to related documentation directly within the development environment. See .

Finally, developers can now get AI-powered explanations of their ATC findings and code in the Custom Code Analysis/Custom Code Migration app. See and .

Get started .

麻豆原创 Business AI for industries

Tender Analysis Agent
General availability

Sales teams can elevate their tender response process with the Tender Analysis Agent, which automates the review of complex RFQ documents. The agent extracts critical product requirements, flags potential risks and policy gaps, and suggests optimized configurations tailored to customer needs. By reducing the effort to process incoming tenders by five percent and improving win rates, organizations can achieve measurable revenue growth while accelerating sales cycles and uncovering valuable cross-sell and up-sell opportunities.

Get started .

麻豆原创 Commodity Management, AI-assisted commodity work center
General availability

Commodity traders can transform how they capture and manage complex deals using the commodity work center in 麻豆原创 Commodity Management. Working alongside Joule, the feature converts verbal or written negotiations into detailed draft deals, automatically populating the numerous fields that traditionally require extensive manual entry. This enables traders to redirect their focus toward negotiating better commercial outcomes, while improving data accuracy and driving greater operational efficiency across their trading activities.

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麻豆原创 Intelligent Clinical Supply Management, AI-assisted predictive subject dynamics
General availability

Clinical trial coordinators seeking to boost their supply planning capabilities will find a powerful ally in 麻豆原创 Intelligent Clinical Supply Management. The predictive subject dynamics feature analyzes historical and real-time data to forecast patient enrollment trends and dropout rates, automatically generating insights that would otherwise require extensive manual analysis. This enables supply chain teams to redirect their focus to strategic decision-making, while reducing clinical inventory waste costs by up to two percent and improving demand forecasting accuracy across their trial operations.

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Joule with 麻豆原创 Intelligent Clinical Supply Management
General availability

Clinical supply professionals juggling multiple tasks and complex systems need quick access to information without disrupting their workflow. Together with Joule, 麻豆原创 Intelligent Clinical Supply Management delivers an intuitive, conversational interface that understands natural-language requests, enabling users to retrieve critical data and navigate to relevant applications effortlessly. This streamlined experience results in an 83% reduction in time spent on information searches, freeing teams to concentrate on higher-value activities and significantly boosting overall productivity.

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麻豆原创 Self-Billing Cockpit, AI-assisted document processing
General availability

Billing clerks managing self-billing workflows frequently encounter invoices arriving in a mix of formats鈥擡xcel, PDF, CSV, or text files鈥攐ften unstructured and spanning multiple languages. 麻豆原创 Self-Billing Cockpit addresses this challenge by leveraging intelligent document processing to parse and extract invoice data from virtually any format, converting it into structured payloads ready for automated billing. The result is significantly reduced time spent processing invoice line items, fewer customer-specific interfaces for integration specialists to build and maintain, and improved extraction accuracy through minimized manual intervention.

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麻豆原创 Business AI for business transformation management

Joule with 麻豆原创 Signavio solutions
General availability

Process analysts and optimization specialists working across complex organizational workflows require rapid access to diagrams, documentation, and performance metrics. 麻豆原创 Signavio solutions integrate with Joule to enable natural-language keyword searches across process diagrams, dictionary items, and help resources. At the same time, best-practice KPI recommenders guide users to the most relevant success measures. This intuitive approach delivers 50% faster information searches and navigation, ensuring teams make data-driven decisions with improved search quality and an enhanced overall user experience.

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麻豆原创 Signavio solutions, AI-assisted business process model and notation simulation insights
General availability

Process analysts leveraging 麻豆原创 Signavio can now access embedded business process model and notation simulations directly within their process diagrams, eliminating the need for fragmented tools and manual interpretation. Key metrics such as costs, cycle times, and resource utilization are automatically translated into clear, actionable summaries that highlight bottlenecks and opportunities for improvement. This streamlined approach reduces time to access process modeling insights by 50%, empowering teams to compare scenarios effortlessly and communicate findings to stakeholders with greater confidence and clarity.

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麻豆原创 LeanIX solutions, AI-assisted architecture guidance
General availability

Enterprise architects seeking to accelerate transformation initiatives can leverage 麻豆原创 LeanIX to surface actionable insights directly from their architecture inventory. The feature analyzes enterprise architecture data to identify opportunities and guides users through the workflows and tasks needed to efficiently act on recommendations. Organizations benefit from a 95% reduction in time to discover insights, 80% faster transformation execution, and a five percent reduction in value erosion from delayed action. Overall, this feature drives greater architectural productivity and more agile decision-making.

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Jonathan von Rueden is chief AI officer of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks, and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, expressor implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

With the听听1H鈥�2026 release,听we鈥檙e听deepening those connections across the HR lifecycle. This release focuses on听four听core priorities:听connected,听suite-wide听AI; unified experiences that adapt to how organizations work;听processes designed for clarity, accuracy, and compliance; and stronger foundations for skills and long-term growth.听Together, these innovations help organizations听anticipate听needs earlier, reduce friction in daily work, and move forward with greater confidence.听

Connected AI that works across HCM

AI in HR delivers the greatest impact when it works continuously across the entire workforce lifecycle鈥攏ot as isolated features, but as connected capabilities that share context and insight.

The 1H鈥�2026 release expands听suite-wide听agentic AI听across 麻豆原创 SuccessFactors solutions, helping听employees听get clearer answers, act sooner, and keep听work moving听across roles and responsibilities.听A connected network of听听now supports areas such as recruiting, workforce administration, payroll, learning, performance, and talent development鈥攚orking together behind the scenes to help听anticipate听next steps and surface relevant guidance.

This release also introduces a growing听workforce knowledge network, bringing trusted external expertise and research directly into the flow of work through Joule.听Teams can now access expert-backed global employment guidance and听research-driven听insights without leaving their workflows鈥攕upporting听faster, more听confident decisions.

To听further听support learning in the flow of work,听intelligent Q&A in听听now helps employees find information more easily. AI听can deliver instant,听context-aware听responses drawn directly from an organization鈥檚 learning content,听along with relevant links and resources,听so employees can get answers quickly without searching through courses or documentation.听

Unified experiences that adapt to how work gets done听

As HR听tasks听become more embedded in听day-to-day work, experiences need to feel intuitive, connected, and responsive听wherever work happens. In the 1H 2026 release,听麻豆原创 SuccessFactors solutions continue to unify experiences across the suite, giving employees, managers, and HR teams what they need听in听the moment.听

• Connected recruiting and onboarding:听Native integration between听 solutions, , and听听can bring AI-enabled听recruiting, core HR, and onboarding together into a single, continuous experience, helping hiring teams move faster while听maintaining听consistency from candidate through new hire.听

• Tailored experiences,听built faster:听The new听extensibility wizard听can provide guided, step-by-step support for creating custom extensions on听听(麻豆原创 BTP) directly within听麻豆原创听SuccessFactors solutions, making it easier to adapt experiences to unique business needs while preserving governance.听
• Simpler, clearer employee moments:听A redesigned, configurable 401(k) experience听in听听for U.S.听employees helps simplify enrollment and management by clearly explaining employer contributions and guiding deferrals and beneficiary setup, helping employees make informed decisions with confidence.听

Processes designed for clarity, accuracy, and compliance听

In the 1H鈥�2026 release, 麻豆原创 SuccessFactors introduces new capabilities that help organizations bring greater clarity and rigor to pay practices.

With听pay听transparency insights听in the , organizations can analyze compensation patterns and potential pay gaps, supporting transparent, data-driven pay practices in-line with evolving regulatory expectations,听including in the EU.听

Skills governance听for sustainable growth听

Preparing for听what鈥檚听next requires trusted, consistent skills data that organizations can rely on across HR, talent, and workforce planning.

In the 1H鈥�2026 release,听we are听strengthening听the听听with enhanced听skills governance, providing a centralized interface to help manage skills, apply governance standards, and ensure alignment across 麻豆原创 SuccessFactors solutions and partner applications. This helps organizations improve听skills听data quality, maintain consistency at scale, and make more confident,听skills-based听decisions.听

A connected foundation for the future 

This听release听reinforces听麻豆原创鈥檚 continued focus on an intelligent, connected HCM听foundation鈥攐ne designed to evolve with your organization and support confident decisions at every stage of work. By bringing together data, AI, and experiences across the HR lifecycle, these听enhancements help organizations reduce friction today while听laying听the groundwork for听tomorrow.

To explore what鈥檚 included in this release, check out the or watch the overview .

Bianka Woelke is group vice president and head of Application Product Management for 麻豆原创 SuccessFactors.

That鈥檚 why, in Q4 2025, we significantly enhanced the way customers work with AI through new models, sovereign cloud offerings, and partnerships, alongside numerous product updates. Let鈥檚 dive straight in.

麻豆原创-RPT-1 is a novel AI model that is optimized explicitly for predictions on tabular data. While LLMs predict the next word in a text sequence, 麻豆原创-RPT-1 forecasts the next field in a table row; it can interpret relational business data and handle virtually any predictive task. Additionally, as our single, universal AI engine, 麻豆原创-RPT-1 enables customers to simplify their approach to working with AI by eliminating the need for a myriad of narrow AI specialist models, each requiring arduous training, maintenance, and investments. 麻豆原创-RPT-1 also requires 50,000 times less energy, 100,000 fewer GPU FLOPs, and offers up to 3.5 times better predictions and 50 times more speed than state-of-the-art LLMs. Announced at 麻豆原创 TechEd and now available in our generative AI hub, customers can leverage the .

EU AI Cloud is our new full-stack sovereign cloud offering that supports EU data residency and full sovereignty. It makes meeting regulatory and operational requirements easier by giving customers complete control over their infrastructure, platform, and software. Customers can deploy it on 麻豆原创鈥檚 own data centers, on trusted European infrastructure, or as a fully managed solution on-site. Now, European enterprises and public sector organizations can benefit from the latest AI innovations securely, in full compliance with European standards and with the sovereignty and flexibility they need.

We also took steps to simplify our customers鈥� data landscape and preserve the business context of all data. 麻豆原创 Snowflake combines and (麻豆原创 BDC). This partnership enables zero-copy data sharing across Snowflake and 麻豆原创 BDC Connect. Customers using Snowflake can integrate their existing instances with 麻豆原创 BDC for seamless, real-time access to combined, semantically rich 麻豆原创 and non-麻豆原创 data in 麻豆原创 BDC. 麻豆原创 Snowflake will be made generally available in Q1 2026, and 麻豆原创 BDC Connect for Snowflake will be available later in H1 2026.

Furthermore, 麻豆原创鈥檚 generative AI hub includes the latest frontier models from Mistral, OpenAI, Gemini, and Anthropic, allowing customers to implement the model that best suits their specific use cases. The 350 AI features, including Joule Agents, along with the over 2,400 Joule skills, are already delivering unparalleled value to customers鈥攂uilt on AI Foundation in  (麻豆原创 BTP).

Here are some of the highlights from Q4 2025:

• Joule was more integrated than ever in Q4. The bidirectional integration with Microsoft 365 Copilot offers a unified user experience, allowing users to access insights directly within their workflows. Joule for Consultants has enhanced citation visibility, while Joule deep research capability provides users with synthesized explanations for complex inquiries that draw on both internal and external data鈥攕tructured or unstructured鈥攗sing capabilities like Model Context Protocol, document grounding, and Perplexity. Joule analytics center offers customers granular insights into user adoption, and the Joule preview landscape provides a dedicated customer environment for testing and validating software updates before they are released to production. Explore all the new capabilities for Joule in the section below as well as within the specific products.
• 麻豆原创 Business AI for supply chain delivers unprecedented clarity. New analysis capabilities in 麻豆原创 Integrated Business Planning summarize complex optimization, inventory, and forecast results, translating intricate calculations into clear, natural language. The new Production Planning and Operations Agent automates prerequisite checks for releasing production orders by identifying material shortages and suggesting workarounds to prevent delays. There鈥檚 more to discover below.
• 麻豆原创 Business AI for human resources is transforming talent management and reducing administration. The Performance Preparation Agent automates data collection and generates talking points to ensure managers are fully prepared for more impactful one-on-one meetings. Employees can also boost internal mobility by identifying and surfacing hidden skills directly from their resumes. There is so much more to explore; dive into everything below.
• 麻豆原创 Business AI for finance is packed this quarter, with new agents automating more complex processes. The Accounting Accruals Agent helps expedite the period-end close. The International Trade Classification Agent ensures robust compliance for global shipping, and the Cash Management Agent provides unparalleled oversight of cash flow. Joule also now assists with master data governance, analyzes allocation run results, and simplifies risk management tasks. There is just the beginning in finance, so check out everything below.
• With 麻豆原创 Business AI for IT and developers, customers can build, automate, and analyze more quickly and easily than ever. Joule Studio agent builder is in GA and enables users to create custom AI agents that automate complex, end-to-end business processes. To manage this growing landscape, the new AI agent hub in 麻豆原创 LeanIX offers a central dashboard for governing agents. 麻豆原创 is also introducing its own foundational models: 麻豆原创-RPT-1, a new model for structured business data, and 麻豆原创-ABAP-1 to efficiently understand ABAP code. See more below.
• The latest 麻豆原创 Business AI innovations for spend management, procurement, and customer experience are simplifying complex processes and making them more personalized. In spend management, the new Booking Agent simplifies trip planning with tailored recommendations, while the Receipt Analysis Agent ensures accurate expense reports. Procurement customers can use natural language to route demands in 麻豆原创 Ariba and automate the creation of statements of work in 麻豆原创 Fieldglass. In customer experience, marketers can now instantly build reports in 麻豆原创 Emarsys using simple prompts, and service agents receive AI-generated summaries to resolve billing inquiries more efficiently.

Joule

Joule with Microsoft 365 Copilot
General availability

Bidirectional integration between Joule and Microsoft 365 Copilot has been completed. This integration helps deliver a unified user experience across enterprise systems. Users can now access Joule capabilities directly from within Microsoft 365 Copilot, bringing Microsoft-powered insights into the generative AI environment in Joule.

This tight interoperability will help strengthen how organizations work, collaborate, and make decisions within their 麻豆原创 and Microsoft landscapes.

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Joule Analytics Center
General availability

麻豆原创 customers, including IT administrators and development teams, can now utilize the Joule Analytics Center to gain granular, tenant-specific insights into user adoption and engagement. This interactive dashboard enables them to filter and visualize usage data by product, scenario, interaction type, and client, revealing precisely how end-users are leveraging Joule over time. By analyzing these trends and specific usage patterns, organizations can gain a clear understanding of the most impactful scenarios, identify opportunities for improvement, and make data-driven decisions to optimize the overall user experience.

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Joule Preview Landscape
General availability

麻豆原创 customers, including IT administrators and development teams, can also leverage the Joule Preview Landscape, a dedicated environment within 麻豆原创 BTP designed to provide greater visibility and control over software updates. Addressing the previous challenge of deploying new capabilities to all tenants simultaneously, this landscape introduces a crucial validation period. Customers can test and validate new Joule framework updates for two weeks and content updates for four weeks before they are released to production systems. This proactive approach allows teams to thoroughly assess the impact of changes, identify potential issues, and ensure a seamless transition, ultimately empowering them to adopt new features with confidence while avoiding disruptions to live business operations.

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麻豆原创 Joule for Consultants, product enhancements
General availability

麻豆原创 consultants can now benefit from enhanced features within 麻豆原创 Joule for Consultants, designed to improve trust and the quality of answers. The conversational solution offers greater transparency, with improved citation visibility that clearly displays all information sources, including public web searches. We have begun integrating more than 9 TB of 麻豆原创-exclusive, gated content, including the Implementation Guide (IMG), 麻豆原创 Simplification List, and the 麻豆原创 Enterprise Architecture Reference Library. The tool鈥檚 knowledge base is continually updated with the latest information from 麻豆原创 Learning, 麻豆原创 Help, and additional sources, including 麻豆原创 News, the AI Feature Catalogue, and other related public sources.

This provides consultants with a more trustworthy experience by showing exactly where information comes from, while the expanding knowledge base helps them deliver more complete, accurate, and context-rich answers to their queries, thanks to the increased input character count, which has expanded from 2000 to 10000.

We鈥檝e also enabled new functionality 鈥� Console, which provides access to the latest release notes, usage metrics (Admin-Only), an integrated Prompt Library, and system settings (Admin-Only) for both Standard and Administration-level users. Additionally, we have initiated limited pilot programs that enable the direct incorporation of customer-specific documents into 麻豆原创 Joule for Consultants, allowing for more personalized and tailored consulting experiences. These pilots are designed to test the integration of client proprietary information with the broader knowledge base, ensuring that consultants can access both general industry insights and customer-specific data within a single, secure platform.

With 麻豆原创 Joule for Consultants, consultants can save up to 1.5 hours per day through faster, more precise knowledge access, up to 50%* fewer design iterations and subsequent rework, and 14%* faster project execution (see this for details).

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Joule deep research capability
Beta release

麻豆原创 users across various functions can now unlock a profound understanding of their business challenges through Joule deep research capability. This advanced feature enables them to submit complex inquiries and receive not just data, but expertly synthesized explanations and contextual insights, intelligently drawing from both their internal 麻豆原创 data and comprehensive external web sources via Perplexity, all presented directly within their work environment.

This deep interpretive power significantly reduces the effort required for manual data reconciliation and analysis, fostering more confident decision-making and equipping users with a straightforward, actionable narrative for strategic initiatives.

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麻豆原创 Business AI for human resources

Performance Preparation Agent
General availability

The Performance Preparation Agent proactively prepares managers by automating data collection and generating personalized talking points, ensuring they arrive at every employee 1:1 with relevant insights and actionable next steps, such as scheduling follow-ups or requesting peer feedback.

This intelligent preparation significantly simplifies the performance review process, dramatically reducing manager administrative burden by up to 50%* in prep time and 80%* in follow-up efforts, ultimately fostering more impactful discussions that can lead to a 30%* reduction in voluntary turnover.

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麻豆原创 SuccessFactors solutions, AI-assisted skill identification from resume
General availability

Employees leveraging 麻豆原创 SuccessFactors solutions can now effortlessly surface their full capabilities, enriching their Growth Portfolio through an innovative AI-driven skill identification process. By simply uploading a resume, the system intelligently analyzes its content, identifies relevant skills against the universal taxonomy, and presents them for inclusion, revealing previously undocumented “hidden skills” to create a more comprehensive “Whole-Self” profile.

This not only reduces employee time spent on skills profile maintenance by up to 50%* but also significantly enhances internal talent mobility and succession planning, resulting in an up to 10%* increase in internal fill rates and substantial reductions in HR and manager effort for talent-related tasks.

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麻豆原创 SuccessFactors Succession and Development, AI-assisted successor recommendation
General availability

HR leaders and succession planners now gain an unparalleled advantage with this feature that intelligently recommends potential successors. By using generative AI to analyze a rich dataset encompassing skills, competencies, and work experience from Employee Central, Talent Intelligence Hub, and Job Profile Builder, this capability provides a meticulously curated list of candidates.

This not only slashes HR鈥檚 time spent on successor analysis and recommendations by up to 50%*, but critically, it also eliminates subjective biases and surfaces highly qualified nominees who might otherwise be overlooked, thereby reducing critical role vacancies by half and instilling greater confidence through explainable ranking results.

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麻豆原创 SuccessFactors solutions, 麻豆原创 Document AI, embedded edition
General availability

麻豆原创 Document AI is now generally available in 麻豆原创 SuccessFactors Onboarding to boost user efficiency and data precision. This intelligent solution seamlessly automates the critical step of extracting key data 鈥� such as ID type, number, and validity dates 鈥� directly from uploaded national ID documents, discreetly prompting new hires to validate the captured information before final submission.

The result is an up to 15%* acceleration in overall onboarding cycles and a significant 30%* improvement in validation accuracy, collectively delivering error-free data management and enhancing productivity across the entire talent acquisition process.

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Watch the full highlights of the 麻豆原创 SuccessFactors H2 2025 release:

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麻豆原创 Business AI for supply chain

Production Planning and Operations Agent
Beta release

Production planners can significantly accelerate order-to-delivery cycles with the Production Planning and Operations Agent. This agent automates crucial prerequisite checks for releasing production orders, covering material, capacity, and scheduling availability. It identifies material shortages and suggests workarounds, including alternative components or scheduling adjustments. Once all criteria are met, the human planner approves, and the agent releases the production order.

This capability reduces manual work, keeps production moving, and boosts throughput by cutting order processing delays, leading to up to 50%* higher productivity among production supervisors in locating release order information and a 2%* reduction in production downtime losses.

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麻豆原创 Integrated Business Planning, AI-assisted supply optimization analysis
General availability

Supply chain planners leveraging 麻豆原创 Integrated Business Planning gain unprecedented clarity into their complex optimization runs with a new feature for supply optimization analysis.

Powered by Joule, the explanation function helps planners understand issues that arise with optimizer runs by providing the reasons for unfulfilled requirements. Joule can provide explanations for the following types of unmet requirements: 鈥淒emand Not Fully Met,鈥� 鈥淢issed Inventory Targets,鈥� and 鈥淢issed Adjusted Values.鈥�

For instance, planners can ask Joule questions such as, 鈥淲hat is the status of the optimization run for planning area XYZ?鈥� 鈥淲hich products are affected by unfulfilled demand?鈥�, or 鈥淭ell me which locations have unfulfilled inventory targets.鈥�
As a result, planners achieve up to 25%* higher productivity in analyzing planning results, translating into quicker and more confident adjustments to the supply chain model and enhanced overall operational agility.

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麻豆原创 Integrated Business Planning, AI-assisted analysis of inventory optimization results
General availability

Inventory planners utilizing 麻豆原创 Integrated Business Planning are now empowered with profound clarity into their complex inventory optimization results through a new feature designed for detailed analysis of safety stock output. This advanced capability precisely summarizes the rationale behind recommended safety stock levels and any adjustments, translating intricate calculations into accessible human language by highlighting key influences such as demand variability, lead time fluctuations, and service levels, alongside any planner deviations.

This dramatically increases the speed of analysis and adoption of outputs, ensuring both inputs and outcomes align with strategic business goals for working capital management and customer service, ultimately leading to a reduction of up to 25%* in the time inventory planning FTEs spend deciphering optimizer run results.

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麻豆原创 Integration Business Planning, AI-assisted forecast results analysis
General availability

Supply chain planners managing 麻豆原创 Integrated Business Planning can now access advanced forecast results analysis, offering a generative AI summary of statistical forecast details directly within their planning UI. This capability clarifies complex information, such as the chosen algorithm鈥檚 rationale and time series considerations, while providing concrete recommendations for accuracy improvement.

This enhanced insight significantly improves planner visibility, usability, and efficiency, directly leading to an up to 25%* boost in productivity for analyzing forecasting runs and enabling more confident, strategically sound decisions across the supply chain.

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麻豆原创 Integrated Product Development, AI-assisted text generation
General availability

Product managers can utilize AI-assisted text generation capabilities within 麻豆原创 Integrated Product Development to enhance descriptions for new campaigns and ideas. The feature transforms simple text into more creative and compelling narratives, which users can then further enrich or simplify.

By improving the quality of these foundational descriptions, organizations can reduce campaign creation costs by up to 50% and drive a potential 1% increase in revenue from new products.

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Joule with 麻豆原创 Logistics Management
麻豆原创 Early Adopter Care release

Logistics clerks engaging with 麻豆原创 Logistics Management can now harness Joule to streamline their warehouse and transportation planning operations. Through natural language interactions, they can efficiently perform tasks such as querying and creating storage bins, managing freight tendering, and scheduling or inquiring about pickup and delivery documents.

This intuitive, conversational capability fundamentally improves decision-making and streamlines end-to-end logistics processes. It boosts the productivity of supply chain planners by delivering a reduction of up to 30%* in time spent on information search requests and a 20%* reduction in the effort required to navigate to relevant content.

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麻豆原创 Business AI for finance

Accounting Accruals Agent
Beta release

Finance teams can enhance precision and speed during period-end close using the Accounting Accruals Agent. This agent systematically processes accruals by analyzing historical financial data and relevant accounting policies, automatically generating journal entries ready for quick review and confirmation.

This capability not only boosts productivity by reducing the manual effort in calculations by up to 80%* and review/posting by up to 50%*, but it also ensures a timely month-end close, freeing staff for more strategic responsibilities.

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International Trade Classification Agent
Beta release

Global trade compliance teams and product classification specialists now gain a strategic advantage with the International Trade Classification Agent. This AI agent rigorously classifies goods for international shipping by intelligently applying product characteristics against trade regulations, recommending precise customs tariff numbers and commodity codes with transparent rationale for expedited review.

This capability ensures robust compliance, minimizes manual classification errors, and provides an audit-ready decision-making process, resulting in a reduction of up to 50%* in the effort required to manage international trade product classification.

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Cash Management Agent for 麻豆原创 S/4HANA Cloud Public Edition and 麻豆原创 S/4HANA Cloud Private Edition
Beta release

Cash managers across both 麻豆原创 S/4HANA Public Cloud and 麻豆原创 S/4HANA Private Cloud editions gain unparalleled oversight and optimized financial performance with the Cash Management Agent. This agent meticulously gathers opening balances and projected cash flows to forecast precise closing positions. It proactively identifies potential shortages or surpluses in alignment with treasury policies, and for 麻豆原创 S/4HANA Private Cloud Edition users, extends its capabilities to automate bank reconciliations with high accuracy.

The agent then generates and proposes efficient bank transfers and cash optimizations, enabling managers to fund operations effectively, capitalize on investment opportunities, and maximize interest yields. This integrated approach fundamentally streamlines data retrieval and decision-making, resulting in a substantial reduction of up to 70%* in overall cash management effort.

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Change Record Management Agent
Beta release

Product managers and design engineers can accelerate product development and manage engineering changes with greater precision using the Change Record Management Agent. The agent proactively identifies similar change records impacting the same product, suggesting the creation of new change record drafts and initiating the process with recommended next steps.

This capability not only eliminates delays caused by fragmented data and manual checks but also significantly enhances governance and traceability, resulting in an up to 20%* reduction in time to create change requests, a 1% *reduction in time to market new products, and a 2%* reduction in overall engineering change costs.

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麻豆原创 S/4HANA Cloud Private Edition, AI-assisted depreciation key explanation
General availability

Asset accountants operating within 麻豆原创 S/4HANA Cloud Private Edition now get enhanced clarity and efficiency in managing fixed assets. This specialized feature provides user-friendly, natural language explanations of depreciation keys and their underlying calculation procedures, making complex accounting concepts accessible to business users.

The result is increased productivity and satisfaction for accounting teams, enabling faster onboarding, more efficient period-end closing activities, and improved decision-making for future investment planning. Specifically, it reduces the effort required to specify depreciation keys during implementation by up to 75%* and to analyze and address fixed asset queries by up to 90%*.

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麻豆原创 S/4HANA Cloud Private Edition, Joule for Developers, ABAP AI capabilities
General availability

ABAP developers working within 麻豆原创 S/4HANA Cloud Private Edition find a specialized copilot in Joule that鈥檚 uniquely trained on 麻豆原创 data and processes. Joule accelerates development tasks by providing real-time explanations of ABAP objects, predicting and generating subsequent lines of code, and supporting full-stack ABAP Cloud scenarios directly within ABAP Development Tools for Eclipse.

This sophisticated assistance can significantly reduce the time and effort required for coding by up to 20%* and for testing by up to 25%*, ultimately boosting developer productivity, enhancing clean core implementations, and delivering a 6.6%* faster time to realized value.

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麻豆原创 Master Data Governance on 麻豆原创 S/4HANA Cloud Private Edition, AI-assisted central governance
General availability

Sales managers, procurement specialists, and other business users utilizing 麻豆原创 Master Data Governance on 麻豆原创 S/4HANA Cloud Private Edition can now streamline master data tasks with Joule. This capability enables them to interact with Master Data Governance functions using natural language processing, allowing for seamless search, display, submission of new business partners, modification of existing ones, and tracking of governance process status, without requiring extensive technical knowledge.

This approach significantly increases flexibility and ease of data entry, resulting in a reduction of up to 85%* in effort for managing master data and a decrease of up to 10%* in annual operating income loss due to delayed or incorrect updates.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted allocation run results
General availability

Business analysts and cost accountants now gain immediate clarity into their financial data with a new Joule feature for allocation run results. This capability allows them to efficiently view amounts allocated across diverse objects, including cost centers, profitability objects, or profit centers, and quickly navigate to detailed run reports for in-depth review.

This streamlined access reduces the effort of synthesizing data from multiple sources, provides rapid insights into complex cost allocations, and enables swift assessment of potential impacts from organizational changes, resulting in an up to 70%* decrease in time spent on allocation result analysis and up to 40%* faster resolution of allocation issues.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted hands-free production order management
General availability

Production supervisors working in 麻豆原创 S/4HANA Cloud Public Edition can now benefit from hands-free production order management. By leveraging natural language queries, supervisors can effortlessly retrieve order details and manage operations without physical interaction.

This advancement significantly enhances operational efficiency, facilitates rapid responsiveness to unplanned demands, and ensures more reliable production order processing, ultimately leading to an up to 50%* increase in supervisor productivity and a 2%* reduction in production downtime losses.

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Joule with 麻豆原创 Risk and Assurance Management
General availability

Compliance managers and risk specialists working with 麻豆原创 Risk and Assurance Management can significantly simplify tasks through Joule. This integration allows business users to intuitively navigate the system and access critical enablement content using natural language, enabling them to quickly find answers and perform work-related tasks without extensive prior knowledge.

This streamlined experience fosters greater user satisfaction and frees up valuable time for strategic activities, resulting in a reduction of up to 50%* in time spent on informational searches and a corresponding decrease of up to 50%* in time navigating and performing tasks within the system.

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麻豆原创 Business AI for spend management

Booking Agent
General availability

Business travelers enjoy a significantly streamlined and personalized booking experience through the Booking Agent. This Joule Agent proactively delivers tailored flight and hotel recommendations by analyzing individual traveler preferences, company travel policies, and budget constraints, all accessible via chat-based interaction.

This not only enhances user satisfaction and supports sustainable choices but also reduces the time spent booking a trip by up to 11.5%*, while simultaneously improving policy compliance and granting organizations superior oversight and control over travel expenditures.

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Receipt Analysis Agent
麻豆原创 Early Adopter Care release

Employees submitting business expenses now experience unprecedented accuracy and efficiency with ExpenseIt, powered by the Receipt Analysis Agent. This AI agent leverages a comprehensive suite of data, including maps, vendor databases, web searches, and Concur Travel itineraries, to itemize and categorize receipt data precisely.

By reasoning both the receipt content and external context, it creates highly accurate expense entries, dramatically reducing the time spent manually managing and editing them. This ensures ExpenseIt gets it right the first time, reducing the need for send-backs and resulting in a potential up to 19%* reduction in the time required to generate expense items.

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麻豆原创 Business AI for procurement

麻豆原创 Ariba Intake Management, AI-assisted demand intake
General availability

Employees creating procurement demands within 麻豆原创 Ariba Intake Management now experience a smarter, more efficient process with the Demand Intake feature. By simply using natural language to articulate their needs, employees can rely on the AI to intelligently assess their requests and route them to the most appropriate procurement or buying channel.

This innovative approach delivers up to 12%* productivity gain for casual users creating requisitions, while significantly reducing the risk of maverick spending with a 5%* improvement in non-compliant spend, and further streamlining operations with a 10%* reduction in purchase order processing time.

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麻豆原创 Fieldglass Services Procurement, AI-assisted SOW deliverables creation
General availability

Procurement professionals and buyers using 麻豆原创 Fieldglass can now streamline the creation of comprehensive statements of work (SOWs). This feature analyzes project scope and existing data to automate critical SOW components, automatically drafting structured event hierarchies, and generating precise, relevant deliverables.

By automating these time-consuming tasks, this integrated approach reduces manual effort, improves data consistency, and ensures deliverables are closely aligned with project goals, enabling businesses to achieve up to a 70%* reduction in manual creation time and an up to 50%* reduction in poor outcomes tied to inadequate SOWs.

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麻豆原创 Business AI for customer experience

麻豆原创 Emarsys Customer Engagement, AI-assisted report builder
General availability

Marketers have a powerful new way to create individualized reports with the AI-assisted report builder in 麻豆原创 Emarsys Customer Engagement. Using simple user prompts, they can query underlying datasets to instantly generate custom reports and visualizations, eliminating the need for specialized BI skills or technical support. This streamlined approach to flexible reporting enables marketing teams to reduce the time spent on campaign performance analysis by up to 67%*, allowing them to iterate quickly and communicate results more effectively throughout the organization.

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麻豆原创 Service Cloud Version 2, AI-assisted premise billed consumption summary
General availability

Customer service agents using 麻豆原创 Service Cloud Version 2 can more effectively resolve customer billing inquiries with the AI-assisted premise billed consumption summary. This feature automatically analyzes the latest 12 billing cycles, correlates consumption data with temperature trends, and generates a concise, human-readable summary.

By providing agents with immediate, actionable insights that eliminate the need for manual analysis, it helps increase the speed of issue resolution and reduces the average time to summarize business objects by up to 90%*.

麻豆原创 Business AI for IT and developers

Joule studio, agent builder
General availability

Business and IT professionals can now use Joule Studio鈥檚 agent builder to create powerful AI agents capable of automating highly complex business processes. This tool allows them to build agents that can plan, reason, and dynamically orchestrate multi-step workflows across both 麻豆原创 and non-麻豆原创 systems, effectively tackling ambiguity where standard automation falls short.

With Joule Studio agent builder, organizations have the potential to reduce the time spent on frequent business tasks by up to 40%* and cut the time needed to build and deploy custom agents by up to 35%*, significantly improving decision-making speed and operational efficiency.

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Generative AI Hub in AI Foundation, enhancements
General availability

麻豆原创-RPT-1, 麻豆原创鈥檚 first enterprise relational foundation model

麻豆原创 introduced its first enterprise relational foundation model, 麻豆原创-RPT-1, accompanied by a no-code testing playground environment.

Unlike large language models (LLMs), 麻豆原创-RPT-1 is a foundation model that establishes a new category of AI models specifically designed for relational and structured business data. 麻豆原创-RPT-1 comes pretrained, significantly reducing the need for customers to handle time-consuming and costly model training tasks that are typically required with narrow AI models. It delivers reliable, fact-based predictions by grounding responses in verified enterprise data, providing the accuracy and dependability that critical business operations require.

麻豆原创-RPT-1 addresses analytical and predictive tasks through in-context learning, enabling users to perform classification and regression on tabular data by providing example records directly within the API call. The model can be consumed as a ready-to-use endpoint and integrated into applications and business processes. The initial release supports common predictive scenarios, including binary and multiclass classification, as well as numerical regression.

麻豆原创 also offers an interactive, web-based testing environment, 麻豆原创-RPT playground, where customers can experience the in-context learning capabilities at no cost, utilizing their own data or 麻豆原创-provided example datasets, without any coding.

麻豆原创-RPT-1 is available on the generative AI hub in AI Foundation for productive use. It comes in two flavors: 麻豆原创-RPT-1-small for ultra-fast predictions and high throughput, and 麻豆原创-RPT-1-large for maximum accuracy.

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麻豆原创-ABAP-1 foundation model

To empower customers and partners to build custom, AI-driven developer productivity use cases, the 麻豆原创-ABAP-1 foundation model is now available on the generative AI hub. Trained on more than 250 million lines of ABAP code, 30 million lines of CDS code, and extensive technical documentation, 麻豆原创-ABAP-1 is purpose-built to efficiently understand, explain, and give immediate access to ABAP code knowledge, best practices, and latest innovations.

Customers can try the new model for free as part of the generative AI hub trial. Additional capabilities will be released in 2026.

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Prompt Optimizer

Developed in close collaboration with Not Diamond, the prompt optimizer helps automate and accelerate the creation of effective AI prompts across leading models. This frees users to adapt their prompts to any model for their use cases without the manual effort of rewriting prompts.

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Orchestration registry

Developers can now manage the lifecycle of orchestration workflow configurations, including saving, versioning, and deleting orchestration configurations.

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New models available

New models are supported, including Perplexity Sonar, Sonar Pro, Anthropic Claude 4.5 Sonnet, Anthropic Claude 4.5 Haiku, Cohere Command A Reasoning, and Gemini 2.5 Flash Lite.

For more information on new and deprecated models,

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麻豆原创 Document AI, enhancements
General availability

Vision-enabled information extraction

Schema administrators can now choose between . When enabled, documents are processed by a multimodal model that interprets visual elements, such as hazard pictograms, stamps, signatures, logos, charts, and labels, in conjunction with the text. This improves accuracy for visually rich documents, such as Safety Data Sheets (SDS) or Compliance Declarations. It improves data completeness and accuracy, reduces manual tagging and verification by automating the extraction of visual elements, and optimizes cost and performance with per-schema control.

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Processing of e-mail attachments

Users can now process e-mail attachments alongside or separately from the e-mail body, providing extensive flexibility and enhancing data extraction.

Get started with and .

Document workflows

Users can now quickly and easily define multistep workflows to process documents according to their specific needs. The new Workflows feature allows users to combine basic capabilities of 麻豆原创 Document AI to automate and streamline complex tasks.

Workflows can be triggered automatically via inbound channels, with no need for additional tools or integrations. Alternatively, users can upload a file and start the workflow manually. Workflows extend beyond extraction and classification, providing support for tasks such as e-mail processing, content-based routing, and automated processing.

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Built-in transport management

麻豆原创 Document AI provides an Integration with 麻豆原创 Cloud Transport Management, allowing users to leverage the Transports feature to export and import their schemas across their 麻豆原创 Document AI service instances 鈥� for example, development, quality, and production. It ensures that schemas and workflows are consistent across instances, facilitating better collaboration among teams and systems.

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麻豆原创 Cloud ALM, AI-assisted requirement generation
General availability

Consultants can now automatically generate high-quality business requirements directly from Fit-to-Standard workshop transcripts. By analyzing discussion content, this new feature in 麻豆原创 Cloud ALM populates a predefined template. It integrates 麻豆原创 Best Practices to suggest solution proposals, shifting the consultant鈥檚 focus from manual transcription to strategic review and refinement.

This automation reduces the time spent creating requirements by up to 50%* and the time needed for subsequent user story creation by up to 20%*, significantly accelerating project documentation.

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麻豆原创 Micro-App Hub, AI-assisted user learning, and change management
Early Adopter Care program

Learning specialists and content creators can now streamline their entire 麻豆原创 user-learning lifecycle, accelerate adoption, and reduce costs with 麻豆原创 Micro-App Hub. By connecting with 麻豆原创 Signavio and 麻豆原创 Cloud ALM, this feature analyzes project scope, identifies learning needs, and automatically generates tailored, business-aligned training content for every user role.

This not only produces up-to-date materials quickly for various authoring and learning tools but also dramatically cuts the time for initial learning needs assessment by up to 60%* and content development by up to 50%*, ensuring faster onboarding and higher accuracy by aligning learning with 麻豆原创 updates.

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麻豆原创 Business AI for industries

Utilities Customer Self-Service Agent
General availability

Utilities organizations can with the Utilities Customer Self-Service Agent. This AI agent provides fast, personalized answers in multiple languages. It provides a deep understanding of customer context, including contracts, tariffs, and consumption data, through its integration with 麻豆原创 S/4HANA Cloud Private Edition.

Designed to address industry shifts such as deregulation and prosumer growth, it efficiently handles complex customer interactions, resulting in a reduction of up to 90%* in the average cost of AI-handled contacts and a decrease of up to 60%* in overall customer service operational costs.

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Tender Analysis Agent
General availability

Sales and bid management teams can optimize their response process with the Tender Analysis Agent. This agent automates the evaluation of complex tender and RFQ documents by extracting critical product requirements, flagging potential risks or policy gaps, and suggesting optimized configurations based on predefined company standards.

This automation reduces manual effort and accelerates sales cycles, helping businesses achieve up to a 1%* improvement in operating margin from personalized products, a 0.5%* increase in cross-sell/up-sell revenue, and a 5% reduction in sales FTEs per billion in revenue.

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麻豆原创 Sports One, AI-assisted scouting
General availability

Scouts using 麻豆原创 Sports One now have access to unparalleled efficiency in player assessment, thanks to AI-assisted scouting. This capability allows them to rapidly digest complex scouting reports and match analyses through generated summaries in Joule, as well as pose specific questions using natural language to extract precise answers.

This significantly reduces the need for extensive documentation, liberating substantial time and resources, which translates to a decrease of up to 75%* in the effort and cost associated with summarizing player scouting reports, directly supporting sporting directors with enhanced decision-making.

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麻豆原创 Information Collaboration Hub for Life Sciences, AI-assisted error analysis
General availability

Supply chain planners can quickly resolve complex issues in serialization data exchange with the error analysis feature in 麻豆原创 Information Collaboration Hub for Life Sciences. The tool automatically classifies errors, provides easy-to-understand descriptions, and proposes resolution steps, helping planners identify root causes and manage exceptions without needing technical support.

Organizations can increase the productivity of their operational support teams by up to 25%* and lower distribution costs by up to 5%* through minimizing disruptions.

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麻豆原创 Batch Release Hub for Life Sciences, AI-assisted batch release processing
麻豆原创 Early Adopter Care program

For users of 麻豆原创 Batch Release Hub for Life Sciences, making swift, informed decisions about batch releases are becoming significantly more efficient with AI-assisted batch release processing. Through the Joule interface, this feature streamlines access to essential data and provides an organized view of worklist items, clearly highlighting releases that require detailed investigations due to blocked checks.

The conversational search capability further simplifies finding product documentation, ensuring critical issues are addressed promptly, and past insights are readily available for current decisions, ultimately reducing the time needed to access vital batch release information by up to 90%*.

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麻豆原创 Business AI for business transformation management

Dashboard Analyzer Agent for 麻豆原创 Signavio
Beta release

Business process professionals utilizing the Dashboard Analyzer Agent can transform 麻豆原创 Signavio dashboards into intelligent, prescriptive tools. This AI agent autonomously interprets complex event logs and KPIs to identify inefficiencies, explain root causes, and generate actionable recommendations in natural language.

By embedding these AI-driven insights directly into the user鈥檚 workflow, organizations can achieve a reduction of up to 80%* in the time required to access process mining insights and significantly reduce the value erosion caused by poor data interpretation.

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Screen Guide Agent for 麻豆原创 Signavio
Beta release

Business users and process analysts can accelerate their understanding and adoption of the 麻豆原创 Signavio platform with the Screen Guide Agent. This AI agent provides dynamic, on-screen guidance by explaining the purpose of different features, highlighting the most relevant data, and offering next-step recommendations in natural language.

By transforming complex screens into intuitive experiences, organizations can reduce new user onboarding costs by up to 50%* and cut the time needed to interpret a page by up to 30%*, empowering users of all levels to work more confidently and productively.

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Workspace Administration Agent for 麻豆原创 Signavio
Beta release

Administrators and workspace managers can now significantly simplify and expedite user onboarding in 麻豆原创 Signavio with the Workspace Administration Agent. This AI agent automates the process of creating users in bulk, assigning correct roles and licenses, and granting immediate access to necessary dashboards and collaborative workspaces.

By implementing this tool, organizations can achieve a reduction of up to 90%* in the time it takes to provide user access rights, ensuring new team members can contribute from day one.

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Value Case Creation Agent for 麻豆原创 Signavio
Beta release

Process improvement leaders and business analysts can translate raw process insights into compelling, data-driven business cases with the Value Case Creation Agent. This AI agent automatically identifies operational inefficiencies, quantifies their potential financial impact, and generates editable value case drafts that summarize the problem and expected benefits.

By streamlining the justification for transformation initiatives, organizations can reduce the time required to create a value case by up to 70%* and decrease the erosion of value from inaction, ensuring that improvement efforts are prioritized based on clear ROI.

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Process Content Recommender Agent for 麻豆原创 Signavio
Beta release

Enterprise architects and process managers can rely on the Process Content Recommender Agent for intelligent guidance on specific process questions within 麻豆原创 Signavio. By reasoning over thousands of best practices from both 麻豆原创 and internal custom models, the agent delivers a structured, prioritized list of tailored content, including relevant KPIs and value accelerators.

This capability enables organizations to reduce content search time by up to 50%* and improve the productivity of their business process management resources, allowing teams to make faster, data-driven decisions on their transformation initiatives.

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麻豆原创 Signavio Process Transformation Manager, AI-assisted insights description generator
General availability

Analysts working with 麻豆原创 Signavio Process Transformation Manager can collaborate more effectively and accelerate decision-making through this new integrated feature. It automatically generates clear, consistent, and business-user-friendly descriptions for insights derived from 麻豆原创 Signavio Process Intelligence.

Analysts can save significant manual effort by transforming complex meta-model terms into readily understandable language, which improves readability and stakeholder alignment. The result is an up to 80%* reduction in time spent translating meta-model terms and an up to 5%* improvement in overall business user productivity.

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麻豆原创 Signavio solutions, AI-assisted transformation advisory, initiative builder
General availability

Transformation leads can now translate high-level business documents into concrete, actionable projects using the initiative builder in 麻豆原创 Signavio solutions. By uploading strategic reports, operational reviews, or financial statements, users can automatically extract key challenges and instantly convert them into pre-defined initiatives within the 麻豆原创 Signavio Process Transformation Manager.

This ensures that transformation efforts are directly aligned with company goals, dramatically improving efficiency by reducing the manual effort required to find relevant insights by up to 75%* and accelerating overall execution.

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麻豆原创 LeanIX, AI Agent Hub
General availability

The AI Agent Hub enables CIOs and business leaders to view their entire AI agent landscape immediately. From a single dashboard, they can understand where agents are deployed, which processes they interact with, and how agents are performing.

This enables teams to evaluate effectiveness, identify redundancies, and manage AI as they would any other enterprise asset: aligned to outcomes, governed by policy, and continuously optimized for performance.

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WalkMe, 麻豆原创 Joule Action Bar
麻豆原创 Early Adopter Care release

Employees working across different enterprise systems can leverage the Joule action bar, a proactive AI assistant powered by WalkMe. This intelligent overlay operates seamlessly across both 麻豆原创 and non-麻豆原创 applications, interpreting on-screen context to understand user activities and deliver real-time insights or recommend the subsequent best actions directly within their workflow.

By offering a unified and intuitive AI experience that anticipates user needs, the action bar helps people work faster and more efficiently, reducing friction and harmonizing tasks across all systems.

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Philipp Herzig is CTO of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks, and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, expressor implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

To navigate AI鈥檚 evolution, organizations need to understand that it鈥檚 no longer just a question of “What can AI do?” but “How do we set our organization up for success with AI? How do we build for it? What problems do I solve with which models? How do we govern it?”

Looking ahead to five critical themes that will define enterprise AI in 2026, these present both opportunities and challenges for organizations. Let’s dive in.

1. New categories of AI foundation models unlock enterprise value

Advances in generative AI stem from breakthroughs in 鈥渇oundation models,鈥� massive neural networks trained on vast amounts of data that can be adapted to a wide range of tasks.

Large language models (LLMs) were the first wave of foundation models at scale. General-purpose LLMs, trained on the equivalent of all the text on the internet, opened the door to many value-adding use cases, including summarizing documents, writing code, and powering applications like ChatGPT and Claude. Over the last few years, we have already seen the foundation model approach applied to other domains, such as video creation and voice.

In 2026, specialized foundation models optimized for specific data types and domains will power the high-value enterprise AI use cases. Video generation models have already shown that models grounded in real-world physics data can reason about scenes and physical dynamics. Emerging world models demonstrate that simulating the physical world unlocks new possibilities in simulation, synthetic training data, and digital twins. Vision-language-action models demonstrate that robot-specific foundation models can generalize to new tasks and environments, enabling the transformation of web-scale knowledge into real-world actions in logistics and manufacturing.

In the enterprise domain, a similar shift is underway for structured data found in databases and transactional business software. While LLMs are impressive across many enterprise use cases, they cannot handle tasks like numerical predictions, such as inferring a delivery date or supplier risk score. However, work on relational foundation models shows that training on structured datasets鈥攆or example, data in tables, rather than generic text or images from the internet鈥攃an deliver high predictive accuracy without the tedious feature engineering and training required in classical machine learning. This means organizations can deploy predictive models in days, not months. Recent launches of relational foundation models, such as 麻豆原创-RPT-1, Kumo, and DistilLabs, highlight how new models can directly support use cases like forecasting, anomaly detection, and optimization across ERP, finance, manufacturing, and supply chain scenarios.

In 2026, these specialized models are expected to scale to deliver superior performance and economics for structured business tasks, surpassing general-purpose LLMs and state-of-the-art machine learning algorithms. These models will emerge as the workhorses behind high-value enterprise tasks.

2. Software evolves toward AI-native architecture

AI has seen various approaches create value over the decades, from the first rules-based expert systems to probabilistic deep learning and the recent explosion in generative AI. In 2026, organizations will shift from enhancing existing AI applications and processes to AI-native architectures, which will fully realize the promise of modern AI.

AI-native architecture adds a continuously learning, agentic intelligence layer on top of deterministic systems, enabling applications to become intent-driven, context-aware, and self-improving rather than being statically coded around fixed workflows. Agentic systems will still only be as good as the context layer they can reliably retrieve and ground on. Here, organizations should invest in truly comprehensive, semantically rich knowledge graphs that provide a scalable source of context, making AI-native software dependable and self-improving.

Enterprise applications will increasingly be built natively around AI capabilities, featuring user experiences designed for multi-model, natural language interaction; AI agents reasoning through complex processes; and a foundation managing foundation models, services, and a knowledge graph capturing semantically rich business data.听AI-native architecture also enables more employees to create apps鈥攕uch as smaller, ad-hoc productivity applications鈥攊n a matter of minutes without straining IT.听

AI-native architecture builds on, and even requires, established SaaS principles and investments in modern cloud applications. The technical term for combining probabilistic, adaptive AI models with deterministic systems of record is called neurosymbolic AI. It brings together AI鈥檚 best capabilities to adapt with reliable, governable, and deterministic processes. Next-gen applications will not just have AI bolted on; they鈥檒l be built around AI at their core. This means combining reasoning, business rules, and data to deliver insights and automation seamlessly. Imagine ERP systems that proactively flag anomalies, recommend actions, and even execute workflows autonomously鈥攁ll while staying aligned with company policies and regulations.

3. Agentic governance becomes mission-critical

Over the past two to three years, generative AI has introduced a wave of value-added use cases. These use cases were largely based on users sending a prompt to a model, receiving a response, and then interacting with the model again.

Last year saw the start of the next wave of innovation: AI agents capable of planning and iteratively reasoning through multi-step tasks, including selecting tools, self-reflecting on progress, and collaborating with other AI agents. These advanced AI agents promise to tackle complex business processes that were previously immune to automation, such as analyzing myriad documents, records, and policies to or .

However, the proliferation of AI agents, many of which handle critical tasks and sensitive data, demands the development of new capabilities. Agentic governance will emerge as a critical capability as organizations deploy hundreds of specialized AI agents. The “agent sprawl” challenge will mirror previous shadow IT crises, but with higher stakes given agents’ autonomous decision-making capabilities.

Forward-thinking enterprises will establish comprehensive governance frameworks addressing five dimensions: agent lifecycle management (version control, testing protocols, deployment approval, retirement procedures); observability and auditability (agent inventory, logging, reasoning paths, and action traces); policy enforcement (embedding business rules, regulatory constraints, and ethical guidelines into agent execution); human-agent collaboration models (defining autonomy boundaries, approval requirements, and escalation pathways); and performance monitoring (tracking accuracy, efficiency, cost, and business impact).

The organizational shift will prove profound鈥攆rom viewing AI as an independent tool to managing agents as digital coworkers requiring onboarding, performance reviews, and continuous improvement. HR and IT functions will collaborate on “digital workforce management” as organizations treat agentic governance as seriously as they do traditional workforce oversight.

4. Intent-driven ERP and generative UI emerge as a new user experience

Consumers are becoming increasingly familiar with computer interactions requiring prompts in natural language, voice, and even images and gestures. At the same time, generative AI鈥檚 ability to create text, graphs, code, and HTML on the fly is improving rapidly. In parallel, AI agents enable users to simply express their intentions, allowing the agent to determine how to work toward achieving that goal.

These advancements open the door to varied and entirely new modalities for users to work with enterprise software, as well as 鈥渘o-app ERP鈥� experiences. For example, to book a customer visit, a worker typically needs to open an analytics application to review the account, look in the CRM system to retrieve the customer鈥檚 address, and then navigate to another application to book travel, among other tasks. 

In 2026, we will see 鈥済en UI鈥� experiences increasingly surface via digital assistants, relieving users from the need to navigate between multiple applications and perform manual tasks. With time, AI will allow the user to simply express the intent: 鈥淧repare a trip to my customer with the most leads.鈥� From here, an AI agent will plan out the steps and required systems, interacting with the user to confirm travel details while dynamically generating analytical graphs and briefing material in the window. As AI agents develop stronger calculation and prediction tools, users will be able to “speak to their data” more naturally, with agents making data-based decisions in the background. To be clear, interactions with agents will extend far beyond a chat box; organizations will enjoy rich visualizations, complete workflows, and the ability to build hyper-personalized apps with just a few commands.

The user interface will not disappear. No-app ERP experiences and autonomous agents require the same foundational substrate that humans rely on for their daily work: structured workflows, security, governance, and business logic defined in business applications. The difference is that agents consume these primitives programmatically at scale, not only through a GUI, and humans can interact with these agents via natural language without ever needing to open the application.

These capabilities will usher in a new paradigm for human-AI collaboration and productivity in the workplace. Personalized experiences and adaptive workflows across applications and data sources will lower adoption barriers. This ability to focus solely on achieving a user鈥檚 intention, regardless of the interaction modality and underlying systems, will drive return on investment (ROI) in AI and enterprise software.

5. Deglobalization drives sovereign AI offerings

AI sparked debates about digital sovereignty among nations due to AI鈥檚 potential impact on everything from scientific discovery and national security to economic productivity and even culture. Events in geopolitics, such as supply chain disruptions caused by tariffs and war, have only intensified the urgency that many nations and organizations feel to become digitally sovereign.

Digital sovereignty has two broad definitions. First, digital sovereignty is an information security designation governing data storage and access, such as U.S. FedRAMP and German VSA, required to process sensitive governmental data in a 鈥渟overeign cloud.鈥� Second, and more broadly, sovereignty refers to the provenance of physical assets, intellectual property, legal jurisdiction, and services along the cloud stack. For example, does an application utilize an AI model created in Europe, the U.S., or China, and is the data center geographically isolated?听

The high stakes, geopolitical uncertainty, and complexity of 鈥渟overeign AI鈥� will lead enterprises to increasingly demand AI and cloud solutions that are simultaneously cutting-edge, flexible, and fully sovereign. This intensifies the shift from globalized one-size-fits-all cloud to regionally compliant, AI-powered enterprise platforms. At the same time, governments will continue to refine their national AI strategies to invest in areas along the stack where they can compete and create value.

Executing on the 2026 AI themes

In 2026, AI is poised to move from a supporting tool to a fundamental pillar of the enterprise. This shift is driven by a convergence of defining trends鈥攊ncluding increasingly capable agents, generative UI, and AI-native architecture鈥攖hat push AI from the application layer and into the very core of business operations.

Organizations that thrive will be those that recognize this shift and build an enterprise that is purpose-built for AI: establishing robust governance to manage a new, collaborative workforce of humans and AI agents; embracing gen UI to lower adoption barriers and an intent-driven user experience that helps employees interact naturally; seeking out specialized foundation models that are precisely tuned for enterprise use cases to drive business value; and, finally, building applications natively around AI that combine reasoning, business rules, and data, delivering proactive insights and automation.

However, in 2026, organizations will still need high-quality, connected data. Data siloes severely limit the effectiveness of AI. As mentioned, AI-native architecture requires established investments in modern cloud applications that harmonize data across the entire business鈥攂ecause unified data means AI鈥檚 outcomes are more accurate and relevant.

Jonathan von Rueden is chief AI officer at 麻豆原创 SE.
Walter Sun is senior vice president and global head of AI for 麻豆原创 Business AI at 麻豆原创.
Sean Kask is vice president and head of AI Strategy for 麻豆原创 Business AI at 麻豆原创.

Personalization in AI is no longer an innovation layer; it is becoming a foundational expectation. Whether it鈥檚 for driving operational excellence, improving customer experiences, or enabling faster decision-making, organizations are increasingly prioritizing AI that understands their reality.

Generic AI models are designed to be broadly applicable, but that also makes them inherently limited. These models often fail to account for the specific nuances of a business, resulting in lower accuracy, generic insights, and poor cross-functional scalability. Their one-size-fits-all nature makes them difficult to adapt across industries with diverse regulatory needs, data types, and operational complexities.

In critical industries, where precision, compliance, and context are non-negotiable, relying on generic models can lead to inefficiencies and missed opportunities. Additionally, integrating these models into enterprise governance, security, and compliance workflows becomes an uphill task. The result? Underperformance and a growing recognition that one-size-fits-all AI is not built for the complexity of enterprise needs.

This is why more enterprises are investing in differentiated innovations with AI solutions designed from the ground up to serve specific business goals.

A clear example of this is our partnership with . Managing close to 1 million invoices annually across more than 40,000 contracts, the company faced a complex, manual billing process. Together, we used 麻豆原创 Business Technology Platform (麻豆原创 BTP) and generative AI to create a compliant, intuitive application that allows account executives to manage invoicing directly and navigate rate cards and contract terms without relying heavily on specialist teams.

The results are tangible. Billing is faster and more accurate, the user experience has improved, and commercial teams can focus more on clients instead of operational tasks. By year-end, billing efficiency is expected to improve by 32 percent and setup times halved. Much of the manual work has been replaced by an intelligent, automated platform.

Where it鈥檚 working: Sector-level transformation

Customer-specific AI applications are transforming industries by shaping intelligence around the specific data, processes, and challenges each sector faces.

In manufacturing, the impact of customer-specific AI applications is evident in how companies are streamlining complex operational processes. For instance, our team developed a solution for Henkel to support their financial supply chain management deduction and dispute management indexing process. This solution automates the analysis and indexing of claim documents received from customers, embedding advanced AI capabilities directly into the daily workflows of dispute management users. The result is faster, more accurate claim case creation, improved efficiency, and greater agility in handling disputes.

In oil and gas, AI models trained on geological data, equipment logs, and environmental variables are improving drilling forecasts and enabling proactive maintenance, enhancing both safety and energy efficiency. The automotive industry is seeing similar gains, with AI supporting predictive maintenance, autonomous driving systems, and real-time diagnostics, while also delivering personalized in-car experiences. Retailers are leveraging AI that adapts to regional buying patterns and live sales data, allowing for sharper demand forecasts, localized inventory planning, and more relevant promotions that reduce waste.

Even government agencies are finding value in context-aware AI, automating routine processes, prioritizing citizen requests, and designing policies with greater precision to deliver faster, more effective public services.

Across these examples, the pattern is clear: AI that understands the context in which it operates drives smarter decisions, more efficient operations, and better outcomes for both organizations and the people they serve.

麻豆原创鈥檚 vision: Building enterprise-grade customer-specific AI applications

麻豆原创 is at the forefront of this shift toward enterprise-grade personalized AI. The company鈥檚 vision is rooted in creating AI that is not experimental, but enterprise-ready.

Rather than building standalone solutions, 麻豆原创 embeds AI directly into core business processes across finance, HR, supply chain, and more. Through co-innovation with customers and partners, 麻豆原创 is working to make every AI solution technically robust and aligned with real-world use cases.

For AI to drive true enterprise transformation, it needs to be designed in and not bolted on. That means working closely with domain experts, aligning with compliance standards, and constantly tuning models based on real-time feedback. Customer-specific AI applications are not just about code; they are about collaboration, trust, and long-term value.

Our approach is to empower organizations to build AI that mirrors their structure, culture, and customers–making it more relevant, reliable, and responsible.

The time to scale is now

Organizations that want to stay competitive can no longer afford to treat AI as a side project. The era of experimentation is over. This is the time to scale AI that works for you intelligently, responsibly, and at speed. Customer-specific AI applications are not tech features but are strategic enablers of innovation, efficiency, and differentiation.

The future belongs to those who can scale personalization without sacrificing performance. It鈥檚 time to build with AI that knows your business.

Sindhu Gangadharan is head of Customer Innovation Services at 麻豆原创.

The International Trade Classification Agent and Cash Management Agent optimize finance, while the Bid Analysis Agent and Receipt Analysis Agent clarify spending. The Production Planning and Operations Agent, Change Record Management Agent, and Supplier Onboarding Agent handle supply chain logistics. In human resources, the HR Service Agent, People Intelligence Agent, and Career and Talent Development Agent level up your workforce, while customer-facing teams get support from the Digital Service Agent. Finally, the Utilities Customer Self-Service Agent cut service costs, while the Process Content Recommender Agent and Workspace Administration Agent accelerate business-wide transformation and onboarding.

With the growing number of Joule Agents, we want to make it as easy as possible for our customers to engage with AI. That is why we鈥檙e introducing AI Assistants in Joule as a grouping concept. This means that the agents are role-aware depending on the user logged onto the system, whereas the assistants will be more abstract, coarse-grained group around a semantically closely aligned set of agents. While Joule manages the tasks, the assistants will initiate sub threads for more targeted conversations when mentioned. If the user becomes lost in the details or does not receive the expected response from the selected assistant, Joule can step in.

Want to learn more? The has all innovations announced at 麻豆原创 Connect.

In Q3, 麻豆原创 received its , which means customers get responsible AI systems, such as Joule, 麻豆原创 AI Core, and more, that can be confidently integrated into their operations. This certification assures that our AI solutions meet the highest industry standards for ethics, security, and compliance, including adherence to regulations like the EU AI Act.

麻豆原创 Business AI is fully on track to have more than 400 AI features, including Joule Agents, by the end of 2025 that will deliver unparalleled business value to customers. These features are being built with AI Foundation on  (麻豆原创 BTP) and will add to the over 300 existing AI scenarios and 1,900 Joule skills.

Here are some of the highlights from Q3 2025:

• 麻豆原创 Business AI for supply chain is ensuring the entire supply chain runs smoothly while boosting productivity. The new Shop Floor Supervisor Agent proactively manages factory floor disruptions by analyzing issues and recommending actions. AI-assisted mobile execution in 麻豆原创 Service and Asset Manager lets customers in the field use voice commands for hands-free job documentation. 麻豆原创 Integrated Business Planning provides clear summaries for complex statistical results and safety stock calculations, to name a few. There is much more to check out about 麻豆原创 Business AI for supply chain below.
• 麻豆原创 Business AI for finance has always been packed, and this quarter is no exception. We are boosting productivity and simplifying complex tasks through embedded AI. Joule has new capabilities that let customers interactively verify supplier invoices or perform mass updates using natural language. Generative AI explains more core financial processes, including complex costing variants. 麻豆原创 Document AI automation alleviates more tedious tasks, such as extracting and matching data from incoming quality certificates. There is so much more, so dive into everything 麻豆原创 Business AI for finance below.
• The latest innovations don鈥檛 slow down for industries, spend, and procurement. The Booking Agent in Concur Travel is a new personal assistant that simplifies our customers鈥� trip planning with personalized flight and hotel recommendations. Procurement customers can automate statements of work (SOWs) creation with a new document extraction feature in 麻豆原创 Fieldglass that pulls data directly from existing files. Finally, the Utilities Customer Self-Service Agent offers a new 24/7 self-service that feels personal and effective across any channel for utility customers. Check out industries, spend, and procurement in detail below.
• 麻豆原创 Business AI for customer experience welcomes new agents that will free up more of employees鈥� time and boost customer service. The Digital Service Agent supercharges customer support with instant answers to common inquiries, freeing human agents to focus on more complex, high-value interactions. The Catalog Optimization Agent continuously scans product descriptions and translations to identify inconsistencies or gaps in global product catalogs. Get all the details for customer experience below.
• With 麻豆原创 Business AI for IT and developers, customers can build, automate, and analyze faster and more simply than ever. agent builder is at the top of the ticket, as users can now create custom AI agents to automate complex, end-to-end business processes. 麻豆原创 Analytics Cloud is seeing exciting enhancements, with customers able to generate complex formulas and chart summaries from natural language. 麻豆原创 Joule for Developers also further accelerates ABAP code generation and testing. There鈥檚 so much more, so read on below.
• 麻豆原创 Business AI for business transformation management and 麻豆原创 Signavio are taking business value to new heights by transforming how business leaders understand customer experience. Customers can now automatically analyze sentiment from unstructured customer feedback and link it to events in their operational processes. My Process Overview in 麻豆原创 Signavio offers a highly personalized and role-specific experience for understanding processes. Learn more about AI and business transformation management below.
• In Q3 麻豆原创 Business AI for sustainability is all about simplifying what was once complex: environmental compliance and reporting. AI-powered permit management in 麻豆原创 S/4HANA Public Cloud extracts requirements directly from PDF documents to make manual effort and the risk of costly fines a thing of the past. 麻豆原创 Green Ledger uses AI to make sophisticated carbon analysis accessible to all business users through natural language queries. Business users can now effortlessly explore carbon emissions data and its financial impact in natural language. Get more information about AI and sustainability below.

Joule

麻豆原创 Joule for Consultants
Product enhancements
General availability

Consultants leading complex innovation and transformation projects require swift and reliable information to ensure success. assists them by providing instant clarity on ABAP code purpose, business logic, and structure, drawing from a model trained on 麻豆原创鈥檚 exclusive code and vast documentation. 麻豆原创 Joule for Consultants translates to an up to 14% acceleration in project execution, a 50% reduction in design rework, and an estimated 1.5 hours saved per consultant per day through faster knowledge access and improved code interpretation.
Read more about this release in our Q2 2025 highlights.

In Q3 2025, 麻豆原创 Joule for Consultants has gotten some key enhancements. Consultants can now leverage a new Prompt Guide for quick-start tips and a filterable Prompt Library to browse pre-formulated questions by role or area. The tool鈥檚 knowledge base is continually refreshed with the latest 麻豆原创 Learning journeys and courses, Activate Roadmap content, and now integrates 麻豆原创-exclusive, gated-content Knowledge Base Articles (KBA) and 麻豆原创 Notes. Once Joule provides an answer, the new 鈥淐opy Answer to Clipboard鈥� function allows consultants to quickly share the entire response and specific code snippets for seamless integration into other applications.

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麻豆原创 Business AI for supply chain

麻豆原创 Service and Asset Manager
AI-assisted mobile execution
General availability

Field technicians can now document job details more efficiently using AI-assisted voice commands within the 麻豆原创 Service and Asset Manager mobile app. This mobile execution feature lets them capture work updates through natural language, which the system instantly converts into structured data, streamlining the job completion process.

By guiding the user and enabling a hands-free experience, this capability delivers a 50%* increase in technician productivity and a 75%* reduction in costs from job completion errors, fundamentally improving data quality and the mobile user experience.

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Shop Floor Supervisor Agent
Beta release

Production supervisors can use the Shop Floor Supervisor Agent to proactively manage and resolve potential factory floor disruptions. The agent helps them quickly understand the severity of an issue, resequencing production orders and reallocating resources to maintain a seamless workflow.

This proactive approach boosts supervisor productivity in handling disruptions by 50%* and reduces unplanned downtime by two percent*, ensuring greater operational efficiency.

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麻豆原创 S/4HANA Cloud Public Edition, product compliance
AI-assisted compliance information processing
Beta release

Master data specialists in product compliance can leverage an AI-assisted feature in 麻豆原创 S/4HANA Cloud Public Edition to automatically process supplier compliance disclosures. The tool extracts key information, such as regulations and status data, and maps it directly to the corresponding compliance requirements within the system.
This automation improves the accuracy of compliance data, reduces the risk of errors that could lead to fines, and allows specialists to focus on strategic priorities instead of manual data entry.

This can reduce organizations’ costs of processing disclosures by up to 90% and environmental management penalties and fines by 67%.

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麻豆原创 Integrated Business Planning
AI-assisted forecast results analysis
麻豆原创 Early Adopter Care release

Demand planners can dramatically accelerate their forecast analysis using a generative AI summary embedded directly within their planning user interface. This intelligent narrative explains complex statistical details, such as why the best-fit algorithm was chosen, and provides clear recommendations for improving future results.

This enhanced visibility, powered by Joule, boosts planner productivity in analyzing forecasting runs by 25%*, enabling faster and more confident adjustments to the supply chain model.

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麻豆原创 Integrated Business Planning
AI-assisted analysis of inventory optimization results
麻豆原创 Early Adopter Care release

Inventory planners can now leverage AI-assisted analysis to better understand the key drivers behind their recommended safety stock values. The feature supports root cause analysis by translating complex calculations 鈥� such as demand variability, lead time fluctuations, and service levels 鈥� into clear summaries of the factors influencing inventory optimization outputs.

This capability accelerates the speed of analysis and boosts confidence in system recommendations, helping to ensure that inventory outcomes are strategically aligned with crucial business goals for working capital management and customer service. Organizations will enjoy a 25%* improvement in inventory planner productivity.

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麻豆原创 Business AI for finance

麻豆原创 S/4HANA Cloud Public Edition
AI-assisted processing of incoming quality certificates with 麻豆原创 Document AI
General availability

Quality technicians can elevate operational efficiency by automating the intake of quality certificate documents. The solution utilizes 麻豆原创 Document AI to intelligently extract data upon upload, automatically matching it to corresponding system objects to update or generate certificate receipts with minimal manual intervention.

This streamlined workflow accelerates stock release and delivers significant business value, reducing certificate processing time by 70%* and cutting potential revenue loss from associated delays by an equal measure.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted note corrections for project billing
General availability

Billing specialists can enhance the professionalism of their invoices by leveraging the smart notes feature within the manage project billing application. This tool automatically suggests grammatical corrections for notes on time and expenses items, allowing specialists to review and approve changes instead of performing tedious manual edits.

By improving invoice accuracy and speeding up generation, this capability directly reduces the time spent on note corrections by 50%* and helps to shorten customer payment cycles.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted explanation of fixed asset key figures
General availability

Asset accountants can demystify complex financial data with a new AI-powered feature that explains fixed asset calculations in simple, natural language. This tool lets them quickly comprehend asset valuations, ensure compliance, and answer stakeholder questions rapidly and confidently.

This intuitive approach reduces the effort spent analyzing asset values and responding to inquiries by up to 75%*.

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Joule with 麻豆原创 S/4HANA Cloud Public Edition
Product enhancements
General availability

As part of the new capabilities introduced this quarter in Joule with 麻豆原创 S/4HANA Cloud Public Edition:

Supplier invoice verification

The supplier invoice verification capability in 麻豆原创 S/4HANA Public Cloud enables accountants to interact with Joule using natural language to get immediate updates on supplier invoices, such as identifying the current approver or checking a payment status. They can also perform crucial tasks, like releasing an invoice from a payment block or canceling a posted document, without leaving the conversational AI. By providing this direct access to both information and transactional capabilities, the solution drastically reduces time spent on manual searches and boosts the overall productivity of the accounts payable team. The capability reduces the time required to search for invoice details by 60%* and provides a 10%* improvement in overall accounts payable productivity.

Costing variant explanation

Cost accountants working in 麻豆原创 S/4HANA Cloud Public Edition can now use the AI-assisted costing variant explanation for precise, natural language explanations for complex costing variants. This feature helps them quickly understand the logic behind product price calculations, ensuring they can efficiently select the correct parameters for cost estimates.

This intelligent guidance streamlines configuration and troubleshooting, delivering a 66%* reduction in the time needed to set up calculations and significantly increasing efficiency when resolving valuation errors.

Mass update of delivery date

Purchasers managing procurement timelines in 麻豆原创 S/4HANA Public Cloud can leverage Joule to execute mass updates of delivery dates. When a supplier communicates a schedule change, purchasers can use natural language to identify all relevant purchase order items and apply the new dates in a consolidated action.

This capability eliminates repetitive manual data entry and ensures downstream planning is based on the most accurate information, resulting in an 80%* increase in purchaser productivity for this task.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted smart solution for situations in My Home
Beta release

Upon logging into 麻豆原创 S/4HANA Cloud Public Edition, business users can now leverage a smart homepage that automatically summarizes key updates and tasks requiring their attention. This feature provides a comprehensive overview of significant changes since the user’s last session, allowing them to identify and act on high-priority items immediately.

By bringing actionable insights directly to the entry page, users can boost productivity and significantly reduce the time spent on daily tasks, freeing them to focus on higher-value activities. Employees will see an up to 46%* reduction in time needed to resolve situations.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted smart personalization of My Home for applications
Beta release

麻豆原创 S/4HANA Cloud Public Edition users can now personalize their homepage by using natural language to find the right applications for their tasks. The AI-powered feature interprets the user’s request and suggests the most relevant app, which can be added directly to the My Home entry page with a single click.

This significantly reduces users’ time searching for tools and helps new users get up to speed more quickly. The personalization costs of My Home are reduced by up to 33%*.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted easy fill
Beta release

With the easy fill feature, 麻豆原创 S/4HANA Cloud Public Edition users can populate business object fields using natural language. This streamlines data entry by allowing users to describe an update in a business-relevant format, which the system then uses to automatically and accurately populate all corresponding fields.

This accelerates the process, improves data accuracy, and ensures all required information is captured, leading to an 80%* increase in speed, enhanced data accuracy, and a significant reduction in business process complexity and user training time.

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麻豆原创 S/4HANA Cloud Public Edition
AI-assisted payment exception analysis and explanation
Beta release

Accounts payable accountants using 麻豆原创 S/4HANA Cloud Public Edition can more efficiently analyze and resolve payment exceptions. The feature provides enhanced tools to search payment logs and view a transparent history of changes made to payment proposals.

This enables users to quickly identify the root cause of an issue, leading to a higher rate of on-time payments and improved transparency for both end-users and auditors. Overall, it will increase the average rate of on-time payments by up to 85%*, reduce the time for analyzing payment run logs from up to one hour to just 10 minutes*, and lower the overall cost of 麻豆原创 support.

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麻豆原创 Business AI for spend management

Booking Agent
麻豆原创 Early Adopter Care release

Business travelers can streamline their trip planning with the Booking Agent in Concur Travel. The Joule Agent analyzes individual preferences, company policies, and budgets to deliver personalized flight and hotel recommendations through a conversational interface.

This approach reduces the time needed to book a trip by 11% *and improves user engagement by 50%*. It also increases policy compliance and simplifies the overall booking experience.

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麻豆原创 Business AI for procurement

Joule with 麻豆原创 Ariba solutions
General availability

Procurement professionals using 麻豆原创 Ariba solutions, from sourcing experts to casual requisitioners, can now avoid navigational and transactional complexities. Joule integrates with 麻豆原创 Ariba Sourcing, 麻豆原创 Ariba Supplier Management, and 麻豆原创 Ariba Buying, providing intuitive navigation and natural language processing for information access and task completion.

This results in up to 50%*鈥� faster informational searches and up to 50%*鈥� quicker execution of navigation and transactional tasks, enabling procurement teams to redirect their efforts toward strategic activities and maximize their contribution to organizational goals.

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麻豆原创 Fieldglass Service Procurement
AI-assisted document information extraction
General availability

With AI-assisted document information extraction, project managers can streamline the extraction of SOWs from existing files. This helps them reclaim time and eradicate errors during critical migrations. 麻豆原创 Fieldglass Service Procurement extracts essential SOW details from existing PDFs. This advanced capability shifts the focus for project managers from tedious manual data entry to cultivating stronger collaboration among all stakeholders in the SOW life cycle.

The ultimate benefit is a marked 80%* reduction in the time required for SOW creation, a significant decrease in the risk of costly errors, and an overall improvement in collaborative efficiency.

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麻豆原创 Business AI for customer experience

Catalog Optimization Agent
Beta release

E-commerce product managers who optimize global product catalogs can use the Catalog Optimization Agent for intelligent automation within 麻豆原创 Commerce Cloud. This Joule Agent continuously evaluates product descriptions, attributes, and translations to identify and flag inconsistencies or gaps, ensuring accurate and complete information.

This enhancement of merchandising standards improves product discoverability. It drives higher conversion rates, resulting in significant efficiencies, such as a 70% reduction in translation time and a 65% decrease in the time spent adding descriptions per asset.

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Digital Service Agent
General availability

Customer service and sales teams can enhance their support capabilities by deploying the Digital Service Agent to respond to inquiries in natural language. This Joule Agent leverages a company’s internal 麻豆原创 business knowledge to instantly provide accurate answers and resolve common issues. The agent integrates with existing business portals and e-commerce platforms through content-rich APIs and uses machine learning to continuously improve its response quality.

This automation frees human agents to focus on complex, high-value interactions, ultimately decreasing support costs, improving overall customer satisfaction, and boosting conversion rates. Organizations can increase sales staff productivity by 50%*, service staff productivity by 50%* for agent-handled tasks, and overall operational performance.

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麻豆原创 Business AI for IT and developers

麻豆原创 Datasphere
AI-assisted semantic generation
General availability

Data analysts often spend valuable time manually defining the semantic types for ingested non-麻豆原创 data, a necessary but time-consuming preparation task. 麻豆原创 Datasphere accelerates this process with its AI-assisted semantic generation. The embedded feature automatically recognizes and assigns the correct semantic characteristics to data, allowing analysts to bypass manual preparation and move directly to higher-value modeling work.

This capability reduces the time and costs associated with creating semantics for non-麻豆原创 entities by up to 95%* and empowers organizations to derive insights from their data faster.

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麻豆原创 Analytics Cloud
AI-assisted commenting
General availability

Within 麻豆原创 Analytics Cloud, a new AI-assisted commenting feature helps users consume and create commentary. For business analysts, the tool can automatically summarize long comment threads, aggregate comments along a data hierarchy for new insights, and translate the results into the user’s preferred language.

Users can get the help of AI to rephrase their input when authoring comments for improved quality and clarity. This capability dramatically reduces the time needed to analyze qualitative feedback, enabling faster and better-informed decision-making. Organizations will enjoy a dramatic increase in efficiency, with an 80%* reduction in the time required to rephrase business comments, an 80%* reduction in time to aggregate and translate descendant comments, and an 80%* reduction in the time it takes to summarize and translate comments by cell or thread.

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麻豆原创 Analytics Cloud
AI-assisted data actions
General availability

麻豆原创 Analytics Cloud now assists planning professionals by automatically generating advanced formula scripts from natural language descriptions. Users can write a comment explaining the desired logic, and the AI will create the corresponding script. Conversely, the tool can also analyze an existing script and generate business-friendly comments, greatly simplifying documentation and knowledge transfer.

This dual capability equips organizations with a 75%* reduction in the time needed to author scripts and a 75%* reduction in the time required to create fully documented scripts.

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麻豆原创 Analytics Cloud
AI-assisted chart summary
General availability

Users can automatically generate a text summary for any chart using the 麻豆原创 Analytics Cloud add-in for Microsoft PowerPoint. The feature creates a three-bullet point summary inserted directly into the presentation as editable text with a single click. The summary can be regenerated on demand to ensure it always reflects the latest data in the source chart.

This feature significantly reduces the time spent writing presentation commentary. It improves chart comprehension for the audience, offering an up to 96%* reduction in time for writing and updating a chart summary.

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麻豆原创 Analytics Cloud
AI-assisted calculations
General availability

A new AI feature simplifies working with calculations in 麻豆原创 Analytics Cloud. Users can now generate complex calculation formulas simply by describing what they need in natural language. Conversely, the tool can also take an existing, complex formula and explain its function in clear, easy-to-understand text.

This dual capability cuts the time required to create and understand calculations by 60%*, making the platform more accessible and efficient for all users.

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麻豆原创 Document AI
Embedded edition and workspace
General availability

麻豆原创 Document AI, embedded edition, automates the entire document lifecycle within enterprise processes. The solution can automatically retrieve documents from sources like email inboxes, extract key information based on predefined templates, and then seamlessly post the data into target systems like 麻豆原创 S/4HANA. This end-to-end automation accelerates document handling, improves data accuracy, and reduces the delays and value loss associated with manual processing.

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麻豆原创 Document AI workspace is the central administration hub for managing automated document processing. It provides a comprehensive suite of tools for administrators to define data extraction schemas, orchestrate intelligent workflows, and integrate various input channels. The workspace also includes real-time monitoring and analytics, offering complete transparency and control over performance. Centralizing these functions streamlines the setup and governance of document AI solutions, accelerating deployment and simplifying the management of large-scale document processing. Both will grant organizations a 70% *reduction in document processing time, an 83% reduction in template maintenance, and a 40%* mitigation of the value lost to manual processing delays.

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Employees working remotely or in the field often need to submit documents while on the go. Integrating 麻豆原创 Document AI with 麻豆原创 Mobile Start lets users seamlessly upload photos and files for automated processing directly from their mobile device. This mobile-first accessibility streamlines document-heavy workflows, improves overall processing efficiency, and provides a more convenient and user-friendly experience for the entire workforce.

Generative AI Hub
Product enhancements
General availability

Developers can experiment with leading models and orchestration tools with generative AI hub in 麻豆原创 AI Core. This enables scalable AI development and productization across 麻豆原创 and non-麻豆原创 landscapes with built-in trust and compliance.

The open-source coding agent Cline has been integrated into generative AI hub this quarter. It connects developers to over 40 cutting-edge AI models鈥攊ncluding GPT-5, Claude Sonnet 4, and 麻豆原创-managed options鈥攖hrough a single, secure 麻豆原创 AI Core endpoint. It streamlines coding workflows with context-aware assistance, automated code generation, and seamless model switching, all within existing 麻豆原创 development tools. .

New models are also joining the generative AI hub to give customers more flexibility in choosing the best for their organization鈥檚 individual use cases. The latest models include Claude Opus 4, Claude Sonnet 4, GPT-5, GPT-5 Mini and GPT-5 Nano, Mistral Medium Instruct, Cohere Reasoning A Command, Nova Premier from AWS Bedrock, Gemini Embeddings, and Amazon Titan Multimodal Embeddings G1 model.

For more information on new and deprecated models, .

Finally, 麻豆原创 Document Management is now supported as a repository type for the orchestration grounding module. .

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麻豆原创 Joule for Developers, ABAP AI capabilities
Product enhancements
General availability

麻豆原创 Joule for Developers will remain free for another year, allowing customers and partners to benefit from AI-driven development through material numbers 8019124 (customers) and 8019541 (TDD partners). .

With 麻豆原创 Joule for Developers, ABAP developers can expect a 20%* reduction in time and effort to write ABAP code, a 25%* reduction in time and effort to test ABAP code, and a 4.4%* faster time to realized value.

This past quarter, 麻豆原创 Joule for developers, ABAP AI capabilities have been enhanced with several capabilities:

• ABAP developers can generate complete ABAP Cloud applications based on the ABAP RESTful application programming model (RAP). With simple prompts, they can specify a data model based on the given data dictionary structures of the underlying ABAP repository. On top of the generated data model, a full RAP application with an 麻豆原创 Fiori user interface is generated.
• Developers can also integrate RAP applications with OData services exposed by an 麻豆原创 S/4HANA Cloud system using Joule, which helps to create the necessary code automatically.
• They can leverage Joule to create custom fields and logic without diving into the technical implementation details.

of 麻豆原创 Joule for Developers, ABAP AI capabilities in 麻豆原创 S/4HANA Cloud Private Edition in Q4 2025.

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麻豆原创 Build solutions
AI-assisted content creation and summary
General availability

Business users and content creators can now directly leverage embedded generative AI assistance within 麻豆原创 Build Work Zone. This feature enables them to instantly generate text from simple prompts or summarize lengthy information into clear, digestible formats, streamlining the content creation process from within their digital workplace.

This capability reduces the time required to produce an external-facing blog from six hours to just one*, enabling the rapid creation of high-quality content.

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Joule studio
Agent builder
Beta release

Using the agent builder in Joule studio, business and IT users can create custom AI agents to automate complex, end-to-end business processes. These agents are designed to plan, reason, and dynamically solve problems by coordinating multi-step workflows across 麻豆原创 and non-麻豆原创 systems. By invoking APIs, interacting with documents, and collaborating with users, they can handle ambiguous or fragmented processes that exceed the scope of traditional automation.

This allows organizations to drive efficiency in scenarios requiring expert decision-making and exception handling, all while providing central management for governance and visibility.

This unlocks new levels of operational agility and employee productivity for every organization, reducing the time to deploy custom Joule skills by 10%* and cutting the time spent on frequent business tasks by up to 25%*.

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麻豆原创 Business AI for industries

Utilities Customer Self-Service Agent
General availability

Utility customers increasingly expect intuitive, 24/7 self-service options that feel personal and effective across any channel. The Utilities Customer Self-Service Agent addresses this need by providing a conversational AI to handle service requests and product inquiries. Fully integrated out of the box with 麻豆原创 for Utilities data and processes, the agent delivers a consistent and satisfying experience at any time of day.

This agent helps utility providers strengthen customer relationships while driving operational excellence, resulting in an approximate 90%* reduction in the average cost for each AI-handled contact.

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麻豆原创 Business AI for business transformation management

麻豆原创 Signavio solutions
AI-assisted context analyzer, text-to-event matching
Beta release

Process owners can now leverage an AI-assisted context analyzer to automatically match free-text customer experience data directly to specific events within their operational processes. This capability creates a unified view correlating customer sentiment with process execution in a single dashboard.

Eliminating time-consuming manual data mapping lets teams pinpoint the root cause of issues more quickly, leading to enhanced decision-making and targeted improvements for operational efficiency and the overall customer experience. Process owners can expect to improve process analysis accuracy by up to 30%*.

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麻豆原创 Signavio solutions
AI-assisted context analyzer, sentiment analysis
Beta release

Process owners now have an automated method to interpret customer sentiment from free-text data using an AI-assisted context analyzer. The system intelligently classifies unstructured feedback as positive, negative, or neutral, revealing how specific operational processes influence the customer’s perception.

This provides actionable insights to identify root causes, enabling targeted process improvements that enhance customer satisfaction and support proactive experience management. Process owners can expect to reduce the time it takes to access insights from experience records by up to 90%鈥�*.

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麻豆原创 Signavio Collaboration Hub
AI-assisted role-based process overview
Beta release

The My Process Overview feature provides business users in 麻豆原创 Signavio Collaboration Hub with a highly personalized and role-specific experience. Leveraging an AI-driven setup wizard, the system automatically surfaces the most relevant processes and content, eliminating the need for manual searching and navigation.

This tailored environment provides employees with immediate clarity on their responsibilities, significantly boosting productivity while reducing the administrative overhead required to configure and maintain role-specific access paths. It reduces the time needed to navigate to relevant content by 50%* and shortens new user onboarding by 10%*, all while delivering a superior user experience that drives rapid adoption.

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麻豆原创 Business AI for sustainability

麻豆原创 S/4HANA Cloud Public Edition, EHS environment management
AI-assisted permit management
Beta release

Environmental compliance managers using 麻豆原创 S/4HANA Cloud Public Edition can now automate the setup of EHS permit data by extracting it directly from PDF documents. The AI-powered feature intelligently scans permits of any length to capture header data and identify all requirements and propose corresponding compliance tasks. An intuitive side-by-side view lets users validate the AI’s suggestions while reviewing the document, ensuring complete coverage and simplifying audits.

This approach reduces manual effort and the risk of costly omissions, leading to a potential 65%* reduction in management costs and an 80%* reduction in fines, while also eliminating the need for a separate optical character recognition (OCR) solution.

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麻豆原创 Green Ledger
AI-assisted carbon emission analysis
麻豆原创 Early Adopter Care release

Business users can encounter challenges accessing and analyzing intricate carbon emissions data, especially when correlating environmental impact with financial outcomes. 麻豆原创 Green Ledger offers an AI-assisted solution that seamlessly integrates financial data from 麻豆原创 S/4HANA Public Cloud, enabling on-demand exploration of carbon emissions and the creation of meaningful KPIs that directly link environmental performance with business results.

This lets users effortlessly request complex reports using natural language prompts via Joule, making sophisticated insights readily available even to those without extensive data science backgrounds. This reduces the time required for carbon accounting analysis by 90%*.

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麻豆原创 S/4HANA Cloud Public Edition, workplace safety
AI-assisted safety observation reporting
Beta release

Production operators and industrial hygienists can enhance workplace safety using the AI-assisted safety observation reporting in 麻豆原创 S/4HANA Cloud Public Edition. This intelligent capability allows workers to describe safety observations in their own words, with the system processing the natural language input, asking for any missing details, and automatically creating a structured safety observation record.

By removing the need for complex forms, this streamlined process helps businesses capture standardized, actionable data for faster risk prioritization, ultimately delivering up to a 71%* reduction in reporting costs and five percent* cost avoidance for time loss due to incidents.

Get started .

Philipp Herzig is CTO, chief AI officer, and a member of the Extended Board of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks, and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, expressor implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

gives organizations the tools to lead with confidence. Part of the , 麻豆原创 SuccessFactors brings together global core HR, AI-driven insights, and a unified skills foundation to connect people and processes, close skills gaps, simplify compliance, and build a workforce ready for what鈥檚 next.

With the second half 2025 (2H 2025) product release, we鈥檙e excited to introduce hundreds of new features and enhancements in 麻豆原创 SuccessFactors, many enabled by AI. Together, these innovations help HR teams, business leaders, and employees work smarter, move faster, and stay future-ready.

Drive better people and business decisions

Data about people, skills, performance, and business outcomes exists everywhere, but without a clear view, it鈥檚 difficult to act. , now generally available, is designed to help organizations make better workforce decisions by unifying 麻豆原创 and third-party data. Through intuitive dashboards, AI-assisted insights powered by Joule, and hundreds of HR metrics, leaders can now move from insights to action with unprecedented speed.

With pre-built use cases spanning critical areas like skills, compensation, recruiting, learning, performance, and succession, People Intelligence makes it easier to uncover trends, identify opportunities, and take action. By bringing together clean, centralized HR data and powerful AI, it equips HR and business leaders with the intelligence they need to drive meaningful workforce transformation.

Build a future-ready workforce

To stay competitive, organizations must continuously evolve alongside their people. This release introduces new innovations that align skills, performance, and development with future business needs.

We are excited that the in 麻豆原创 SuccessFactors is now available. This agent empowers managers to lead consistent, high-impact performance conversations by analyzing employee data, such as performance goals, activities and achievements, and continuous feedback, to create tailored conversation prompts for each employee. Using Joule, managers receive AI-guided insights like goal progress summaries, key accomplishments, growth focus areas, and development recommendations. Users can ask follow-up questions to dive deeper into any of these areas. 

Additionally, business rules integration in performance management support consistent and transparent performance reviews by automating feedback prompts and actions based on predefined conditions, such as dynamically exposing a comment field only when a rating condition is met.

Succession planning is also getting a boost with skills-based successor recommendations in , which analyzes skills, proficiency levels, and internal work experiences captured in employee growth portfolios to recommend potential successors who might have been overlooked using traditional metrics. And with the new person-based model for talent management, organizations can drive smarter talent decisions, faster reskilling, and greater workforce agility by unifying learning and talent data in a person-based view that follows employees across changing roles, teams, and assignments. 

Enable agile and compliant HR 

As regulations evolve and business needs shift, HR must stay both agile and compliant. This release introduces new capabilities to help teams adapt quickly while ensuring accuracy and trust.

The new solution,available to early adopters in January 2026, supports optimized shift planning in manufacturing and other production industries by aligning workforce skills and staffing levels with operational demand. Geofencing in 麻豆原创 SuccessFactors Time Tracking helps prevent fraud and ensure compliance by defining work site locations and ranges to govern where employees can clock in and out. 麻豆原创 SuccessFactors Employee Central simplifies U.S. leave management by connecting with FMLA service providers to automate leave deductions and improve tracking accuracy.

Across the suite, our updated home page delivers a more intuitive and personalized experience for users with streamlined navigation, targeted communications, and real-time insights across desktop and mobile.

Extend applications to easily adapt

As workforce expectations and business priorities evolve, flexibility is key. This release delivers new capabilities to help seamlessly connect and optimize HR processes, maximizing investments while supporting the changing needs of people and the organization.

is now enhanced by Joule and generative AI to deliver faster access to information, improved self-service, and more informed decision-making. Joule streamlines tasks with role-based self-service, workflow automation, and real-time insights, while generative AI simplifies feedback, coaching, and goal updates with context-aware insights. Employees can also quickly find company-specific knowledge through Joule for accurate, relevant information when they need it.

Lead the future of HR

With the 2H 2025 release, 麻豆原创 SuccessFactors HCM helps HR leaders navigate complexity with ease. By uniting global HR, AI-driven insights, and a unified skills foundation, organizations can make smarter decisions, develop future-ready talent, and stay agile in a rapidly changing world.

To learn about our latest innovations and enhancements, check out the or . 听

Bianka Woelke is group vice president and head of Application Product Management for 麻豆原创 SuccessFactors.

This makes a lot of sense given that today However, the results aren鈥檛 always matching the hype.

A recent found that while enterprise AI adoption is rising, real impact is often elusive. The reason? Many businesses are still operating with disconnected systems and disjointed data. Without a strong foundation, AI can鈥檛 deliver what it promises.

Siloed systems aren鈥檛 just a technology problem鈥攖hey鈥檙e a business barrier.

The CX Disconnect: When Fragmentation Undermines Intelligence

Too many organizations still rely on a patchwork of tools for customer experience, supply chain, finance, and HR. While these point solutions solve individual challenges, they create friction and disconnect across the business. In an AI-powered world, friction is the enemy.

AI thrives on complete, clean, and . If your marketing, sales, service, and fulfillment teams cannot see the same data in real time, or trust that it鈥檚 accurate, your AI strategy will not be set up to succeed.

With the best intentions to embrace AI in an effort to achieve incredible efficiency, instead, customers will still lose valuable time on manual integration, inconsistent customer experiences, and AI outputs that are only as good as the (fragmented) feeding them. The delightful experience aspirations turn into trust lost and frustration all around.

Modular Innovation, Meet Enterprise Intelligence 

麻豆原创 has reimagined enterprise management with , representing a fundamental shift from traditional ERP systems to a modular, composable architecture that integrates AI, data, and applications into a unified platform.  

Grounded in harmonized, semantically rich data, this architecture allows businesses to make sense of data that has traditionally been scattered across systems and trapped in silos, so AI has the comprehensive data it needs to quickly generate meaningful insights.

麻豆原创 Business Data Cloud (麻豆原创 BDC) with native integration of 麻豆原创 Databricks, serves as a data backbone for business AI. It seamlessly connects all 麻豆原创 data and third-party data and provides integrated governance to enable real-time AI-driven decision making. 听

Companies do not lose precious time locating and preparing data for AI. AI systems work on trusted, contextualized data, not just generic data. This produces accurate, reliable, and actionable AI recommendations that enable organizations to scale AI innovation rapidly across business domains.听

麻豆原创 BDC is the foundation for , 麻豆原创鈥檚 AI copilot that acts as an intelligent orchestrator across the entire business suite. 麻豆原创 BDC ensures that Joule has structured business context for natural language processing and that its outputs are accurate so that Joule can provide always-on assistance to break down silos between business operations.听

For example, when a customer service or sales representative handles a complex order issue, Joule can: 

• Check real-time supply chain constraints

• Respond to RFPs faster
• Personalize the response by pulling in relevant customer history from
• Speed response with automated case routing and research

The results are faster resolutions, happier customers, empowered employees, and incredible business outcomes with less effort and overhead.

CX + AI + ERP = Real Results

Integrating CX AI with core ERP systems enables end-to-end process optimization that was previously impossible with fragmented systems. When CX systems connect natively to back-office systems, organizations gain:听

• Real-time personalization powered by operational data
• Intelligent workflows that prioritize high-value customers
• Predictive insights that help teams act before issues arise

The numbers speak for themselves. According to an , customers using this approach reported these benefits:

• Up to 60% reduction in the number of issues service and support teams deal with due to fewer manual errors, automated self-service support functions, automated self-service, and AI chatbots
• 25% to 50% improvement in time to resolution for issues that did require service or support resources
• 25% to 70% improvement in productivity of digital marketing and customer operations teams
• 50% to 90% improvements in sales team productivity by offloading smaller transactional sales, faster quote generation, and streamlined order management
• 20% to 40% increase in productivity of business operations due to less time spent on invoices, payments, shipments, and returns and more informed decision-making

This is not just incremental change; it鈥檚 enterprise transformation, driven by customer needs and powered by AI.

The Future of Intelligent Enterprise Operations 

Embedded within a composable business suite represents a bright future that takes the possibility of AI and makes it a reality.听

• Businesses can seamlessly orchestrate intelligence across all functions, delivering experiences that feel effortless to customers while optimizing operations behind the scenes.听
• Artificial intelligence won鈥檛 just automate individual tasks, but also orchestrate entire business ecosystems to deliver superior outcomes.听听
• Maintaining enterprise-grade reliability and enabling modular innovation will allow organizations to adapt to changing market conditions while creating competitive advantages.听

With the rise of AI, businesses face a pivotal moment in time. Taking advantage of all that technology has to offer demands more than point solutions and departmental optimizations; it requires unified platforms, complete clean underlying data, and a clear unified strategy.

Jessica Keehn is chief marketing officer of 麻豆原创 Customer听Experience.

On top of that, you know AI agents are the new frontier and will allow you to automate processes that today absorb a large amount of time and resources. You want to know how to be among the first to use them to gain an early advantage.

To get these answers and discover how 麻豆原创 is uniquely positioned to help you leverage AI for business results, attend in 2025, being held October 6-8 in Las Vegas as well as virtually. It鈥檚 the destination for leaders ready to embed the latest from AI into the foundation of how their organizations run to produce real, enterprise-wide outcomes.

Learn how to become a leader in the era of AI

According to Boston Consulting Group, which the relatively small number of companies already scaling these advanced technologies, “AI鈥檚 greatest value lies in core business processes where leaders are generating 62% of the value. Leveraging AI in both core business and support functions gives these companies a competitive advantage.”

This is exactly our approach and position of strength at 麻豆原创. We infuse AI directly into the business processes, decisions, and data models that power finance, supply chain, HR, customer service, and more. That’s also how are enabling systems that anticipate needs, reason, act and learn and adapt in real time. And because these tools are built on (麻豆原创 BTP), they operate with the scale, security, and interoperability that enterprises demand.

麻豆原创 Connect is where this vision comes to life. Over three days, the program will move from strategic framing to hands-on guidance, tailored to every role in an organization, and with each day anchored on specific business needs.

An agenda focused on moving your business forward

Day one at 麻豆原创 Connect addresses strategy: how to turn geopolitical and market volatility into a catalyst for growth, unify your organization through shared data and synchronized purpose, and elevate your workforce with AI. Our will show you how to navigate uncertainty by leveraging enterprise-wide data capability, Joule Agents, and 麻豆原创 Business Suite to turn insight into action鈥攃reating a sustained advantage for your enterprise.

Day two focuses on how to use our latest innovations across 麻豆原创 Business Suite applications to bring AI-driven results to life within your enterprise, plus practical road maps across your lines of business.

Day three is about execution: how to leverage 麻豆原创 BTP and a unified data core to activate agile technologies, build interconnected ecosystems, and accelerate returns on innovation. Our will show you how to use a unified foundation to smoothly extend, integrate, automate, and innovate while leveraging AI and data to transform your company.

The core theme across all three days is how to build, adopt, and scale AI that spurs impactful business outcomes. For example, you will learn from companies using embedded AI to improve forecasting accuracy, unlock working capital, boost workforce productivity, and reduce operational risk.  These enterprise use cases are already delivering measurable value.

Three days of learning and leadership

For leaders looking to advance their knowledge on AI, the agenda at 麻豆原创 Connect is built for depth and relevance, and AI content and insights will be available across all tracks: spend management, supply chain, customer experience, and human capital management.

For example, in the session, you will learn how AI agents are transforming enterprise agility by autonomously executing tasks, adapting in real time, and driving productivity.

麻豆原创 Connect is a working session for those ready to lead the next phase of intelligent business. For leaders building AI strategies that are real, resilient, and ready to scale, this is the place to advance them.

, set up your , and take your seat at the center of the business AI movement.

Brenda Bown is chief marketing officer for 麻豆原创 Business AI at 麻豆原创.

However, its potential goes far beyond simple optimization: generative AI can be a trusted ally for personal growth and confidence building, especially when navigating unfamiliar professional territory.

Whether you鈥檙e assuming a new leadership role, mastering a complex technical skill, or simply feeling uncertain about your next career step, AI platforms can truly help you gain clarity and confidence.

Here are three straightforward ways to use AI as a growth tool when venturing beyond your career comfort zone.

1. AI as a judgment-free partner

One valuable yet often underappreciated role of generative AI is its ability to serve as a non-judgmental sounding board. Transitioning to a new role or company often brings uncertainty, questions, and sometimes self-doubt. Regardless of the change, AI offers a non-judgmental space where users can openly share thoughts and explore solutions. This use of AI can help individuals better understand their uncertainties and organize their experiences in a positive, constructive way — laying the groundwork for confident problem-solving and, ultimately, success through a transition or challenge.

2. Breaking down big hurdles into bite-size goals

Facing broad, complex objectives can feel overwhelming. Generative AI can aid career growth by breaking down daunting challenges into smaller, manageable milestones. By asking AI to convert broad objectives into 鈥渂ite-size鈥� tasks, professionals gain a clear road map to achieve their goals. This approach reduces cognitive overload and encourages momentum through steady progress. Whether leading a new team or mastering advanced analytics, these small wins build confidence and reinforce a proactive mindset.

3. Expert-curated learning tailored to your needs

Finally, generative AI can customize and deliver high-quality learning resources that address your unique knowledge gaps and career context. For instance, AI can recommend expert insights and training modules that align with your individualized development path via the 麻豆原创 Learning site, which provides access a broad portfolio of self-paced and premium learning opportunities to achieve business transformation and grow your career with free, self-paced, and on-demand 麻豆原创 learning resources to both . From exploring agile frameworks as a project manager to deepening cybersecurity expertise as an IT professional, AI acts as a personalized guide to expert-level content designed to meet your specific needs.

To further support scalable and targeted learning, the 麻豆原创 Learning site provides learners access to both self-paced and guided learning resources, allowing them to follow learning journeys tailored for specific roles and skill levels in a self-paced way. This adaptive approach enhances engagement and retention, helping users not only acquire new skills, but effectively apply them in their roles. Seamlessly embedded into everyday workflows, these online courses empower employees to engage in continuous development without interrupting their daily responsibilities — strengthening both their individual growth and overall organizational capability.

Whether managing cross-functional projects, mastering data analysis, or navigating career pivots, AI-enhanced learning experiences provide dynamic support that transforms uncertainty into clarity and fosters sustained growth.

Leveraging generative AI has become essential for confident, forward-thinking career advancement as new skills and roles emerge rapidly. Integrating AI into personal development helps professionals transition into new roles with greater assurance and agility.

More than a productivity tool, AI serves as a growth partner — listening without judgment, breaking down complex challenges into clear steps, and offering tailored learning paths. By embracing AI as a trusted resource, individuals and organizations can nurture a culture of continuous learning and navigate change and growth opportunities with confidence.

Andre Bechtold is president of Industries & Experiences at 麻豆原创.

Research from multiple industry sources indicates that this isn鈥檛 just an emerging trend — the emphasis on consolidation is growing at an unrelenting pace.

According to ADAPT’s CIO Edge , a comprehensive study of more than 140 CIOs, are planning to consolidate their vendor landscape.

This trend is not just about making minor adjustments to meet market demands; a majority of organizations are targeting a , which represents a significant and fundamental shift in how enterprises approach their technology ecosystems.

The urgency for CIOs to transform their vendor landscape is palpable across all sectors and industries. A of more than 1,000 technology professionals revealed that 90 percent of IT professionals identified software consolidation as a priority, with 73 percent predicting their organizations will continue growing software investments while simultaneously consolidating vendors.

This paradox — expanding capabilities while reducing complexity — defines the modern CIO’s challenge.

The false promise of best-of-breed

This vendor consolidation trend contrasts with movements like the MACH alliance, which  promotes a pure 鈥渂est-of-breed” approach. While its underlying architectural approaches (Microservices, API-first, Cloud-native, Headless) are sound and arguably have become table stakes in the SaaS world, MACH created unexpected challenges for enterprises.

Initially lauded for its flexibility and agility, MACH ended up creating significant complexity 鈥� more than most enterprises can handle 鈥� at a time when they are looking for simplicity more than ever.

The economic reality is stark: fully MACH implementations usually upfront compared to a unified solution that is pre-configured. Companies must consider not only the purchasing of multiple services, but also the cost and time required for employee training and adoption. Running MACH architecture requires people with highly specialized skills in cloud infrastructure, APIs, microservices, and tools designed to streamline development of the user-facing part of a website or web application. The job market for that talent is uber-competitive, even in the age of AI, meaning you’ll need to have the resources to pay them well or else your competitors will.

The hidden costs of fragmentation

Research reveals several critical drawbacks to the fragmented fully best-of-breed  approach:

• Increased complexity: Managing hundreds of microservices becomes exponentially daunting and expensive rather quickly, with system issues potentially impacting multiple services simultaneously. The management and expertise required to oversee such architectures can be daunting 鈥� and expensive. Once system issues are discovered, they could impact numerous services, which requires deep knowledge coordinated across multiple areas of expertise for troubleshooting and debugging. This can make resolution complicated and cost prohibitive.
• Integration challenges: Trying to make connections between services and systems that were not designed to work together requires additional development expertise, which is expensive.听 Incompatibilities between functions like search, customer service, catalog management, and OMS can lead to degraded customer experience and loss of loyalty.
• Security concerns: The beauty of MACH architecture is also the beast: all of the composable microservices, APIs, and cloud offerings represent security risks. Comprehensive security requires consistent implementation across all components, which can be challenging when using solutions from different vendors. Businesses must develop robust security frameworks and governance models to ensure protection across their entire MACH ecosystem.
• Vendor management complexity: Best-of-breed usually means working with dozens of vendors rather than a few, which can add vast complexity to development and customer support depending on the long-term viability of each vendor, which must provide critical functionality for services or tools that could be discontinued or significantly changed in the future.

The strategic advantage of unified platforms

As CIOs prioritize vendor consolidation, 麻豆原创’s approach to “Suite as a Service” or “best of breed as a suite” offers a pragmatic solution that addresses the fundamental challenges of fragmented architectures. Rather than forcing organizations to choose between flexibility and integration, the (麻豆原创 CX) portfolio provides both through a unified yet composable business suite that spans front and back-office operations, in conjunction with a pre-integrated and certified rich ISV ecosystem that allows businesses to compose with intention, wherever this makes sense business-wise.

The flywheel effect: applications, data, AI

The true power of consolidated platforms lies in what 麻豆原创 calls the “flywheel effect.鈥� In this model, applications generate data, data trains AI, and AI optimizes applications. This creates a virtuous cycle where:

• Better data feeds better AI
• Better AI feeds better applications
• Better applications generate better data

This integrated approach is only possible when organizations move beyond siloed point solutions to embrace unified platforms that can leverage the full spectrum of business data. Companies already invested in 麻豆原创 technologies have discovered that a to the data architecture that AI requires.

Quantified benefits: the economic case for consolidation

of 麻豆原创 CX solutions reveals compelling evidence for the vendor consolidation approach:

• Operational Efficiency Gains
  • Faster time to value: Organizations can fully connect and integrate their CX and ERP data in as few as six months
  • Reduced implementation time: Companies avoid roughly 25 to 50 percent of the time and effort required to build integrations from scratch
  • Improved productivity: Depending on job function, customers report 10 to 300 percent improvement in daily productivity
• Cost Optimization
  • Lower total solution costs: While individual solutions may appear cheaper, the holistic end-to-end solution approach is far more cost-effective
  • Reduced maintenance overhead: Organizations can eliminate up to 70 percent of the time required to manage and maintain systems
  • Resource optimization: Companies avoid having to grow teams by up to 2x to support custom development and integrations
• Strategic Advantages
  • Enhanced customer experience: Seamless connectivity between customer and operational data enables superior customer service
  • Faster innovation: End-to-end visibility enables quicker, more informed decisions leading to faster product launches
  • Reduced operational risk: Standard iFlows provide more reliable connections with fewer potential connectivity issues

The AI-driven imperative

AI is driving the consolidation trend as much as the need to reduce costs. AI models demand high-quality, accurate data to be useful. When — often the result of disconnected digital tools — AI efforts fall short of expectations or stall entirely.

麻豆原创’s unified approach addresses this challenge directly. By providing harmonized SLAs, UX, data models, and provisioning across the stack, along with embedded AI via 麻豆原创 Business AI and a unified and semantically rich data layer via 麻豆原创 Business Data Cloud, organizations can fully leverage AI capabilities across domains without the complexity of integrating multiple disparate systems.

The consolidation acceleration

The trend toward vendor consolidation is accelerating across multiple dimensions:

• Seventy-five percent of organizations pursued vendor consolidation in 2022, up from 29 percent in 2020, according to
• that by 2027, 70 percent of organizations will optimize cloud-native application vendors to a maximum of three
• For midsize companies, the average number of SaaS tools in the last two years

The path forward: strategic consolidation

The evidence is clear: 2025 marks a pivotal moment for CIOs. Organizations that embrace strategic vendor consolidation and choose unified platforms over fragmented point solutions will gain significant competitive advantages in operational efficiency, cost management, and AI readiness.

麻豆原创 CX represents the future of customer experience technology 鈥� not as a collection of disparate tools, but as a unified, intelligent platform that can adapt and evolve with business needs. As CIOs navigate the challenges of 2025, the choice between complexity and consolidation will define their success.

The question isn’t whether to consolidate; it’s whether to lead the trend or be left behind.

With 68 percent of CIOs already planning consolidation initiatives, organizations that act decisively on vendor consolidation will be best positioned to win when it comes to the future of enterprise technology.

Geert Leeman is chief revenue officer of 麻豆原创 Customer Experience.

麻豆原创 Sapphire saw further cement itself as our new UI in the age of AI, as it continues to redefine the end-user experience. Customers are asking questions in natural language, and Joule is working hard behind the scenes to find answers.

More than 40 Joule Agents were announced at 麻豆原创 Sapphire, and the first set of Joule Agents is now available to customers. These agents work across business functions to help customers resolve dispute cases, maintain strong customer relationships, complete follow-up tasks, and more. , the AI operating system for all 麻豆原创 Business AI solutions, simplifies AI development by centralizing all the tools to build, extend, and run custom AI solutions and agents at scale.

And those are just a few announcements from 麻豆原创 Sapphire! Check out the or this overview for more announcements and the full picture. As we close the second quarter of 2025, we have a ton of 麻豆原创 Business AI updates to share.

In the second quarter of 2025, we continued accelerating the delivery of high-impact innovations to customers with enhancements to Joule, Joule Agents, and additional AI scenarios embedded across the portfolio. These features are all built with AI Foundation on  and add to over 240 existing AI scenarios and 1,600 Joule skills. We are working hard and are fully on track to have over 400 AI scenarios by the end of 2025 that will deliver unparalleled business value to customers.

Here are some of the highlights from Q2 2025:

• Joule continues to redefine the way people interact with 麻豆原创. As is now generally available, consultants can rapidly grasp ABAP code and best practices for faster project execution, less rework, and time savings. The phased integration of Joule with Microsoft 365 Copilot offers a unified experience across 麻豆原创 and Microsoft environments for seamless task completion. Joule’s analytical insights feature is generally available, delivering tailored, on-demand decision support through natural language.
• Joule Agents and AI Agents: For example, in supply chain management, agents can already do so much, from autonomously scheduling and optimizing service orders to continuously analyzing real-time data to suggest maintenance schedule adjustments, help reprioritize tasks, and improve asset health. In human capital management, the Performance and Goals Agent provides managers with data-driven insights before one-to-one employee meetings. In 麻豆原创 CX AI Toolkit, the Shopping Agent and CX Agents Builder are now generally available, with the opportunity to build custom agents for customer experience scenarios, such as quote creation, Q&A, or service classification.
• is working to minimize disruptions and simplify planning. 麻豆原创 Digital Manufacturing gets error analysis, and Joule鈥檚 general availability provides instant access to critical information through natural language. There鈥檚 an add-in for Microsoft Excel and 麻豆原创 Integrated Business Planning (麻豆原创 IBP) to generate IBP formulas using natural language. These are just some of the supply chain updates. Explore more below.
• : It鈥檚 all about efficiency when it comes to and spend. Joule partners with 麻豆原创 Document and Reporting Compliance to translate complex e-invoicing errors into natural language. This way, error misunderstandings are a thing of the past. Joule enhancements in 麻豆原创 S/4HANA Cloud Public Edition increase efficiency with proactive sales order fulfillment monitoring, direct fixed asset master data creation, and price adjustment suggestions. For 麻豆原创 S/4HANA Cloud Private Edition, Joule helps users with field logistics, cash management, contract analysis, and streamlines convergent invoicing processes. The first Joule agents are now available in spend management. The Concur Travel Meeting Location Planner Agent simplifies off-site planning by automating information gathering and coordination. The Concur Expense Report Validation Agent can proactively flag issues and guide users through corrections, reducing report preparation time dramatically. Learn more below.
• 麻豆原创 Business AI for procurement sees Joule join 麻豆原创 Fieldglass and boosts Contingent Workforce Management with AI-assisted skill-based job postings, which reduce time defining and matching skills and lower worker ramp-up time. Plus, the AI summarizer in 麻豆原创 Ariba slashes document review times by 50%, and the Sourcing Agent, available in beta, speeds up the sourcing event creation process. Dive in below.
• shows the power of AI and 麻豆原创 SuccessFactors. New language features streamline translation, interview feedback improves candidate evaluations, and “Explain Pay” in Joule reduces payroll help desk tickets and raises employee satisfaction. Explore more below.
• puts the power of Joule in developers鈥� hands. Generative AI hub in AI Foundation gets the latest and greatest models, including Google Gemini 2.5 Pro and Flash, OpenAI GPT, o3, o4-mini, 4.1, 4.1-mini, 4.1-nano, and Mistral Small 3.1, Anthropic Claude Opus 4, Sonnet 4, and NVIDIA Llama 3.2 nv embedqa 1b. The . It automates prompt optimization across AI models, eliminating vendor lock-in and expediting model adoption. 麻豆原创 Document AI now includes file filtering, for example, allowing AI agents to process only relevant document pages for more efficient processing and more flexibility for task-specific document handling. Learn more below.

We will deliver more use cases across our entire solution range in the second half of 2025. Customers can stay updated with .

Joule

麻豆原创 Joule for Consultants
Generally available

Consultants navigating complex innovation and transformation projects require access to reliable and efficient information. assists consultants in rapidly understanding ABAP code purpose, business logic, and structure through a model trained on 300 million lines of ABAP and 30 million lines of CDS code. This access to 麻豆原创鈥檚 exclusive content, coupled with over 200,000 pages of 麻豆原创 documentation, over 50 麻豆原创 Certifications, and more than two terabytes of curated 麻豆原创 Community content, allows consultants to make informed decisions and align projects with best practices.

The resulting business value includes up to a 14 percent acceleration in project execution, a 50 percent reduction in design iterations and rework, and an estimated 1.5 hours saved per consultant per day due to much faster knowledge access and improved code interpretation.*

This capability was recently included in the which shows how AI can be applied in real-world scenarios to solve complex global challenges responsibly.

Discover how KPMG is revolutionizing 麻豆原创 transformations with 麻豆原创 Joule for Consultants and 麻豆原创 Business Data Cloud:

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Joule in Microsoft 365 Copilot and Microsoft Teams
Generally available

Modern enterprises rely on interoperability between critical business systems. Joule is now generally available within Microsoft 365 Copilot and Microsoft Teams, including Microsoft Teams Mobile. This integration enables users to access information and complete tasks while leveraging the strengths of both ecosystems.

Customers can now chat directly with Joule in Microsoft Teams, use Joule in Microsoft Teams and Microsoft Teams Mobile as an app, and ask Joule questions directly in Microsoft 365 Copilot. The integration of Joule and Microsoft 365 Copilot provides a unified AI experience across 麻豆原创 and Microsoft environments. The integration will increase employee productivity, reduce information silos, and streamline workflows, ultimately leading to improved operational efficiency and data-driven decision-making across the organization. Later this year, we鈥檒l launch the second half of the integration, bringing Microsoft 365 Copilot capabilities into Joule and 麻豆原创 applications. Business users will be able to access data from Microsoft Teams, Outlook, OneDrive, and SharePoint — all from within Joule.

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Analytical insights feature
Generally available

Joule’s analytical insights feature delivers tailored, on-demand decision support directly within any 麻豆原创 business application workflow. Business users can ask Joule natural language questions such as “Who were the top three sales managers last month?” or 鈥淲hat is the amount of sales commission this month?鈥� and get immediate, context-rich insights, enabling them to make more informed decisions faster without needing to access 麻豆原创 Analytics Cloud dashboards directly. This results in an 80 percent reduction in steps to get analytical insights and a seamless user experience.*

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麻豆原创 Business AI for supply chain

Joule with 麻豆原创 Digital Manufacturing
Generally available

Production engineers face a common challenge: the need for instant access to key information without navigating through lengthy help content or documentation. Joule with 麻豆原创 Digital Manufacturing addresses this directly by providing an intuitive, natural language conversational search. It interprets queries and instantly retrieves relevant, summarized information from the application’s help content.

This streamlined access to critical knowledge translates to a significant business value, including a 30 percent reduction in the time required to gain insights in digital manufacturing, boosting productivity.*

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麻豆原创 Digital Manufacturing, AI-assisted production engineering
Beta release

麻豆原创 Digital Manufacturing offers an AI-powered production engineering feature tailored to product engineers who need to manage production processes efficiently. This feature empowers users to analyze error logs with AI assistance, automatically identifying root causes and generating resolution instructions. Furthermore, it allows engineers to extend processes through script tasks created from natural language input.

By streamlining error analysis and script creation, this feature delivers up to a 25 percent reduction in error analysis time for production process errors and a one percent reduction in non-productive time.*

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麻豆原创 Integrated Business Planning, add-in for Microsoft Excel, AI-assisted planning
麻豆原创 Early Adopter Care release

Supply chain planners can now significantly enhance workflow efficiency with the 麻豆原创 Integrated Business Planning (麻豆原创 IBP) add-in for Microsoft Excel. Utilizing AI-assisted planning, users can generate 麻豆原创 IBP formulas through natural language input, eliminating the need for in-depth technical knowledge of functions and parameters. This intuitive functionality allows for the seamless integration of custom calculations within planning views.

The resulting business value is a demonstrable 10 percent improvement in supply chain planner productivity when updating key figures and attributes via the Excel add-in.*

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Field Service Dispatcher Agent
Beta release

The new Field Service Dispatcher Agent enables dispatchers to efficiently plan and optimize service orders by leveraging real-time data, technician availability, and intelligent recommendations. It proposes the right technician for the right job at the optimal time and location, reducing manual effort and decision fatigue. Each proposal is verified by a dispatcher, maintaining human oversight while streamlining operations. This “human-in-the-loop” approach helps ensure both precision and trust.

This agent boosts dispatcher productivity by reducing manual tasks, minimizing errors, and enabling faster, more efficient decision-making. It also optimizes resource allocation by analyzing real-time data, reducing misallocations, and ensuring the right resources are assigned to the right jobs.

Dispatchers can expect to increase their productivity by up to 50 percent and reduce erroneous technician assignments by up to eight percent.*

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Maintenance Planner Agent
Beta release

Maintenance planners can efficiently manage and prioritize a growing list of maintenance tasks while ensuring equipment reliability and minimizing downtime. Collaborating with the maintenance planner, the Maintenance Planner Agent continuously analyzes real-time data and suggests maintenance schedule adjustments, reprioritizing tasks and improving asset health.

It helps maintenance planners create and streamline maintenance event backlogs faster and more efficiently, reducing downtime by quickly identifying and addressing maintenance issues.

Maintenance planners can expect to increase their productivity by up to 40 percent* and reduce unplanned downtime by up to one percent.*

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麻豆原创 Business AI for finance and spend

麻豆原创 Document and Reporting Compliance, AI-assisted electronic document error handling
Generally available

Tax accountants encountering challenges with the growing complexities of e-invoicing can benefit from Joule with 麻豆原创 Document and Reporting Compliance. This solution translates intricate electronic document errors into easily understandable natural language, eliminating the need to navigate technical jargon. This allows for quick identification and efficient resolution of underlying issues, minimizing disruptions and potential penalties.

The demonstrated business value is an up to 80 percent reduction in the time spent on understanding error specifics and determining the root cause, driving significant gains in efficiency and compliance.*

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Joule with 麻豆原创 S/4HANA Cloud Public Edition product enhancements
Generally available

Joule is now more powerful than ever in 麻豆原创 S/4HANA Cloud Public Edition, providing greater efficiency and control over key business processes. In addition to viewing business data for Work Centers and Resources, business users can now monitor sales order fulfillment proactively. By flagging potential issues and providing remediation suggestions, Joule helps users keep orders on track.

Furthermore, Joule allows users to create fixed asset master data directly within the 麻豆原创 S/4HANA Cloud Public Edition, reducing time for large-scale training and supporting greater accuracy and better data governance.

Additionally, Joule can help pricing specialists better handle expiring prices by suggesting new adjusted prices, reducing the time and cost of expiring price detection and new price creation by up to 90 percent.*

For detailed information on the latest enhancements, .

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Joule with 麻豆原创 S/4HANA Cloud Private Edition product enhancements
Generally available

Joule with 麻豆原创 S/4HANA Cloud Private Edition is getting new capabilities across several business functions. Field logistics users can now directly fetch quantities for non-stock items. Furthermore, Joule now unlocks comprehensive cash management capabilities, including monitoring bank statements and initiating transfers. Users working on convergent invoicing can now manage key processes directly, including assigning processors to clarification cases and controlling print locks on invoicing documents.

Joule also enables shipping specialists to fetch details of outbound deliveries and show detailed information, such as picking statuses or ship-to parties for outbound deliveries and sales orders, without the need to find and open the relevant apps. For example, Joule can show all outbound deliveries with goods not yet fully picked or all sales orders due to be delivered, enabling faster issue resolution and improved fulfillment tracking.

And that鈥檚 not all. With the help of Joule, sales representatives can now efficiently extract key contract details, track historical changes, analyze critical KPIs, and rectify errors. This enables deep analysis and swift resolution of sales negotiations, enhancing renewal and upsell opportunities. Additionally, Joule simplifies contract inquiries, boosting customer satisfaction. Sales representatives can expect to reduce the time spent summarizing subscription contract data by up to 80 percent.*

For additional information on these enhancements,

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Accounts Receivable Agent
Beta release

Accounts receivable accountants now have support for processing data related to overdue receivables. The Accounts Receivable Agent can find overdue receivables from different applications and perform appropriate follow-up tasks with customers based on their profiles and payment histories.

Using this Joule Agent, customers can expect to reduce the days sales outstanding (DSO) by up to one percent, the uncollectible write-offs by up to two percent, and the effort analyzing and reconciling open accounts receivable (AR) items by up to 75 percent.*

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Meeting Location Planner Agent
Beta release

Meeting planners can simplify and accelerate off-site event planning with Meeting Location Planner Agent. It suggests locations that minimize travel time for attendees, recommends an event location based on a company鈥檚 office, suggests suitable hotels, offers a comprehensive overview of the total pricing for the offsite, and provides an email template with a deep link for attendees to book their trip. Ultimately, this enables users to plan within their budget.

Automating information gathering and coordination streamlines planning and boosts productivity. It empowers more informed choices to control expenses while meeting event goals and improves the attendee experience with seamless communication and clear booking instructions.

This yields up to a 10 percent cost avoidance for planned meetings and a 15 percent reduction in the time required to plan offsites, improving the process of sharing information with all attendees.*

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Expense Report Validation Agent
麻豆原创 Early Adopter Care release

Expense managers can streamline the expense reporting process with Expense Report Validation Agent. It proactively flags issues and guides users through corrections to minimize delays caused by rejected or returned reports. It improves the user experience by assisting in completing and submitting expense reports, reducing errors, and ensuring all necessary details are included by prompting users for needed information.

This leads to a 30 percent reduction in the time spent preparing and submitting expense reports and a 24 percent increase in first-pass expense reports, improving the overall user experience.*

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麻豆原创 Business AI for human resources

麻豆原创 SuccessFactors solutions, AI-assisted bulk translation
Generally available

System administrators seeking to enhance employee engagement and support compliance can utilize bulk translation within 麻豆原创 SuccessFactors solutions. This tool instantly translates preset page content into multiple languages and features an intuitive edit UI for reviewing translations. The resulting benefits include a simplified translation process, which saves time and costs compared to manual methods, improved translation quality and consistency, and enhanced employee engagement through localized content.

System administrators can reduce the cost of translating customer-specific objects鈥� during system localization by up to 90 percent.*

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麻豆原创 SuccessFactors Learning, AI-assisted image generation for learning
Generally available

Learning administrators using 麻豆原创 SuccessFactors Learning can now benefit from AI-assisted image generation to create more engaging content without relying on external image sourcing. This tool allows for the quick and easy generation of images for custom cards, banners, items, programs, and curricula by simply entering a description. The key benefits are significantly reducing time spent searching for images, enabling faster content creation, and ultimately enhancing the overall learning experience for administrators and users.

Learning designers can expect to reduce their time spent on generating learning images by up to 70 percent, and learning administrators can reduce external spend on stock imagery by up to 90 percent.*

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麻豆原创 SuccessFactors Performance & Goals, AI-assisted sentiment analysis in 360 reviews
Generally available

HR professionals and managers can now utilize sentiment analysis in 360 reviews to gain deeper insights into employee performance with 麻豆原创 SuccessFactors Performance & Goals. This feature analyzes the sentiment behind rater feedback on 360 review forms, providing a clear understanding of an employee’s attitude towards skills and competencies.

The resulting benefits are time savings through a quicker grasp of performance narratives, data-driven decision-making to improve employee performance, and an intuitive way to identify employee strengths and growth opportunities.

This feature is expected to reduce by up to 30 percent the proportion of voluntary turnover that can be attributed to unclear sentiments behind 360掳 feedback.*

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麻豆原创 SuccessFactors Performance & Goals, AI-assisted team goals
Generally available

Team leaders and managers using 麻豆原创 SuccessFactors Performance & Goals can now leverage AI to efficiently build meaningful and inspiring team goals. The system generates well-structured goals that align with organizational standards by describing desired team achievements. Users can review, edit, and regenerate content as needed.

The feature creates high-quality, aligned team goals and shifts focus from ideation and drafting to achieving results.

Managers can reduce the time allocated to creating team goals by up to 65 percent.*

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麻豆原创 SuccessFactors Performance & Goals, AI-assisted performance insights
Generally available

Managers can now utilize performance insights to comprehensively understand employee performance based on feedback received from 麻豆原创 SuccessFactors Performance & Goals. This feature generates a summary and synthesis of qualitative feedback from a given performance year, allowing managers to visualize and understand employee performance more effectively.

The benefits are improved efficiency in completing performance forms and preparing for one-on-one meetings, connecting qualitative feedback and achievement data with quantitative ratings, and expanded information for leading performance management within the team.

Managers can reduce by up to 70 percent the time spent preparing their direct reports鈥� performance histories for respective review discussions.*

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麻豆原创 SuccessFactors Succession & Development, AI-assisted successor insights
Generally available

Succession planners and people managers using 麻豆原创 SuccessFactors Succession & Development can now leverage successor insights to streamline and enhance succession planning. Users gain valuable insights into potential successors directly from the position card, including role alignment, performance, key achievements, strengths, and development areas.

The benefits are readily available and relevant insights to guide succession planning decisions, a shift in focus from data digging to strategic workforce management, and the ability to define targeted career growth and skill development to build a broader bench of qualified candidates for key positions.

Both successor planners and managers can expect to reduce the time spent on succession planning by up to 20 percent through automated insights into candidate profiles and succession data management.*

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麻豆原创 SuccessFactors Recruiting, AI-assisted interview feedback insights
Generally available

Recruiters and hiring managers can now leverage AI-powered interview feedback insights to streamline candidate evaluation. The system provides a comprehensive evaluation of candidates by incorporating assessments of skills and competencies, overall comments, notes, skill-specific feedback, and the final recommendation, all generated from interviewer feedback. Recruiters can generate, view, and regenerate these insights as needed, ensuring the latest feedback is reflected.

This improves efficiency in reviewing candidate feedback, eliminates the manual effort of creating summaries, facilitates the easy identification of consensus or concerns across the interview team, and allows for the regeneration of summaries as additional feedback becomes available.

Recruiters can reduce by up to 70 percent the time spent on summarizing interviewer feedback per interviewed candidate.*

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麻豆原创 SuccessFactors solutions, AI-assisted extended AI locales
Generally available

HR leaders aiming to support a global workforce can leverage extended AI locales within 麻豆原创 SuccessFactors solutions to expand language coverage. Managed by system administrators, this feature enables the creation, review, and management of AI-translated locales through a UI and built-in workflow, ensuring human-reviewed and customized translations.

System administrators can reduce up to 90 percent the cost of managing AI-translated locales for customer-specific objects during system localization, while reducing compliance risk.*

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Joule with 麻豆原创 SuccessFactors Mobile
Generally available

麻豆原创 SuccessFactors users can now use Joule with 麻豆原创 SuccessFactors Mobile apps to manage daily tasks more intuitively and efficiently. Joule allows employees to independently resolve issues and reduces the time spent searching for information. It empowers managers to make data-driven decisions, supporting better team performance and growth.

On iPhones and iPads, users can ask Siri to open Joule and use it to answer their questions. For example, mobile users can say, “Hey Siri, ask Joule with 麻豆原创 SuccessFactors” to start the interaction with Joule via Siri.

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麻豆原创 SuccessFactors Employee Central, AI-assisted explain pay
Generally available

麻豆原创 SuccessFactors Employee Central Payroll lets employees utilize the “explain pay” feature with the help of Joule to instantly answer their questions about pay changes and details. This AI-driven functionality provides immediate explanations, significantly reducing payroll help desk tickets and boosting employee satisfaction.

HR departments can expect a 50 percent reduction in pay statement-related HR tickets, and employees can benefit from zero lead time for getting a qualified answer.*

and watch it in action in the 麻豆原创 SuccessFactors H1 2025 release highlights video:

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Performance and Goals Agent
Beta release

The new Performance and Goals Agent in 麻豆原创 SuccessFactors automates data collection, generates personalized talking points for managers, and suggests actionable next steps like producing meeting notes in continuous performance management, scheduling 1:1s, requesting feedback, and more.鈥� It ensures managers are equipped with relevant insights and reduces time spent on manual prep work.

For instance, the agent can alert managers that they have a performance review with one of their employees coming up, but do not have any peer feedback. The agent can work on their behalf to collect feedback from their employees鈥� peers, summarize that feedback, and prepare them before the conversation.

The Performance and Goals Agent simplifies complex HR processes such as performance reviews and compensation planning, reduces the administrative burden, and creates and executes actionable plans with the correct information and data.

It reduces by up to 50 percent鈥� the manager鈥檚 time in preparation for performance discussions, by up to 80 percent鈥� the manager鈥檚 time on following up on performance discussions, and by up to 30 percent鈥� the voluntary turnover that can be attributed to poor performance discussions.*

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麻豆原创 Business AI for customer experience

麻豆原创 Service Cloud Version 2, AI-assisted entity extraction鈥�
Generally available

Contact center agents frequently face the challenge of manually sifting through unstructured text in emails and documents to extract vital information. The new entity extraction feature in 麻豆原创 Service Cloud Version 2 automatically identifies and extracts relevant ID patterns, such as product IDs and serial numbers, converting unstructured text into structured data.

This reduces manual effort, enabling faster case processing and resolution. This leads to a 50 percent increase in service staff productivity and a 30 percent reduction in repeat cases, ultimately improving customer satisfaction.*

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麻豆原创 Service Cloud Version 2, AI-assisted registered product summary
Generally available

Customer service representatives often spend excessive time gathering information about registered products when handling support cases. With 麻豆原创 Service Cloud Version 2, we introduce a new AI feature that generates comprehensive summaries for registered products, including an “about registered product” section and a summary of related cases.

This functionality significantly reduces the time spent on information gathering, enabling faster issue resolution and ultimately improving the overall customer experience. Service staff productivity is expected to improve by up to 25 percent, and the first-call resolution rate is expected to increase by up to 15 percent.*

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麻豆原创 Sales Cloud Version 2, AI-assisted sales order summary
Generally available

Sales managers can now quickly understand all key aspects of a sales order with the AI-assisted sales order summary. They gain immediate insights into pricing fluctuations such as increases or decreases with percentage changes, on-time delivery status, the quantity of free products offered, and instances of product substitution.

This automation eliminates manual data analysis, leading to a saving of 90 percent of the time spent on pricing simulation assessments, and empowering faster, more effective decision-making.*

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麻豆原创 CX AI Toolkit
Shopping Agent
Generally available

Digital operation managers and e-commerce platforms require intelligent tools to enhance customer engagement. The Shopping Agent, a key component of the 麻豆原创 CX AI Toolkit, leverages cutting-edge AI to transform online interactions into natural, conversational experiences. It allows customers to articulate their needs and receive personalized product recommendations. The agent facilitates informed purchasing decisions by understanding context and accessing real-time product information.

The agent increases operational efficiency, improves customer service, and provides a scalable solution for enhancing the shopping experience across diverse product catalogs, driving long-term growth and customer satisfaction.

Digital operation managers can expect an increase in online conversion rate by up to 10 percent, an increase in average order value by up to 10 percent, and an increase in repeat purchases by up to five percent.*

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麻豆原创 CX AI Toolkit
Custom AI agents
Generally available

Customer-facing teams can enhance their efficiency with custom AI agents. These customizable agents empower businesses to configure and deploy specialized AI agents within 麻豆原创 Sales and Service Cloud, automating complex tasks without custom coding. The agents streamline workflows by intelligently classifying cases, proactively capturing knowledge from resolved cases, and providing quick access to comprehensive organizational knowledge.

Customers can access the Quote Creation Agent, Q&A Agent, Classification Agent, Knowledge Base Article Agent, and Digital Service Agent, which are all generally available.

Organizations can experience up to a 50 percent increase in productivity for tasks managed by AI agents within sales and service functions, resulting in improved operational performance.*

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Joule with 麻豆原创 Enterprise Service Management and 麻豆原创 Service Cloud Version 2
麻豆原创 Early Adopter Care release

Service agents can now leverage Joule with 麻豆原创 Service Cloud Version 2 and 麻豆原创 Enterprise Service Management to get customer, supplier, and employee information at their fingertips.

Service agents can ask Joule to create tickets, access cases created, view case details, update case priority and status, and much more.

This integration helps increase productivity by allowing users to access and navigate directly to needed information. It also improves the overall customer experience by responding to queries more quickly.

Register for and .

麻豆原创 Emarsys, AI-assisted product finder
Beta release

Marketers often struggle to incorporate the right products into e-mail campaigns quickly. 麻豆原创 Emarsys, AI-assisted product finder, streamlines this process by enabling intuitive keyword and natural language search. This helps marketers instantly locate relevant products within their catalog. The feature further automates the mapping of product fields to email content blocks, eliminating manual setup.

This empowers marketers to boost campaign speed and flexibility and focus on creating engaging content, improving efficiency, and potentially increasing sales conversion rates.

Marketing managers are expected to see a reduction in time spent manually inserting products into email by up to 60 percent and an increase in campaign speed from template creation to launch by up to 30 percent.*

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麻豆原创 Business AI for procurement

Joule with 麻豆原创 Fieldglass solutions
Generally available

Managers can leverage Joule with 麻豆原创 Fieldglass solutions to effortlessly manage key tasks such as viewing, navigating, searching, approving, and organizing activities. These capabilities are included in timesheets, work orders, and job postings — all within a unified experience.

Joule helps managers find the right templates quickly, such as hiring or services procurement templates, improving efficiency in their document creation. Users get insights into company data by finding applicable reports and seeing valuable KPI trends more easily. Alternatively, they can simply ask questions about a feature. Joule will search 麻豆原创 Help Portal documentation to retrieve the correct information without the user needing to navigate away from the current task.

Managers can expect an improved employee productivity through task completion by up to 50 to 70 percent, with less time spent on finding and editing the right hiring templates, statement of work (SOW) description, shorter interview time, and an easier way to access, create, and modify reports.*

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麻豆原创 Fieldglass Contingent Workforce Management, AI-assisted skill-based job posting
Generally available

Hiring managers can spend a lot of time crafting detailed job descriptions to find the right workers. Now, AI-assisted skill-based job postings in 麻豆原创 Fieldglass Contingent Workforce Management allow managers to focus on key skills rather than full role descriptions. The feature suggests relevant skills from a custom library, facilitating faster and smarter talent matching.

This results in a 50 percent reduction in the time required to define and match skills for a job posting, a 15 to 25 percent increase in productivity, and a 40 percent reduction in worker ramp-up time, ultimately leading to more efficient and effective contingent workforce management.*

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麻豆原创 Ariba Category Management, AI-assisted strategy summarizer
Generally available

Category managers can use the AI-assisted strategy summarizer within 麻豆原创 Ariba to generate concise summaries of category strategy documents, quickly understanding key insights without extensive manual review. The refined summaries can then be sent for approval and regenerated when needed, reducing the time required to review and approve completed category strategy documents by 50 percent*.

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Sourcing Agent
Beta release

Sourcing managers can now automate sourcing events and make real-time updates to match the speed of business. The Sourcing Agent can reason through sourcing event requests, past event data, and supplier information to create tailored events autonomously. Sourcing managers can now create and adapt events in real time and automate smart updates, enabling faster, better-informed purchasing decisions and more agile responses to supply chain disruptions and shifting business conditions.

The Sourcing Agent streamlines procurement by automating RFP creation, ensuring consistency, and reducing manual effort. Sourcing managers gain intelligent recommendations for event duration, questions, items, and suppliers 鈥� and can reduce the time to create an RFP by up to 70 percent.*

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麻豆原创 Business AI for IT and developers

Joule Studio in 麻豆原创 Build
Skill builder
Generally available

Organizations aiming to optimize automation and efficiency across 麻豆原创 and non-麻豆原创 systems can use Joule Studio, a capability within 麻豆原创 Build, to create and deploy Joule skills tailored to their specific business needs. Developers can now build Joule skills for rule-based tasks.

Key benefits include deep grounding in business-specific data and processes for reliable outcomes, an open and extensible framework for seamless connectivity, and built-in security and compliance for centralized management and data privacy.

With skill builder, business users experience a reduction of the time spent on frequent business tasks by up to 25 percent. Developers can reduce the time spent to deploy custom Joule skills by up to 10 percent.*

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Generative AI hub prompt optimizer
Preview

麻豆原创 is paving the way for a multi-model AI future by introducing prompt optimizer, a capability of generative AI hub in AI Foundation. This groundbreaking technology eliminates vendor lock-in by automating prompt optimization when switching between AI models. Automatically converting existing prompts into optimized prompts for various models using public benchmarks drastically reduces the time required to migrate use cases from days to minutes. Organizations can now seamlessly adopt new, more cost-effective, geographically available models without lengthy and expensive re-engineering.

, with general availability expected later this year. This offers greater flexibility in building AI solutions.

Generative AI hub product enhancements
Generally available

The generative AI hub now offers access to , enabling application developers to explore which model works best for their custom AI use case.

Application developers can also easily manage the life cycle of their prompts from design to runtime using , reducing the complexity of dealing with prompt templates and leveraging integration capabilities.

In addition, new models are available as part of the generative AI hub, including Google Gemini 2.5 Pro and Flash, OpenAI GPT, o3, o4-mini, 4.1, 4.1-mini, 4.1-nano, and Mistral Small 3.1, Anthropic Claude Opus 4, and Sonnet 4, and NVIDIA Llama 3.2 nv embedqa 1b.

Finally, a translation module has been added to the orchestration feature, improving answer quality when the configured model performs better when input is provided in a specific language. It can be configured for and text.

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麻豆原创 Document AI product enhancements
Generally available

麻豆原创 Document AI, formerly Document Information Extraction, seamlessly processes, extracts, and understands structured and unstructured data from business documents while automating document processing. It significantly reduces manual efforts and minimizes errors.

The service is now available in new regions across major cloud providers: Amazon Web Services (Sao Paulo, Brazil), Google Cloud Platform (Mumbai, India), and Microsoft Azure (Singapore). This expansion aims to provide lower latency, better scalability, and enhanced global reach for businesses utilizing the service. The goal is to improve user experience and satisfaction by offering faster and more reliable AI-powered document processing.

Moreover, the premium edition of 麻豆原创 Document AI now supports a greatly expanded list of languages, including various dialects and regional languages, such as Ido, Ladino, Fijian, Wu Chinese, and many more. This enhanced language support enables businesses to broaden their global reach, improve inclusivity, and increase the efficiency and accuracy of their document processing workflows across diverse linguistic landscapes.

Finally, file filtering capabilities in 麻豆原创 Document AI are now available, allowing AI agents to process only relevant document pages, for example. This feature streamlines processing, saves time by reducing the scope of analysis, and adds flexibility for task-specific document handling, which is especially beneficial for long or complex documents.

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and start with to access cutting-edge generative AI features in 麻豆原创 Document AI, such as instant learning.

麻豆原创 HANA Cloud product enhancements
Generally available

Developers building custom AI applications on 麻豆原创 Business Technology Platform (麻豆原创 BTP) can now benefit from new capabilities that are included in the latest release of the 麻豆原创 HANA Cloud: 

• Leveraging improved vector similarity search scenarios, based on the new in-database text embedding model version, covering more languages and short-text embedding scenarios
• Getting insights from text data stored in 麻豆原创 HANA Cloud via text embedding features as input to Predictive Analysis Library (PAL), AutoML classification and regression models, and k-nearest neighbors鈥� models
• Explaining tabular data outliers using enhanced isolation forest outlier detection and SHapley exPlanations, for example, applied to financial accounting data in the universal journal
• Managing machine learning model development, documentation, and reproducibility, using new experiment tracking and task scheduling capabilities for PAL models
• Detecting data drift using the new Automated Predictive Library (APL) functions to detect unexpected, suspicious, or fraudulent transactions, and simply trigger the required retraining of machine learning models

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The complete enhancements are available on the and . Check out how enterprises need to rethink their database for AI workloads, and how 麻豆原创 HANA Cloud is leading that shift, here.

麻豆原创 Build Code
麻豆原创 HANA Cloud text to SQL generation
Generally available

The AI-assisted database application development SQL console has been updated to support the generation of standard SQL statements for public monitoring views and custom data models from a customer 麻豆原创 HANA Cloud instance.

During SQL statement generation, the prompt and suitable additional information from the database object metadata and 麻豆原创 HANA Cloud documentation are sent to the large language model (LLM). With this context, the LLM can generate syntactically valid SQL statements that can be executed on 麻豆原创 HANA Cloud. This enhancement personalizes query generation, improves flexibility, and increases efficiency.

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麻豆原创 Build Code
麻豆原创 HANA application migration assistant
Generally available

The new extension, 麻豆原创 HANA application migration assistant is based on Joule and is now available in 麻豆原创 Build Code. This enhanced tool extends the capabilities of the existing database migration assistant by automating the conversion of the service layer that includes XSJSLIB, XSODATA, and XSJS artifacts from or into modern CAP-based services, aligning with .

Using generative AI, it simplifies service layer migration when customers choose “XS Classic to CAP” or “XS Advanced to CAP” templates. This feature eases migration of applications from 麻豆原创 HANA extended application services to CAP.

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Joule with 麻豆原创 Business Accelerator Hub
Generally available

With 麻豆原创 Business Accelerator Hub, developers can explore, discover, and consume APIs, pre-packaged integrations, business services, and sample apps.

In Q2, we released Joule with 麻豆原创 Business Accelerator Hub to help them discover pre-built business accelerators using natural language. With Joule, they can expect to reduce the time needed to access the 麻豆原创 Business Accelerator Hub content by up to 40 percent.*

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Joule with 麻豆原创 Datasphere
麻豆原创 Early Adopter Care release

Data architects and data engineers can leverage Joule with 麻豆原创 Datasphere to quickly learn how to use specific 麻豆原创 Datasphere functionalities and receive answers with references to product documentation. They can also ask Joule for specific information about their 麻豆原创 Datasphere instance or delegate tasks like switching to the system language.

This integration reduces reliance on internal IT for product-related questions and enables faster navigation within 麻豆原创 Datasphere.

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麻豆原创 Business AI for industries

麻豆原创 Cell and Gene Therapy Orchestration, AI-assisted exception management
Beta release

Cell and gene therapy supply chain managers will get unparalleled visibility and control with 麻豆原创 Cell and Gene Therapy Orchestration, enhanced with AI-assisted exception management. When unexpected delays or disruptions occur during the patient-specific manufacturing and delivery process, the AI-powered control tower detects these anomalies and proactively alerts the appropriate personnel.

This feature helps supply chain managers identify exceptions and support resolution and rescheduling to maximize patient access and minimize costs. It optimizes manufacturing for optimal capacity utilization, higher revenue, reduced material waste, and improved user experience to benefit patients and healthcare providers.

Supply chain managers can expect to increase their productivity by up to 60 percent* by handling exceptions.

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Philipp Herzig is CTO, chief AI officer, and a member of the Extended Board of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks, and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, express or implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

It鈥檚 time to rethink what a modern AI-ready database should look like.

麻豆原创 HANA Cloud solves this exact challenge with its single, multi-model platform that brings together vector, graph, text, spatial, and relational data natively. It enables developers and data teams to build smarter, more context-aware AI solutions 鈥� directly on operational data.

One database, every model: native support for complex AI workloads

麻豆原创 HANA Cloud uniquely supports:

• Vector data for semantic and similarity search
• Graph data for explicit relationship modeling and knowledge graphs
• Text and spatial data for real-world context
• Relational data for structured operations and analytics

Rather than sending data across disparate services, you can store and process all of it in one place, accelerating time-to-value while reducing the risk of misalignment.

This is multi-model done right, and it is the foundation for powerful AI workloads that scale.

Semantics + similarity: combining vector search with knowledge graphs

Traditional semantic search engines can tell you what documents are similar, but they cannot tell you why. On the other hand, knowledge graphs can express rich, explicit relationships, but often lack the ease of retrieval.

With 麻豆原创 HANA Cloud, you don鈥檛 have to choose; you get both. Bringing together 麻豆原创 HANA Cloud vector engine and 麻豆原创 HANA Cloud knowledge graph engine empowers developers to build context-aware, intelligent queries that go far beyond keyword matching.

Imagine asking: 鈥淔ind the nearest warehouse in Germany (~ 50 km radius of Frankfurt) for suppliers that are ISO 9001 certified, have low carbon tax rates, and are not flagged for customs delays.鈥�

We can conduct a multi-model query to find the warehouses that fit the above criteria.

Here, we are using a SPARQL table within 麻豆原创 HANA knowledge graph engine to filter the suppliers that comply to the following conditions: ISO 9001 certified, low carbon tax rates, not flagged for customs delays.

We can further combine the SPARQL_EXECUTE function in 麻豆原创 HANA knowledge graph engine with vector-based semantic filtering and spatial constraints to identify suppliers that are located within “~ 50 km of Frankfurt” and whose past custom report narratives align with 鈥渘o custom delays.鈥� This hybrid query leverages 麻豆原创 HANA Cloud vector engine, 麻豆原创 HANA Cloud knowledge graph engine, and spatial engine to rank nearby suppliers not only by distance, but also by their trustworthiness and performance signals.

After running these queries, we have the following supplier warehouses as our best match:

This is the power of semantics plus structure, and it is built into the core of 麻豆原创 HANA Cloud.

Unified queries: SQL, SPARQL, and vector search side by side

Developers must often stitch together multiple tools and languages: SQL for relational data, SPARQL for RDF, and separate APIs for vector stores.

麻豆原创 HANA Cloud removes that complexity. You can write a single SQL query that brings together relational data, semantic reasoning via SPARQL (embedded in SQL), and vector similarity search, using native SQL functions 鈥� all in one go: no ETL, no separate infrastructure, just one unified, in-memory engine.

This approach not only speeds up development, but enables new types of AI applications that were not previously practical in siloed environments.

Built for generative AI and RAG: GraphRAG, VectorRAG, HybridRAG

Large language models (LLMs) are only as good as the data they can reason over. That is why retrieval-augmented generation (RAG) has emerged as a critical pattern for enterprise generative AI.

We have brought in new capabilities into 麻豆原创 HANA Cloud, whether you are grounding an LLM in unstructured text (VectorRAG), structured knowledge graphs (GraphRAG), or both simultaneously (combination of VectorRAG and GraphRAG).

麻豆原创 HANA Cloud ensures transparency, traceability, and performance throughout the generative AI pipeline with all the database management qualities. You get explainable answers and full control over how you retrieve, rank, and assemble information, which is vital for regulated industries.

Real-world impact across industries

Enterprises across industries are already leveraging the multi-model capabilities of 麻豆原创 HANA Cloud for transformative outcomes:

• Supplier matching and environmental, social, and governance (ESG) scoring: Blend structured supplier data with document similarity and relationship insights to identify ideal partners
• Compliance monitoring: Connect and query policies, regulations, and audit trails with natural, semantic inputs
• Fraud detection: Analyze transactional data, behavioral signals, and known fraud patterns 鈥� all in real time
• Life sciences research: Integrate clinical trials, publications, and patient outcomes using hybrid semantic and structured queries

These are use cases where meaning is distributed across formats, systems, and relationships.

Developer experience: simplicity without compromise

麻豆原创 HANA Cloud offers developers:

• One platform for all data models: Combined structured, unstructured, and semantic data without stitching together multiple systems
• Built-in support for modern AI workloads: Enable use cases like RAG without external vector stores or pipelines
• Tight integration with 麻豆原创 and open ecosystems: Leverage 麻豆原创 Business Technology Platform and popular open-source tools with minimal setup
• Focus on innovation, not infrastructure: Eliminate the need to manage and maintain separate triplestores, search engines, or vector databases

The result is faster prototyping, cleaner architecture, and lower operational complexity.

Conclusion: It鈥檚 time to rethink your database

In the AI-first enterprise, data is not just a backend concern; it鈥檚 the front line of innovation. And innovation requires infrastructure that is flexible, intelligent, and unified.

麻豆原创 HANA Cloud provides building blocks to create the infrastructure for AI apps in a way that is easy to consume. It doesn鈥檛 just support AI workloads; it accelerates them, with a single platform that brings together semantics, similarity, and structure in real time.

AI needs more than just access to data and 麻豆原创 HANA Cloud delivers that, natively.

Key takeaways

• Unified multi-model: Vector, graph, spatial, text, and relational data all in one platform
• Smart queries: Compose intelligent queries using SQL, SPARQL, and vector search 鈥� side by side
• Generative AI-ready: Built for GraphRAG, VectorRAG, and HybridRAG with full explainability
• Reduced complexity: No need for separate vector stores or knowledge graph engines

Philipp Herzig is CTO, chief AI officer, and a member of the Extended Board of 麻豆原创 SE.
Stefan Baeuerle is senior vice president and head of 麻豆原创 BTP/麻豆原创 HANA & Persistency at 麻豆原创.

I addressed this challenge in a conversation with Dan Newman at , hosted by and . We spoke about the blockers that leaders face when determining where to apply generative AI to move their businesses forward and what 麻豆原创 Business AI is uniquely bringing to market to help.

Flowing from that conversation, here are four steps you can take, among others we touched on, that will help you become an AI front-runner.

1. Prioritize use cases with the most promise

First, focus on areas of your business in which you can use AI to deliver fast, measurable value. Finance, HR, supply chain, and customer experience are among those AI front-runners often start with. As you assess your options, set aside the idea of a “proof of concept.” Instead, develop “proofs of value鈥� by using your and your team鈥檚 expertise, data, and imaginations to find areas where more value can be unlocked using automation or AI agents.听

By the way, the term 鈥減roof of value鈥� was first coined by AI front-runner , vice president of IT at , in reference to an AI agent for accounts payable that his team designed in partnership with 麻豆原创. The key is to pinpoint what outcomes matter most to your business and choose use cases that quickly prove the value.

2. Deploy intelligent agents to simplify complex tasks

Another practice of AI front-runners is the use of AI agents that span departments and systems to solve end-to-end problems. Their autonomous abilities to handle whole processes is one of the differences between an AI skill and an AI agent. A skill is a single ability, such as the ability to write a message or analyze a spreadsheet and trigger actions from that analysis. An agent independently handles complex, multi-step processes to produce a measurable outcome. We recently an expanded network of to help foster autonomous collaboration across systems and lines of business. This includes out-of-the-box agents for HR, finance, supply chain, and other functions that companies can deploy quickly to help automate critical workflows.

AI front-runners, such as , also create customized agents that can tackle specific opportunities for process improvement. Now you can build them with , which provides a low-code workspace to help design, orchestrate, and manage custom agents using pre-defined skills, models, and data connections. This can give you the power to extend and tailor your agent network to your exact needs and business context.

3. Embed AI into daily workflows

To truly become an AI front-runner, you need AI woven seamlessly into how your teams work every day. You also need to ensure it works across your broader technology ecosystem. Because of these critical business needs, we created to be your natural language AI interface, built right into your 麻豆原创 systems. And we鈥檙e adding a new Joule action bar to make it even more context-aware and better integrated with third-party tools like ServiceNow and Microsoft Copilot. It doesn鈥檛 wait for you to tell it what you need. Instead, it can proactively follow your behavior and suggest helpful next actions in context across multiple 麻豆原创 and non-麻豆原创 applications. This helps remove friction, so your team members don鈥檛 have to toggle between tools or relearn interfaces.

4. Foster an ecosystem of interoperable, leading AI tools

Another way to become an AI front-runner is to tackle fragmented tools and solutions by putting in place an open, interoperable ecosystem. After all, what good is an innovative AI tool if it runs into blockers when it encounters your other first- and third-party solutions? This is why we recently announced a tighter integration with Microsoft Copilot for productivity and partnerships with and for flexible access to leading AI models. These, and many other partnerships, help teams combine multiple AI capabilities, share trusted data across systems, and drive business outcomes faster, without the headache of manual connections.

Ready to lead? Here鈥檚 how to get started

I want to encourage you to lead, not follow, in the AI era. If you鈥檙e ready to do that, there are a few ways to get started. First, go deeper on these subjects in the full . Then and .

Brenda Bown is chief marketing officer for 麻豆原创 Enterprise AI Business.

With AI-powered innovation and a unified approach to HR service delivery, organizations can create the seamless, connected experiences employees expect while unlocking new levels of efficiency and strategic impact for HR. That鈥檚 exactly what 麻豆原创 is enabling with the 麻豆原创 SuccessFactors Enterprise Service Management solution, recently delivered in the 1H 2025 release and now available.

Leading companies like , a global producer of natural ingredients for the food and beverage industry, are already seeing the impact, with benefits such as:

• 33% reduction in case resolution times
• 4X productivity increase
• 80% reduction in e-mail writing time using generative AI

Paul Wittig, head of HR Operations & Services, D枚hler, said, 鈥淓nterprise service management for HR is a huge step towards a more digital and, therefore, more transparent and structured way of work.鈥�

The future of HR service delivery is now

The employee experience is shaped not just by big career moments, but by everyday opportunities, interactions, and the ability to get support when it鈥檚 needed. That鈥檚 why one of the most critical HR touchpoints in any organization is the HR help desk鈥攁nd it鈥檚 also one of the most overburdened.

HR service reps at large enterprises often work in shared business centers and are responsible for managing high case volumes and diverse requests, ensuring accuracy and compliance. They may process hundreds of service requests in a month, each taking 1-3 days to resolve depending on the complexity of the issue, leaving employees waiting for the answers they need and HR teams overwhelmed by volume.

But this model is evolving鈥攁dvancements in technology solutions are fundamentally reshaping how this work gets done. It鈥檚 no longer just about processing more cases, faster. It鈥檚 about preventing many of those cases from being raised in the first place. Intelligent, AI-powered tools enable employees to find answers independently, reducing case volumes and allowing HR teams to focus on more complex issues that require human expertise.

According to Gartner*, 鈥淏y 2025, 70% of organizations with more than 2,500 employees will have invested in an HR service management solution.鈥�

The momentum is clear, and organizations taking action are already seeing the benefits: reduced case volumes, faster resolution times, and a more seamless experience for both employees and HR teams.

The potential of AI to transform service delivery is also reflected in recent 麻豆原创 SuccessFactors research. In one survey, 89% of employees said their workplace experience would improve if they could use AI to get answers to HR questions. In a related survey, HR leaders identified self-service and other AI-enabled administrative tasks as the most valuable use cases for their teams鈥攆reeing them from repetitive requests and creating space for more meaningful conversations with employees, from career development to conflict resolution.

The question is: what does HR service really look like in an era where embedded AI has the potential to transform not just the speed, but the entire nature of support?

The benefits of a single cloud platform, powered by AI

麻豆原创 SuccessFactors Enterprise Service Management enables organizations to completely reimagine HR service delivery with a unified cloud platform powered by AI.

Enhancing the employee experience is among the top benefits of 麻豆原创 SuccessFactors Enterprise Service Management. Delivering added value to HR, the solution can harness the power of AI to help search, analyze, and update the underlying knowledge base and policy data, enabling it to better address employees鈥� questions in the future before cases are generated. can give employees instant access to the answers and support they need through collaboration tools, a rich knowledge base, and omnichannel self-service experiences.

For example, imagine an employee with questions about parental leave. Instead of submitting a case and waiting for an HR response, the employee can simply ask Joule the question from directly within the platform. Joule can provide accurate, personalized guidance based on company policies and the employee鈥檚 specific eligibility, helping to instantly resolve the inquiry without any manual intervention. If the question is more complex or requires documentation, the technology helps seamlessly create and route the case to an HR service rep, along with all relevant details, working to ensure fast, informed support. The best part: Joule can be accessed from anywhere across 麻豆原创 and is not just contained within HR.

The solution also benefits HR teams by helping to simplify daily operations and significantly scale efficiency. 麻豆原创 SuccessFactors Enterprise Service Management can enhance HR service delivery behind the scenes with AI-driven case management, automated document handling, and intelligent knowledge updates, working to reduce manual effort for service reps and improve compliance. AI at work is central to this process, enabling auto-classification of service requests, content summarization to give agents a concise, contextual view of each case, and next-best action recommendations to help resolve issues quickly and effectively. The solution can continuously learn from past interactions, helping to make classification and resolution processes smarter and more accurate over time. Generative AI can further elevate efficiency by automatically generating clear interaction summaries, consistent resolution recaps, and professional, personalized e-mail drafts鈥攈elping to accelerate case handling, enhance communication quality, and ensure a more seamless, consistent service experience for both employees and HR teams.

With embedded 麻豆原创 Analytics Cloud, HR teams can gain real-time visibility into service performance, enabling data-driven decisions to further optimize operations and elevate the employee experience.

A win for the business, employees, and HR

麻豆原创 customers that already use 麻豆原创 SuccessFactors Employee Central for core HR are well positioned to quickly implement and reap the benefits of 麻豆原创 SuccessFactors Enterprise Service Management. Together, these solutions can create a unified, AI-powered foundation that can deliver personalized, compliant HR support at every touchpoint.

Real-time, trusted core HR data from 麻豆原创 SuccessFactors Employee Central helps ensure employees receive accurate, context-aware support, while quick actions embedded in the solution can make it easy to complete common HR tasks with just a few clicks鈥攁ll within the flow of work. Within 麻豆原创 SuccessFactors Enterprise Service Management鈥檚 case management experience, HR service reps can also benefit from direct access to the 麻豆原创 SuccessFactors Employee Central people profile, available as a mash-up, helping to provide immediate, secure visibility into relevant employee information without the need to switch systems. The solution can extend core 麻豆原创 SuccessFactors HCM investments with a secure, compliant service layer to help maintain centralized data governance, streamline service processes, and reduce manual effort鈥攚orking to ensure a seamless, intuitive experience for employees and HR teams alike.

We all know that HR is not just a back-office function. It is central to shaping employee experience and driving business outcomes. With 麻豆原创 SuccessFactors Enterprise Service Management, powered by 麻豆原创 Business AI, organizations can deliver the support employees expect while reducing HR workloads and improving efficiency. The result? A triple win for the business, employees, and HR.

Learn more about .

Lara Albert is chief marketing officer at 麻豆原创 SuccessFactors.

*Source: Gartner: Market Guide for Integrated HR Service Management solutions, May 2024

We’re witnessing the rise of a new wave of intelligent applications reshaping how organizations operate, embedding real-time data and critical operational context with AI models to enable swift and thoughtful decisions. Unlike traditional software that is governed by rigid business rules, these modern applications can learn and adapt to rapidly evolving customer and market demands 鈥� detecting changes to optimize processes, anticipate needs, and collaborate with both human and artificial “thinkers” to create competitive advantage for an organization. 

Yet, we stand at the cusp of a bolder wave of innovation, one that unfortunately only the discerning few organizations may fully harness. Despite the vast potential of AI and cloud technologies, their true impact hinges on using these innovations with the secure and semantically rich data that is vastly available within an organization. 

Transform outcomes with intelligent applications

This year at 麻豆原创 Sapphire, we unveiled a significant expansion of 麻豆原创 Business Data Cloud to deliver on the promise of intelligent applications: prebuilt, composable applications that seamlessly integrate trusted data products, AI capabilities, and business simulations to serve the needs of every business leader.

These intelligent applications are not just analytics tools; they transcend traditional analytics by automating and orchestrating work across both analytical and transactional workflows, enabling customers to make decisions and execute actions within 麻豆原创 Business Data Cloud.

Today, we are introducing new intelligent application capabilities in 麻豆原创 Business Data Cloud, starting with People Intelligence, an offering grounded in workforce composition, skills, and compensation data products. Built on data from 麻豆原创 SuccessFactors software, People Intelligence provides HR and business leaders with AI-driven recommendations to optimize talent decisions, drive engagement, and ensure compliance. It features capabilities such as workforce composition insights, compensation insights, and skill insights, all available in the second half of 2025.

Additional intelligent application capabilities in 麻豆原创 Business Data Cloud that are entering technology preview include: 

• Cloud ERP Intelligence: Empowers leaders with transformative insights, business simulations, and AI capabilities to manage uncertainty, drive profitability, and meet sustainability goals. These capabilities include new data products from key business processes such as manufacturing (production execution, resource optimization, etc.), supply chain (inventory, deliveries. etc.), and contract accounting (payments, billing, etc.). 
• Customer Intelligence: Guide sales, service, marketing, and commerce teams with a 360-degree customer view to anticipate needs, improve targeting, and build a comprehensive customer profile.  
• Finance Intelligence: Provides CFOs and finance teams with real-time forecasting and planning, connected data across systems, and AI-powered anomaly detection. 
• Spend Intelligence: Delivers procurement and operations leaders real-time spend visibility to minimize supplier risk, flag spend outliers, and reduce costs.

Each intelligent application in 麻豆原创 Business Data Cloud is underpinned by curated, governed data products, sets of structured business data and metadata designed to accelerate use cases and reduce data integration overhead. And with 麻豆原创 Databricks natively available in 麻豆原创 Business Data Cloud, users can leverage 麻豆原创 data products with existing lakehouses with a zero-copy approach.

As part of these technology previews, we are also announcing the delivery of hundreds of new data products throughout 2025 across all 麻豆原创 Business Suite domains 鈥� from inventory optimization and delivery analysis to sustainability and compliance data products. The first wave includes new environmental, health, and safety (EHS) and product compliance datasets, with sustainability footprint data to follow later in the year. 

Amplify the value of AI with your most powerful data

In addition, 麻豆原创 Business Data Cloud is expanding its knowledge graph capabilities. Originally launched within 麻豆原创 Datasphere, the knowledge graph can now ingest and map metadata across 麻豆原创 and external sources, and seamlessly consume models published in 麻豆原创 Knowledge Graph on 麻豆原创 BTP. This creates a living model of how business data is structured and connected, providing a semantic backbone for AI to operate with higher precision.

Paired with Joule in 麻豆原创 Business Data Cloud, now generally available, users can engage with complex business data as naturally as they think, without the constraints of traditional technology. Joule unlocks the full richness of enterprise information, empowering people across the organization to navigate, reason, and act with intelligence grounded in real business context.

Open data ecosystem: Expanding intelligence beyond 麻豆原创

We are also making 麻豆原创 Business Data Cloud more accessible to power the next generation of intelligent, multi-cloud applications.

Starting in the second quarter, 麻豆原创 Business Data Cloud is available on AWS, with Google Cloud and Microsoft Azure expected to follow in the second half of 2025. This makes 麻豆原创鈥檚 data foundation more accessible and deployable within multi-cloud strategies, giving customers the flexibility to run intelligent workloads wherever they operate. 

At the same time, 麻豆原创 is actively collaborating with leading partners to build the next wave of intelligent applications.

• Accenture will release six intelligent applications addressing key challenges in supply chain, talent, finance, and procurement (GA timeline pending). 
• Adobe and 麻豆原创 are co-developing an application that fuses Adobe鈥檚 marketing data with 麻豆原创鈥檚 financial and supply chain data, enabling real-time alignment between demand signals and operational planning, expected in late 2025. 
• Palantir and 麻豆原创 are partnering to facilitate joint customers鈥� cloud migration journey and modernization programs. Seamless connectivity between Palantir and 麻豆原创 Business Data Cloud will enable customers to build a harmonized data foundation across their enterprise landscape. 麻豆原创 Business Data Cloud and Palantir Foundry and AIP will transform data silos into a trusted data foundation that enables human + AI teaming in the real world. Together the companies will responsibly deliver essential outcomes and support customers, including the U.S. government, to quickly adapt to changes and disruptions.
• Thomson Reuters will develop an intelligent application to help customers navigate the fast-moving challenges in the current global trade and tariffs environment, planned for end of 2025.
• Joint Collibra and 麻豆原创 Business Data Cloud customers can now run up to 10x more active data quality jobs in Collibra Data Quality & Observability when run on 麻豆原创 BDC data, at no additional cost. This limited time offer helps accelerate decision-making, strengthen compliance, and improve AI readiness, and is available until May 30, 2026.

The scope of partner collaboration also extends to data enrichment use cases. A new partnership with 惭辞辞诲测鈥檚 will let our joint customers blend 麻豆原创鈥檚 accounts receivable data with 惭辞辞诲测鈥檚 risk datasets to enhance cash flow forecasting, prioritize collections, and reduce exposure to bad debt. This solution is scheduled for general availability in the fourth quarter of 2025. 

We鈥檙e excited to partner with our customers and ecosystem to unlock a new generation of intelligent applications in 麻豆原创 Business Data Cloud, where trusted data, AI, and business context come together to drive meaningful change. The future of modern business will belong to those who turn intelligence into action.

Get started

• featuring the latest on data products and intelligent applications in 麻豆原创 Business Data Cloud

Irfan Khan is president and chief product officer of Data and Analytics at 麻豆原创.

AI Innovations Aim to Boost Business Productivity by up to 30 Percent;
Partnerships with Perplexity and Palantir Bring out Customers鈥� Best

ORLANDO 鈥� At its annual 麻豆原创 Sapphire conference, (NYSE: 麻豆原创) unveiled innovations and partnerships that put the power of Business AI in every user鈥檚 hands, revolutionizing the way work gets done.

From a virtually omnipresent Joule assistant to an expanded network of Joule Agents that work across systems and lines of business, 麻豆原创 heralds a new era that democratizes access to Business AI and can drive productivity gains of up to 30 percent.

鈥溌槎乖� combines the world鈥檚 most powerful suite of business applications with uniquely rich data and the latest AI innovations to create a flywheel of customer value,鈥� said 麻豆原创 CEO Christian Klein. 鈥淲ith the expansion of Joule, our partnerships with leading AI pioneers, and advancements in 麻豆原创 Business Data Cloud, we鈥檙e delivering on the promise of Business AI as we drive digital transformations that help customers thrive in an increasingly unpredictable world.鈥�

AI that boosts productivity

麻豆原创鈥檚 generative AI assistant Joule can be everywhere you work, delivering personalized answers on everything you need to be more productive.

Joule can accompany business users throughout their day, in and out of the 麻豆原创 application universe, to find data, surface real-time insights and streamline workflows. Joule鈥檚 new ubiquity includes an action bar powered by WalkMe that studies user behavior across applications, turning the assistant into an always-available, proactive AI that can anticipate users鈥� needs before they arise — always adhering to .

A collaboration with Perplexity, an AI-powered answer engine company, enhances Joule鈥檚 ability to draw on structured and unstructured data to solve complex business problems. Powered by Perplexity and the 麻豆原创 Knowledge Graph, Joule now instantly answers questions with structured, visual answers — such as charts and graphs — grounded in real-time business data within 麻豆原创 workflows. For example, a user could ask the tool how recent external events might impact their business and get a forecast based on both current events and the company鈥檚 own business data.

麻豆原创 also unveiled an expanded library of Joule Agents that reimagine business processes and workflows from the ground up. Fueled by the world鈥檚 most powerful real-time business data and orchestrated by Joule, these AI agents work across systems and lines of business to anticipate, adapt and act autonomously so organizations can stay agile in a rapidly changing world. Partnering with industry leaders, 麻豆原创 offers an ecosystem of interoperable agents that can execute end-to-end processes. The new agents span customer experience, supply chain management, spend management, finance, and human capital management.

Finally, 麻豆原创 introduced an operating system for AI development that transforms how enterprises build, deploy and scale AI solutions. AI Foundation gives developers a single entry point for building, extending and running custom AI solutions at scale, making it the first real operating system for Business AI. A new prompt optimizer, designed collaboratively with the frontier AI lab Not Diamond, also helps developers create more effective AI prompts quickly, reducing work on complex use cases from days to minutes.

Data that drives smarter decisions

麻豆原创 also introduced new intelligent applications in 麻豆原创 Business Data Cloud, each built for a specific line of business. These applications can continuously learn, simulate outcomes and guide actions using business-critical data, detecting changes to optimize processes, anticipate needs, and collaborate with both human and artificial thinkers to drive meaningful impact. The People Intelligence application, for instance, optimizes team performance by transforming people and skills data into workforce insights and AI-driven recommendations.

Additionally, 麻豆原创 and Palantir are partnering to facilitate joint customers鈥� cloud migration journey and modernization programs. Seamless connectivity between Palantir and 麻豆原创 Business Data Cloud will enable customers to build a harmonized data foundation across their enterprise landscape. Together the companies will responsibly deliver essential outcomes and support customers, including the U.S. government, to quickly adapt to changes and disruptions.

Applications that accelerate cloud adoption

The company also announced 麻豆原创 Business Suite packages, which are designed for customers to simplify the adoption of 麻豆原创 cloud solutions that address their specific business challenges. 麻豆原创 Build is embedded in these packages, so organizations can customize applications to meet their unique needs.

Finally, 麻豆原创 unveiled a new solution that helps customers transition to the cloud faster. With Joule as the entry point and drawing on insights from 麻豆原创 solutions including 麻豆原创 Signavio and 麻豆原创 LeanIX, the solution delivers personalized guidance and actionable recommendations tailored to an organization鈥檚 transformation objectives and can help deliver up to 35 percent faster time to value.

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About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit .

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
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麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.
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Many organizations recognize generative AI鈥檚 potential to transform their business, but don鈥檛 know where to start. By combining advanced generative AI technologies with enterprise resource planning (ERP) data from critical systems, companies can unlock significant enterprise value: for example, optimizing delivery routes, anticipating potential impacts to supply chain operations, or developing precise financial outlooks.

The AI Co-Innovation Program represents the two companies鈥� shared vision to help partners define, build, and deploy generative AI applications tailored to their ERP workloads. The program brings together enterprise technology from 麻豆原创 and generative AI services from AWS with professional expertise from both parties 鈥� including teams of AI experts, professional services consultants, and solutions architects 鈥� to help support customers in their implementation journeys.

The program will include dedicated technical resources, cloud credits, and more to support the development, testing, and deployment of industry-specific applications.

“AWS and 麻豆原创’s long-standing partnership has helped customers accelerate their cloud journey and unlock more value from their business data,” said Ruba Borno, vice president of Specialists and Partners at AWS. “Our AI Co-Innovation Program is a significant next step that will give organizations the security and flexibility to build generative AI applications with Amazon Bedrock that can analyze and act on their most critical 麻豆原创 data. This will help customers transform decades of business information into actionable insights while accelerating their path to becoming more agile, data-driven organizations.”

“Through the AI Co-Innovation Program with AWS, we’re enabling businesses to solve their most complex operational challenges with precision and speed,” said Philipp Herzig, CTO and chief AI officer at 麻豆原创. “By combining the power of our fully integrated platform with 麻豆原创 BTP and our deep business process expertise with AWS’s comprehensive generative AI capabilities, partners can now create purpose-built AI agents that solve their most pressing challenges 鈥� identifying financial anomalies in real time to automatically optimizing supply chains during disruptions.鈥�

The program also allows partners to rapidly build and scale generative AI applications using the latest generative AI tools and services from Amazon Bedrock, including large language models (LLMs) such as Amazon Nova and Anthropic Claude in AI Foundation on 麻豆原创 Business Technology Platform (麻豆原创 BTP).

This announcement expands on the work AWS and 麻豆原创 are doing to help customers 鈥� including Hyundai Motor Group, Moderna, and Zurich Insurance Group 鈥� modernize and move 麻豆原创 workloads to AWS, realizing the availability, flexibility, and scalability of the cloud. Running 麻豆原创 workloads on AWS allows customers to then combine their data with generative AI solutions. Partners including Accenture and Deloitte are among the first to work with AWS and 麻豆原创 through the program, helping them accelerate the development and deployment of generative AI solutions to solve complex challenges.

鈥淭he AWS and 麻豆原创 AI Co-Innovation Program brings together AWS cloud infrastructure and 麻豆原创 enterprise software experience. Combined with Accenture’s AI transformation expertise and industry knowledge, we can show companies exactly how to integrate generative AI services with their most critical business workloads,” said Caspar Borggreve, senior managing director and 麻豆原创 Business Group lead at Accenture. “For example, together with AWS and 麻豆原创, we are working with a utilities client to build a natural disaster asset resiliency capability to anticipate and respond to environmental challenges, protecting asset-intensive landscapes and maintaining service continuity for its customers.鈥�

“This AI Co-Innovation Program combines cutting-edge generative AI capabilities from AWS and 麻豆原创 with Deloitte’s deep industry experience and technology capabilities to deliver transformative solutions for our customers,” said Nishita Henry, AWS global chief commercial officer at Deloitte Consulting LLP. “Through the program, we are building a finance solution powered by Amazon Bedrock to help healthcare and life sciences companies optimize their product mix, improve forecast accuracy, and maintain competitive pricing, even during uncertain market conditions.”

For more details on the AWS 麻豆原创 AI Co-Innovation Program, visit .

Kai Muehlbauer is head of AI Product and Partner Management at 麻豆原创.
Sara Alligood is global AWS head of 麻豆原创 at Amazon Web Services.

That is why 麻豆原创 is excited to announce our expanded partnership with Cohere, a leader in secure, enterprise-grade AI.

Together, we plan to bring Cohere鈥檚 powerful generative and advanced retrieval models to the 麻豆原创 ecosystem, starting with its model, and extending evaluations with , to enrich our product suite, playing an important role in powering agentic AI experiences.

These models are planned to be available alongside other leading AI models from 麻豆原创 as well as third parties in the generative AI hub in 麻豆原创 AI Core, with the intent to give customers more choice to build AI-powered solutions that meet their unique business needs.

Expanding 麻豆原创鈥檚 trusted AI model portfolio

is rooted in trust. Our customers expect and deserve AI that respects their data privacy, that it fits within their operational workflows, and that it understands the context and complexity of their industries. Cohere鈥檚 focus on security, efficiency, and enterprise applicability aligns perfectly with 麻豆原创鈥檚 approach to business AI and our generative AI hub.

Cohere Command models are lightweight, high-performing language models tailored for complex business tasks, with support for agentic workflows and multilingual operations. The Embed and Rerank models enable powerful enterprise search and retrieval capabilities, helping customers build accurate, context-aware RAG pipelines across structured and unstructured data.

Cohere models are designed to perform in production environments while respecting enterprise privacy requirements and compute constraints. And because Cohere shares our commitment to privacy-first design, these capabilities are built to serve even the most regulated industries, such as finance, healthcare, and the public sector.

麻豆原创: Launch partner for Cohere鈥檚 reasoning model

As part of the partnership, 麻豆原创 plans to be one of the听first partners to offer Cohere鈥檚 upcoming reasoning model, a purpose-built, high-efficiency model designed to power agentic use cases.

We see enormous potential here. 麻豆原创鈥檚 vision for collaborative AI agents 鈥� capable of automating complex, multi-step tasks across systems 鈥� requires not just scale, but reasoning. Whether it鈥檚 helping consultants configure a system or enabling customer service to resolve cross-system issues, this next generation of AI requires models that can reason, plan, and act securely. Cohere鈥檚 reasoning model is built for exactly that.

We鈥檙e excited to partner with 麻豆原创 and bring its enterprise customers the latest security-first models and solutions from Cohere. We鈥檙e especially excited that 麻豆原创 will be one of the first partners to offer our upcoming reasoning model. 麻豆原创 and Cohere share a vision for practical AI innovation, and our collaboration marks an exciting milestone as we unlock new efficiencies and growth for global enterprises.

Martin Kon, President and COO, Cohere

Powering real-world applications across industries

With this collaboration, 麻豆原创 customers will be able to use Cohere models to solve pressing business challenges across industries, such as:

• Agentic task automation: Enable AI assistants that can take actions across enterprise tools and systems
• Multilingual RAG applications: Retrieve, rank, and summarize data from global policy manuals, compliance documents, or internal knowledge bases
• Secure document analysis: Understand long, structured, multimodal files like financial disclosures, M&A reports, technical manuals, or medical imaging
• Context-aware enterprise search: Improve search accuracy across unstructured content like emails, tables, or contracts

Customers will be able to easily access, test, and scale these models in production within 麻豆原创鈥檚 generative AI hub.

Expanding choice without compromise

With our partnership with Cohere, we are continuing to expand a growing ecosystem of AI capabilities that are open, secure, and business-ready. This partnership helps ensure that customers can choose the right model for their use case, while trusting that it meets 麻豆原创鈥檚 standards for quality, reliability, and compliance.

Together, 麻豆原创 and Cohere are enabling enterprises to harness generative AI with confidence, whether they鈥檙e building knowledge assistants, automating processes, or delivering new intelligent services to users.

To learn more about our approach to enterprise-ready AI, visit .

Walter Sun is senior vice president and head of AI at 麻豆原创.

This solution helps developers create, extend, and automate business applications faster using AI-powered, code-first, and low-code tools.

麻豆原创 Build has been designed as the optimal way to extend 麻豆原创 S/4HANA Cloud and other business applications. Thousands of customers are already experiencing up to 3x faster development speeds with 麻豆原创 Build according to 鈥� and now we’ve made it even better.

We are making it dramatically easier for 麻豆原创 S/4HANA Cloud customers to develop with 麻豆原创 Build. Starting today, all 麻豆原创 Build capabilities, along with 麻豆原创 HANA Cloud, are included in 麻豆原创 S/4HANA Cloud.

Combined with deep technical integration, this unified offering empowers customers to quickly extend and personalize their 麻豆原创 S/4HANA Cloud systems using AI-powered application development and automation, while maintaining a clean core and eliminating additional licensing or budgeting complexity.

麻豆原创 Build now fully included with 麻豆原创 S/4HANA Cloud packages

New pricing and packaging for 麻豆原创 Build provides customers with a frictionless way to innovate by gaining the freedom to choose the right tool for every job — whether it鈥檚 AI-powered code-first or low-code development, no more complexity of multiple licenses. Additionally, 麻豆原创 Build and 麻豆原创 HANA Cloud are now included in 麻豆原创 Cloud ERP Private packages, meaning 麻豆原创 S/4HANA Cloud customers can jumpstart all their development without needing to purchase additional licenses.

• Lower total cost of ownership (TCO): The new commercial approach for 麻豆原创 Build alongside 麻豆原创 S/4HANA Cloud significantly lowers TCO through flexible and cost-efficient model, optimizing resource usage while reducing operational overhead. By integrating seamlessly with existing 麻豆原创 S/4HANA Cloud investments and simplifying application management across the 麻豆原创 ecosystem, organizations can drive greater business value.
• Leverage deep integration with 麻豆原创 S/4HANA Cloud based on proven security and technology platform following clean core best practices: With the 麻豆原创 Build Extensibility Wizard users access a guided experience that helps them jumpstart their extension creation from 麻豆原创 S/4HANA Cloud. The Extensibility Wizard is available now in 麻豆原创 S/4HANA Cloud Public Edition and will be available in the second half of 2025 in 麻豆原创 S/4HANA Cloud Private Edition.
• Build faster with ready-made pre-built content and Joule for developers AI capabilities to generate code and app logic, create data models, sample data, automations, and code explanations with quality and precision.
• Gain flexibility: By offering seamless access to both code-first and low-code tools under one unified license, 麻豆原创 Build makes it easier for businesses to meet diverse development needs of their developers without being locked into restrictive platforms.

“麻豆原创 Build is strategic for Delaware, as we believe it is the future for our 麻豆原创 developers. For our customers, it is the easiest way to achieve a clean core and accelerate innovation, boosting their businesses.”

Tim Leys, 麻豆原创 Platform Unit Lead, Delaware Consulting

Get Started Today

Customers asked for more flexibility and a simpler way to build and automate. We listened and took action to make it a reality. 麻豆原创 Build is the gateway to faster, more efficient application development and automation for all 麻豆原创 systems.

Learn more today:

• for more details
• to learn how to easily extend 麻豆原创 S/4HANA with 麻豆原创 Build

Bharat Sandhu is senior vice president and chief marketing officer for Business Technology Platform at 麻豆原创.

However, there are challenges when we move beyond text to apply these models to structured, tabular data, which is essential for enterprise business operations. This imbalance comes partly because of the availability of training data. Text used to train models is plentiful, often consisting of text scraped from the internet, whereas tabular data, especially data with multiple linked tables, is scarce.

To bring AI advancements to the enterprise sector, researchers working on training and benchmarking the performance of these models in an enterprise setting need realistic tabular data.听That’s why 麻豆原创 developed “Sales Autocompletion Linked Business Tables” (SALT), a curated dataset that includes anonymized data from a customer鈥檚 enterprise resource planning (ERP) system.

SALT is specifically designed to support researchers working on AI models for real-world business contexts and can be accessed on and .

Challenges of getting and working with enterprise data

Providing the research community with realistic enterprise data like SALT has been challenging. Data privacy, confidentiality, and commercial interests make obtaining large, clean, high-quality enterprise datasets difficult for training models and benchmarking them for specific use cases. This means there is a growing gap between what researchers are working on and what actual enterprise data looks like.

In addition to the problem of availability, enterprise data is complex. First, business data is usually stored in multiple interconnected tables. For example, a sales order entry may be linked to numerous tables, such as customer IDs connected to a supplier table containing address information. Second, tables are inherently heterogeneous in the data type they can contain. One field may be text, while the other contains numerical or categorical values. Finally, business data frequently shows significant column imbalances, meaning that, for example, a specific product category makes up 90 percent of all sales orders while others are rarely used.

The best way to help researchers develop enterprise models for these challenges is to provide accurate enterprise data.

SALT dataset

Accurate enterprise data is a bottleneck in AI research. The SALT dataset alleviates this bottleneck by providing the research community with the first real ERP dataset. It uses actual industry data collected by an ERP system that records sales orders. It has been minimally processed to protect privacy.

鈥淭here is a gap between academia and industry in terms of data. It cannot be closed easily because of privacy,” says Tassilo Klein, one of the 麻豆原创 researchers behind the dataset. 鈥淏ut we want to enable the research community to work on real problems, not just simulated problems.鈥�

ERP systems help organizations manage core business operations like finance and spending. With millions of entries and extensive, interconnected relational tables focused on sales, the SALT dataset replicates customer interactions in an ERP system. SALT’s realistic enterprise data means it is a perfect basis for helping models understand the characteristics of business data and validate their performance through benchmarking. It also should help researchers develop better foundation models for linked business data.

Getting this right will advance enterprise automation, as many enterprise business processes are heavily centered around data in structured tabular formats. Even though this data plays a crucial role in enterprise day-to-day activities, the generative AI revolution has yet to tap into them.

“SALT is a first step to providing researchers with authentic representative industry data that gives a glimpse into actual enterprise data; for now, we are starting with just one customer and use case,” shares Johannes Hoffart, CTO of Business AI at 麻豆原创. “However, we plan to publish more datasets that cover a diverse set of customers and use cases that, along with SALT, can serve as a basis for pre-training, adapting, as well as benchmarking models.”

Collaboration with academic institutions is also a motivation for publishing this data.

“At 麻豆原创, we hope to collaborate with academic partners who usually can only publish their results on open repositories,” Klein says. “Another hope for the dataset is encouraging more people to explore and validate new methods that help foundation models better deal with tabular enterprise data.”

What 麻豆原创 is doing

Alongside its investment in the open research community with SALT, 麻豆原创 is building 麻豆原创 Foundation Model to handle enterprise tabular data. This table-native AI model aims to accelerate time-to-value for predictive tasks on tabular data, offering a model that can work with tabular data out-of-the-box with little or no additional training data. The , published alongside SALT, provides a first glance at how this model could look.

Knowledge graphs are critical here. They work by exposing metadata 鈥� the who, what, and when of data 鈥� making relationships between information accessible. This provides a structured, interconnected representation of the data that AI models can easily understand and utilize. With the help of 麻豆原创 Knowledge Graph, 麻豆原创 Foundation Model can be scaled and adapted to a wide array of diverse use cases with some lightweight fine-tuning.

Learn more about:

Customers are already doing so much with 麻豆原创 Business AI, from to . In 2025, we will build on these achievements with the same razor-sharp focus: providing our customers with unparalleled business value.

already offers customers a unified experience across our suite鈥檚 end-to-end business processes. Now, as we enter the era of AI agents, Joule will equip customers with agents that genuinely understand their business context and collaborate across all functions. AI agents that alleviate before creating purchase orders or automatically classify and to the right team. These AI agents are impactful because they are grounded in what makes our customers’ businesses unique 鈥� their processes, tools, and data 鈥� thanks to and 麻豆原创 Knowledge Graph.

When it comes to , our customers are just getting started. That鈥檚 because the possibilities are endless with . Customers can create and deploy custom agents that, like our out-of-the-box agents, are uniquely grounded in their business processes and data. We are excited to see how our customers drive business value in 2025 and beyond.

Before diving into the complete updates below, here are some of the highlights from Q1 2025:

• Joule is gaining a host of new capabilities, including support for 11 languages: English, German, French, Spanish, Portuguese, Japanese, Korean, Chinese, Vietnamese, Greek, and Polish. Strict filters are also coming for precise, personalized answers tailored to each user’s context. Joule鈥檚 responses are now streamed for real-time feedback during processing. This eliminates frustrating delays and ensures a smooth, interactive experience, even with complex queries. Joule is fully integrated into 麻豆原创 S/4HANA Cloud Public Edition for enhanced context and effortless navigation. In Q1 2025, Joule鈥檚 unified experience is reaching more customers across more 麻豆原创 solutions, so be sure to explore everything Joule in the sections below.
• Less manual work and democratized access are the name of the game for 麻豆原创 Business AI in business transformation management. Joule for developers is front and center with code generation and optimization across ABAP, 麻豆原创 Build Code, and 麻豆原创 BTP Cockpit. 麻豆原创 Signavio Process Manager and 麻豆原创 Signavio Process Intelligence let customers use natural language to create process diagrams (“text-to-process”) or generate analytical dashboards (“text-to-widgets”). 麻豆原创 LeanIX has a new AI-assisted inventory builder that automates IT landscape documentation. There is so much more to check out about AI in Joule for developers, 麻豆原创 LeanIX, and 麻豆原创 Signavio below.
• A lot is happening in 麻豆原创 Business AI for finance and spend. AI-assisted enterprise search, personalized “My Home” page features, situation handling, and error explanations are all coming to 麻豆原创 S/4HANA Cloud Public Edition. Joule also expands to S/4HANA Cloud Private Edition, automating journal uploads, service initiations, trade classifications, and more. Plus, additional AI updates are coming to Concur Expense. Dive into everything below.
• 麻豆原创 Business AI for procurement and supply chain are flush with new AI enhancements. Joule joins 麻豆原创 Ariba and 麻豆原创 Field Service Management for natural language navigation and task completion. 麻豆原创 Ariba Category Management offers AI-assisted category recommendations to help streamline strategic planning. 麻豆原创 Green Token introduces AI-powered declaration image analysis for automatic data extraction from supplier declarations. There is much more to see, so check out procurement and supply chain below.
• 麻豆原创 Business AI for IT and developers has a range of exciting tools that will increase productivity and efficiency. 麻豆原创 Datasphere gets AI-powered content generation and natural language search, further evolving into our overall data strategy with 麻豆原创 Business Data Cloud. Generative AI Hub in 麻豆原创 AI Core and 麻豆原创 AI Launchpad offers new large language models (LLMs) to ensure the best fit for customized AI use cases. Its new model library feature simplifies LLM discovery and selection with detailed model cards and one-click deployment and its grounding management feature simplifies the management of grounding pipelines, enabling developers to create, modify, and search repositories using natural language. The new 麻豆原创 HANA knowledge graph engine enhances LLM responses by grounding them in business-specific knowledge. This is just the tip of the iceberg; jump into everything and more below.

The first quarter is off to a strong start, but 2025 will see us deliver more use cases 鈥� on top of the 鈥� across our entire range of solutions. Customers can stay updated with forthcoming  releases .

麻豆原创 Business AI for business transformation management

麻豆原创 BTP, ABAP environment
麻豆原创 S/4HANA Cloud Public Edition
Joule for developers, ABAP AI capabilities
General availability

With Joule, developers can quickly generate precise, contextualized code snippets and explanations. Joule uses purpose-built LLMs designed for 麻豆原创 workloads. The ABAP LLM, for example, powers code predictions and explanations, helping developers work more efficiently.

Joule can also provide developers with real-time, context-aware support for code completion and optimization and create automation pipelines that understand the customers鈥� application environment, development project artifacts, and 麻豆原创-specific syntax.

Key capabilities include:

• Predictive code completion based on context, comments, and project heuristics
• Code explanations of core data services view entities, classes, interfaces, and functional modules
• AI-powered assistance for documentation, best practices, and new concepts
• Workflow development and decision assistance based on processes, API specifications, and connected systems

With these ABAP AI capabilities in Joule, developers can expect up to a 20 percent*鈥� reduction in time and effort spent writing ABAP code and a 25 percent鈥�* reduction in time and effort spent testing ABAP code.

In addition, the introduction of the ABAP AI SDK, powered by intelligent scenario lifecycle management, serves as an AI toolbox for ABAP developers. It allows them to use LLMs available through the generative AI hub in 麻豆原创 AI Core and seamlessly infuse AI capabilities into their custom ABAP applications.

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麻豆原创 Signavio Process Manager
AI-assisted process modeler, text to process
General availability

Process modelers can use the AI-assisted process modeler, text to process, to create business process model and notation diagrams from simple text descriptions. This eliminates the manual effort of traditional process mapping from scratch. Intuitive functionality also means non-technical stakeholders can contribute to process design, facilitating better collaboration and shared understanding.

Process modelers can reduce their business process modeling time by up to 50 percent* and time to value for business process modeling by up to 50 percent.*

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麻豆原创 Signavio Process Intelligence
AI-assisted process analyzer, text to widget
Beta release

Business users at all operational and strategic decision-making levels can quickly analyze process data using the text-to-widget feature in 麻豆原创 Signavio Process Intelligence. This feature allows users to create dashboard widgets instantly using natural language queries, democratizing data analysis and reducing the reliance on specialized analysts for routine tasks. The result is broader access to process insights, faster time-to-value, and increased efficiency for the entire organization.

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麻豆原创 LeanIX solutions
AI-assisted inventory builder
General availability

Enterprise architects can now effortlessly document their IT landscapes with the 麻豆原创 LeanIX AI-assisted inventory builder. This feature lets you easily upload various data formats, including documents, PDFs, diagrams, and pictures. Once uploaded, the AI automatically discovers and extracts relevant architectural elements like applications and IT components.

This translates to significant business value with up to an 80 percent* reduction in the time required to create factsheets, up to a 75 percent* reduction in project implementation timelines, and up to 75 percent faster time to value, ultimately increasing productivity and freeing valuable resources.

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麻豆原创 LeanIX solutions
Joule
Early Adopter Care

Enterprise architects can quickly find the information they need within 麻豆原创 LeanIX using the unified copilot Joule. Joule allows you to search for and navigate to fact sheets, reports, and diagrams from anywhere within the application using simple natural language queries. This boosts productivity by simplifying information discovery and reduces the need for extensive training, especially for infrequent users.

The business impact is substantial, with up to a 50 percent* improvement in search time for relevant documentation and factsheets and up to a 75 percent* reduction in time to productivity for all 麻豆原创 LeanIX users.

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麻豆原创 Central Business Configuration
AI-assisted scoping and configuration services
General availability

Business process owners and IT administrators can now effortlessly manage AI capabilities across their entire 麻豆原创 landscape with 麻豆原创 Central Business Configuration. The new AI-assisted scoping and configuration services tool provides a central hub integrated with 麻豆原创 for Me. It is available free of charge to activate, deactivate, and test 麻豆原创 Business AI features.

This eliminates the previous complexities of individual solution activation and allows you to quickly deploy and leverage the full potential of 麻豆原创’s AI portfolio, saving valuable time and resources while driving innovation.

麻豆原创 Central Business Configuration is free for customers and partners.

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麻豆原创 Business AI for finance and spend

麻豆原创 S/4HANA Cloud Public Edition
AI-assisted explanations of fixed asset deprecation keys, AI-assisted easy filter, AI-assisted smart summarization, and AI-assisted financial business insights
General availability

After a successful beta program conducted with dozens of customers, we are thrilled to announce that these features are now generally available for all 麻豆原创 S/4HANA Cloud Public Edition users:

• reduces implementation effort by 75 percent and slashes the time spent analyzing and resolving fixed asset and depreciation inquiries by 90 percent
•   delivers 83 percent faster filtering in Fiori elements-based list reports, increasing user satisfaction and productivity
•   saves users 88 percent of the time spent summarizing Fiori elements-based object pages and increases user and stakeholder satisfaction
• reduce the time spent analyzing cost center report summaries by 50 percent and summarizing/documenting them by 65 percent

麻豆原创 S/4HANA Cloud Public Edition
AI-assisted easy enterprise search, AI-assisted smart personalization of My Home, AI-assisted situation handling, and AI-assisted error explanation
Beta release

The latest update of 麻豆原创 S/4HANA Cloud Public Edition includes advanced AI capabilities, empowering users across supply chain, finance, procurement, and more to operate smarter and faster. By automating tasks, providing actionable insights, and enabling better decision-making, they help boost the productivity of business users. Examples include:

• finds relevant data of business objects in 麻豆原创 S/4HANA Cloud Public Edition using natural language
• offers context-specific, actionable recommendations, reducing resolution time and accelerating decision-making for faster recovery from disruptions
• enables a better understanding of errors in elements-based 麻豆原创 Fiori apps and initial resolution recommendations

We also expanded Joule鈥檚 capabilities in 麻豆原创 S/4HANA Cloud Public Edition. For instance, business users can access critical business information with . Using natural language queries in Joule, they can instantly generate cards summarizing key data and add them to their “My Home” page with a single click. This empowers them with increased productivity and reduced training time while expanding the availability of personalized insight cards tailored to individual needs. On average, 麻豆原创 S/4HANA Cloud Public Edition users can execute transactional tasks 90 percent* faster, thanks to Joule.

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麻豆原创 S/4HANA Cloud Private Edition

With this 2023 FPS03 release, we have shipped innovative AI capabilities that help businesses increase employee productivity, assist in decision-making, and provide predictive insights to better adapt to changing demands and compete in an unpredictable environment. 

AI-assisted journal upload
General availability

Accountants working on period-end journal entries can streamline their work with AI-assisted journal upload in 麻豆原创 S/4HANA Cloud Private Edition. This new 麻豆原创 Fiori app automates the creation and upload of manual journals. Upload guidance documents, create journal upload cases, and let the AI generate compliant posting proposals. AI-assisted journal upload reduces manual effort by up to 85 percent* per accrual and provision case. It also improves data quality through automated validation, strengthens compliance with full audit trails, and empowers finance teams to become a more strategic and lean function.

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AI-assisted in-house service initiation
General availability

Repair shop managers struggling with mountains of paperwork can now enjoy a streamlined alternative to manual data entry. The AI-assisted in-house service initiation solution uses cutting-edge Document Information Extraction to automatically capture data from existing paper documents and seamlessly populate the 麻豆原创 system, creating a ready-to-use list of repair objects for the team. Repair staff can then review the generated order before processing it to completion.

It eliminates tedious data entry, reduces errors, and prevents data loss, especially crucial when deadlines are tight. Users gain valuable time back, saving up to 50 percent* of the time needed to prepare the confirmation notices of conducted service orders.

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AI-assisted generation of trade classification proposals
General availability

Compliance officers and international trade professionals can streamline global trade compliance with AI-assisted trade classification automation in 麻豆原创 S/4HANA Cloud Private Edition. Users can leverage to generate intelligent proposals for customs tariff numbers and commodity codes based on existing product classifications. These proposals can be quickly activated for single or multiple products, eliminating manual research and ensuring accurate and consistent classifications across the product portfolio.

This automation offers up to a 50 percent* reduction in time and cost for the product classification process to boost productivity, reduce compliance risks, and accelerate time-to-market for internationally traded goods.

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AI-assisted labor demand planning
General availability

AI-assisted predictive labor demand planning allows warehouse supervisors to forecast workload needs precisely for picking and packing processes. The feature uses historical data to predict task durations, eliminating guesswork and complex configurations. This leads to up to a 50 percent increase in warehouse supervisor productivity and up to a five percent reduction in delays related to customer order shipments and deliveries. Warehouses using this tool gain greater transparency into operations, better optimize resource allocation, and improve their on-time delivery fulfillment, boosting customer satisfaction.

.

This release also expands transactional and navigational capabilities in Joule across critical business functions, including:

• Dispute and payment resolution (a detailed description of the dispute resolution agent is below)
• Revenue accounting, contracts, and reconciliation
• Sales order management, issue resolution, and billing info
• Service confirmations: details, actions, and lifecycle
• Maintenance order, notification, and job management
• Project work breakdown structure (WBS) and network management
• Purchase requisitions, updates, and details
• Bill of materials (BOM) and change record access
• Invoicing, billing, and clarification case views

The new features above empower users to automate tasks, access information quickly, and streamline their workflows. This will drive greater efficiency and faster time to insight across the organization.

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麻豆原创 S/4HANA Cloud Private Edition
Dispute resolution agent
Beta release

Accounts receivable clerks can streamline dispute resolution with the intelligent dispute resolution agent in 麻豆原创 S/4HANA Cloud Private Edition. Instead of manually identifying discrepancies, clerks can use AI-driven automation to quickly analyze invoice details and contractual terms, easily detecting errors or mismatches. The system proactively suggests next steps, such as creating a credit memo, ensuring financial accuracy and faster resolution. By automating error detection and resolution, clerks save valuable time and resources while maintaining control over key decisions.

Faster dispute resolution builds trust with vendors, strengthens relationships, and keeps financial operations running smoothly.

With this AI agent, contract accountants can expect to reduce dispute management handling costs by up to 30 percent*, customer churn attributable to disputes by up to 10 percent*, and days sales outstanding (DSO) by up to one percent.*

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Concur Expense
AI-assisted chart of accounts upload
General availability

Setting up Concur Expense just got easier with an automated chart of account uploads. Finance administrators can now seamlessly import expense accounts directly from their accounting systems, such as QuickBooks Online or Xero, or by uploading a chart of accounts file. This feature automatically creates and maps expense types and account codes within Concur Expense, eliminating manual data entry and ensuring accurate alignment with existing financial systems.

The result is a 50 percent*鈥� faster master data setup process, reduced administrative overhead, and a more efficient expense management experience from the start.

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Concur Expense
AI-assisted policy assistance
Early Adopter Care

Finance teams and business travelers often struggle with complex and ever-changing expense policies, leading to errors and frustration. The policy assistance feature in Concur Expense provides real-time guidance and alerts before and or during their business trip, prior to money being spent, allowing the business traveler to make compliant spend decisions during their business trip.

This drives compliant spending, improves the traveler experience, minimizes expense report issues, and can lead to faster reimbursement. Ultimately, companies can reduce costs, boost policy awareness and guide finance teams to make compliant spend decisions.

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麻豆原创 Business AI for procurement

麻豆原创 Ariba Category Management
AI-assisted category strategy recommendation
General availability

Category managers can significantly improve their strategic planning with 麻豆原创 Ariba Category Management. Previously, they had to spend countless hours manually analyzing cost structures, market dynamics, and other data to craft detailed strategy recommendations. With this new feature, category managers are provided with detailed recommendations to improve the category’s performance. This solution eliminates the need for time-consuming manual data analysis, empowering faster, more informed decision-making.

Streamlining the planning process accelerates category strategy development, improves savings on actively managed categories, and increases spend under management, ultimately advancing category management maturity. This translates to up to a 60 percent*鈥� improved efficiency of category management processes.

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麻豆原创 Ariba solutions
Joule
麻豆原创 Early Adopter Care

Procurement professionals using 麻豆原创 Ariba solutions, from sourcing experts to casual requisitioners, can now avoid navigational and transactional complexities. Joule now seamlessly integrates with 麻豆原创 Ariba Sourcing, Supplier Management, and Buying, providing intuitive navigation and natural language processing for information access and task completion.

This results in up to 50 percent*鈥� faster informational searches and up to 50 percent*鈥� quicker execution of navigation and transactional tasks, enabling procurement teams to redirect their efforts toward strategic activities and maximize their contribution to organizational goals.

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麻豆原创 Business AI for supply chain

麻豆原创 Integrated Product Development
AI-assisted digitalization of legacy drawings
Beta release

For companies with extensive legacy 2D drawings, 麻豆原创 Integrated Product Development now offers automated hotspot creation and business data mapping. This feature streamlines the digital transformation of these drawings and allows users to quickly link visual elements to backend data for applications like interactive spare part catalogs and asset management. This increases aftermarket sales revenue and improves customer satisfaction through enhanced service efficiency and more effective stock management.

For example, this results in an up to 10 percent* improvement in field service technician productivity and annual savings of 鈧�71,000* for a company of 2,000 employees and 鈧�1 billion of annual revenue.

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麻豆原创 Green Token
AI-assisted declaration image analysis
Beta release

Sustainability managers and procurement teams can now use the declaration image analysis feature in 麻豆原创 Green Token to automatically search, validate, and extract information from supplier sustainability declarations.

Gone are the days of manual data entries or sifting through countless documents. The data is now seamlessly embedded in 麻豆原创 Green Token, enabling enhanced traceability and compliance with sustainability standards and regulations. This automated data extraction eliminates the need for costly, time-consuming in-house data extraction solutions and ensures accurate data capture from sustainability declarations such as ISCC PLUS.

This eliminates the cost of data extraction tools and reduces the time needed to search for declarations. It also decreases the time required to review, interpret, and post data by up to 93 percent.*

.

麻豆原创 Field Service Management
Joule
麻豆原创 Early Adopter Care

Dispatchers can streamline their processes with Joule in 麻豆原创 Field Service Management. By leveraging intuitive conversational search, dispatchers can quickly and easily find the necessary information. Ask Joule a question using natural language and receive instant answers from 麻豆原创 Help Portal, eliminating the time-consuming process of manual searches. Dispatchers can also plan service orders using transactional capabilities in Joule.

This translates to an up to 12.5 percent* increase in dispatcher productivity, freeing valuable time for more strategic tasks. Moreover, Joule empowers dispatchers to optimize resource allocation, reducing erroneous field service deployments by up to five percent* and driving greater operational efficiency.

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麻豆原创 Business AI for sales and service

麻豆原创 Sales Cloud Version 2 and 麻豆原创 Service Cloud Version 2
AI-assisted duplicate detection
General availability

To detect duplicate sales and service orders, sales and service agents can scan the customer database and existing service orders with AI-assisted duplicate detection. This helps sales agents save time and prevents the creation of duplicate records, ensuring a cleaner database for operations and sales forecasts. Service agents also benefit from reduced mis-dispatch of field technicians, ensuring higher customer satisfaction.

Service agents can expect a complete elimination of in-field service mis-dispatches, and both sales and service agents can reduce the time it takes to detect potential duplicate service orders and records by up to 60 percent.*鈥�

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麻豆原创 Sales Cloud Version 2
Joule
麻豆原创 Early Adopter Care

Sales teams can win more deals with Joule for 麻豆原创 Sales Cloud. Joule enables more effective customer interactions by directly providing intelligent recommendations and insights within the sales workflow. Joule鈥檚 understanding of natural language queries means it can deliver context-specific and accurate search results, guiding users to precisely the information they need within the application.

This offers up to 50 percent* faster informational search and 30 percent* faster navigation for transactional tasks, directly boosting sales team productivity and enhancing the customer experience with more informed and efficient interactions.

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麻豆原创 Business AI for marketing and commerce

麻豆原创 CX AI Toolkit
AI-assisted CX agents
General availability

AI-powered automation offered by the will change how customer service agents handle complex cases within 麻豆原创 Sales and Service. This no-code solution allows businesses to configure AI agents that intelligently classify and route cases, automatically capture knowledge from resolved issues, and quickly surface answers from across the organization’s knowledge base.

This automation frees employees to focus on high-value interactions, improves service quality, provides faster resolution times, and increases customer satisfaction. Organizations can achieve up to a 50 percent鈥� improvement in sales staff productivity of agent-handled tasks and a 50 percent鈥� improvement in service staff productivity of agent-handled tasks.

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麻豆原创 CX AI Toolkit
AI-assisted shopping assistant
麻豆原创 Early Adopter Care

E-commerce businesses looking to enhance their online shopping experience can get game-changing benefits from the shopping assistant in 麻豆原创 CX AI Toolkit. This intelligent assistant integrates with 麻豆原创 Commerce Cloud, allowing customers to interact and find products using natural language, compare options, and receive personalized recommendations, much like a helpful in-store sales associate.

This conversational approach streamlines product discovery, increasing conversion rates, and offers higher average order values through effective up-selling and cross-selling opportunities. Looking at the numbers, this feature provides a five percent*鈥� increase across online conversion rate, average order value, and repeat purchases.

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麻豆原创 Emarsys Customer Engagement
AI-assisted report builder
Beta release

Marketing professionals constantly need to analyze campaign performance and prove their campaigns’ . With the report builder in 麻豆原创 Emarsys Customer Engagement, they can quickly generate custom reports on any metric using simple, natural language prompts. This eliminates the need for complex data manipulation or reliance on IT, freeing up valuable strategic planning and optimization time.

Employees will enjoy an up to 25 percent鈥�* reduction in the time spent on report creation and analysis. Overall, the result is increased marketing efficiency, data-driven decision-making, and the ability to clearly communicate campaign successes and areas for improvement to stakeholders, ultimately driving better business outcomes.

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麻豆原创 Business AI for human resources

麻豆原创 SuccessFactors Incentive Management
Joule
麻豆原创 Early Adopter Care

Employees can get instant answers to incentive management questions with Joule for 麻豆原创 SuccessFactors. For example, sales representatives can now use natural language to quickly access their compensation details, eliminating the need for time-consuming inquiries. Joule provides 24/7 self-service support, delivering accurate and secure responses in seconds. This empowers sales teams to focus on selling, significantly reducing administrative overhead and boosting overall productivity.

The result is a dramatic improvement in efficiency, with an up to 70 percent* reduction in inquiry response time and an up to 85 percent* self-service resolution rate.

.

麻豆原创 Business AI for IT and developers

麻豆原创 Datasphere
AI-assisted content generation for catalog
General availability

With the content generation feature in 麻豆原创 Datasphere, data stewards can better handle the growing volume of data assets. It automates creating business descriptions, assigning business terms, and defining KPIs for data assets within the catalog. Stewards no longer must have deep technical expertise in complex 麻豆原创 data structures. AI-assisted content generation will automatically generate context-aware and comprehensive descriptions and apply relevant tags from a hierarchical list.

This reduces the time required to maintain metadata for catalog assets, freeing valuable time for strategic data governance initiatives by up to 87 percent. Improved data discoverability and comprehension empower data modelers and business users to leverage data more effectively, leading to better decision-making and increased productivity across the organization.

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麻豆原创 Datasphere
AI-assisted search
General availability

Data analysts and business users struggling to find the right data assets within 麻豆原创 Datasphere can now benefit from the AI-assisted search feature, which offers a groundbreaking approach to data discovery. It empowers users to search using natural language queries, eliminating the need to navigate complex filter options and manually sift through hundreds of results. Users can ask for what they need, regardless of query complexity, and the search feature will understand their request and deliver precise results across the repository, catalog, and data marketplace.

This means an up to 90 percent* reduction in time spent on complex data artifact searches, enabling users to focus on analysis and insights generation rather than time-consuming data hunts.

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麻豆原创 BTP cockpit
Joule
General availability

After a limited beta program, Joule in 麻豆原创 BTP cockpit is now generally available with its first set of capabilities. It helps platform administrators ask questions related to their 麻豆原创 BTP resources, such as users or the runtime environment, in the cockpit. Users can also ask questions about 麻豆原创 BTP services or the cockpit.

Joule references 麻豆原创 BTP cockpit documentation, summarizes its findings, and links to relevant help content. Platform administrators will experience up to 95 percent faster informational searches and up to 90 percent more rapid execution of navigation and transactional tasks.

.

麻豆原创 HANA Cloud
AI-assisted database administration
General availability

麻豆原创 HANA Cloud database administrators can simplify complex tasks and boost operational efficiency using this generative AI-powered feature. AI-assisted database administration can quickly generate summaries of issues and alerts, provide seamless navigation to specific applications, convert natural language into SQL statements, and prompt responses to queries for 麻豆原创 HANA Cloud.

These capabilities give administrators an up to 20 percent* reduction in management effort for 麻豆原创 HANA Cloud instances, accelerate productivity for new database administrators, and reduce the time required for issue resolution.

.

Generative AI hub in 麻豆原创 AI Core and 麻豆原创 AI Launchpad
Product enhancements
General availability

The generative AI hub in 麻豆原创 AI Core and 麻豆原创 AI Launchpad enables developers to access market-leading LLMs in a governed environment, run AI models securely and cost-effectively, and maximize value creation from generative AI use cases for 麻豆原创 applications. Developers can save up to 60 percent* on IT expert efforts to onboard and run AI models securely and increase value realization by up to 50 percent* once use cases are available to end users.

This quarter, we released the grounding management feature, designed to simplify the management of grounding data pipelines. It empowers developers to manage their data repositories easily without coding skills. They can easily create, duplicate, and delete repositories. In addition, they can configure and run searches using natural language. Users can view detailed information about their data, manage search settings — for example, chunk size or number of documents retrieved — and integrate search results into their workflows.

.

The new model library feature helps users find and understand the available LLMs in generative AI hub without getting lost in technicalities. With simple browsing modes like “catalog” and “leaderboard” for comparing performance, they can easily pick the perfect model for their needs. Detailed model cards provide all the necessary information, from data types to costs and quality metrics, including safety metrics. Leveraging an LLM is just a click away: check it out and see how effortless model exploration can be.

.

Furthermore, we鈥檙e excited to introduce further content filtering capabilities via Meta鈥檚 Llama Guard framework. Hosted by 麻豆原创, this advanced content filtering module offers enhanced safety by screening inputs and outputs for various content categories, including violent crimes, hate speech, and sensitive topics like child exploitation and self-harm. By providing comprehensive filtering capabilities, LLama Guard helps ensure a safer and more secure user experience, giving you peace of mind knowing that your interactions are protected.

Finally, the generative AI hub has added some fantastic LLMs to its lineup. We now have cutting-edge reasoning models like OpenAI’s o1 and o3-mini and frontier models such as Anthropic Claude 3.7 and Gemini 2.0 Flash. These models have performed exceptionally well in public benchmarks, making top-notch AI accessible to all our developers. Whether you’re working on agentic tasks or need help with completions, these innovative models have got you covered. Check them out and see the difference they can make in your AI projects: visit .

Finally, an 麻豆原创 Early Adopter Care program dedicated to 麻豆原创’s generative AI hub orchestration workflow is now . Since Q4 2024, the orchestration workflow has ensured that LLMs deliver reliable, business-ready results by providing structured inference orchestration, content filtering, and data masking.

Document Information Extraction, premium edition
Product enhancements
General availability

The instant learning feature released last quarter has been enhanced to support 麻豆原创 default schemas for standard document types. Once the user activates instant learning in , premium edition, the service can use extraction result feedback to select the best model for individual fields in pre-configured 麻豆原创 schemas for invoices, payment advice, and purchase orders.

.

Moreover, the service now supports processing text-based files such as DOC, DOCX, EML, MSG, OFT, TXT, and similar, as well as business card, invoice, purchase order, and custom documents in the following file types: CSV, NUMBERS, ODS, TSV, XLAM, XLS, XLSB, XLSM, XLSX, XLT, XLTM, XLTX, and XML. These additional document types improve its usability and help it execute business processes with greater efficiency.

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Users can also subscribe to the Document Information Extraction UI using the Identity Authentication service. This service will handle authentication and authorization tasks in 麻豆原创 BTP with a single sign-on solution across 麻豆原创 software. It allows smooth user authentication, enabling support for both internal and external users.

Document Information Extraction is also available in new data centers, including Google Cloud Platform in the Kingdom of Saudi Arabia (SA30), Google Cloud Platform in India (IN30), and AWS in Brazil (BR10).

.

麻豆原创 Build Process Automation
Generative AI capabilities
General availability

Process developers can streamline and optimize data processing automation from numerous documents efficiently and effectively with the generative AI capabilities of Document Information Extraction premium edition. This feature is now natively embedded into . It automates document reading and processing using AI with schema-based data extraction, eliminating the need for manual intervention and reducing time and effort to process documents by up to 50 percent.*

It also eliminates the need to create and maintain Document Information Extraction templates by enabling schema-based extraction and field-specific prompt engineering, reducing the time and effort required to maintain document templates by up to 80 percent.*

In addition, several generative AI capabilities have been introduced in 麻豆原创 Build Process Automation. Citizen developers can now interactively generate and edit artifacts from natural language descriptions, receive active content recommendations and gap analysis, and generate summarization of artifacts. They can expect to save up to 40 percent* of their implementation time.

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麻豆原创 Build Code
Product enhancements
General availability

Developers can now use Joule in to ask questions related to 麻豆原创 products, services, and software development or engineering and get answers based on content from 麻豆原创 Help Portal.

They can easily retrieve answers to questions about their 麻豆原创 BTP ABAP environment and other 麻豆原创 products. Based on content from 麻豆原创 Help Portal, they can also get guidance on development tools and practices.

.

麻豆原创 HANA Cloud
Knowledge graph engine
General availability

The new knowledge graph engine embedded in 麻豆原创 HANA Cloud offers 麻豆原创 HANA application developers the chance to build meaningful business applications powered by generative AI.

The knowledge graph engine enhances LLM responses by grounding them in business-specific knowledge stored in the knowledge graph, enabling precise natural language querying and improved AI-driven outputs. It also supports graph-based retrieval-augmented generation scenarios, where relevant information is dynamically retrieved from the knowledge graph to improve AI outputs.

麻豆原创 Knowledge Graph integrates seamlessly within 麻豆原创 HANA Cloud, reducing the need for additional data handling while maintaining data quality, governance, and security for intelligent applications. The knowledge graph engine improves decision-making, enhances logical formality, and improves performance and scalability in handling RDF with relational data.

and .

Philipp Herzig is is chief technology officer and chief AI officer of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, expressor implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

麻豆原创 is embedding its generative AI copilot Joule into 麻豆原创 Concur solutions, bringing the portfolio one step closer toward a fully automated travel and expense management process:

• Joule in the Concur Expense solution will help answer employees鈥� questions and ensure that expense reports are ready for submission with minimal effort. General availability is expected in the second quarter 2025.
• Joule in the Concur Travel solution — now in the 麻豆原创 Early Adopter Care program with general availability expected later this year — will help plan locations for offsite meetings, providing meeting location recommendations and high-level flight and hotel cost estimates.

麻豆原创 Concur also announced an expanded partnership with American Express to simplify expense management for shared customers. 麻豆原创 Concur and American Express are launching a real-time authorization data capability whereby American Express Corporate Card purchases automatically generate and categorize expenses in Concur Expense at the time of spend. This feature will first be available for meal expenses. It will also include mobile notifications that send the employee expense policy reminders in the moment.

麻豆原创 Concur is also working to expand access to its integration with , which automates expense entry at the time of purchase, so more Mastercard customers can benefit from a simpler and more efficient experience.

Additionally, , featuring over 2 million properties across 180 countries with competitive rates, into the new Concur Travel solution, providing customers with access to comprehensive hotel content, including negotiated programs and preferred partner rates.

With its Concur Travel and Concur Expense solutions, 麻豆原创 remains the market share leader for worldwide travel and expense management software, * These leading solutions are part of , 麻豆原创鈥檚 comprehensive portfolio of integrated solutions that combines our core cloud ERP and line-of-business applications, fueled by unmatched   business data and actionable AI.

To learn more about  or to join the virtual event, visit the .

Visit the . Follow 麻豆原创 at .

Media Contact:
Kelly Sheldon Murray, +1 (978) 708-6821, kelly.murray@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

*IDC Worldwide Travel and Expense Management Software Market Shares, 2023: Resurgence of Business Travel Heralds a New Chapter in Travel and Expense Software, doc #US51658524, August 2024

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.  Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2025 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

With more than 17,000 customers now leveraging 麻豆原创 Build solutions globally, momentum continues to surge, enabling developers to build, automate, and innovate with greater speed and ease. Today, we鈥檙e taking a huge step forward to bolster developer productivity within 麻豆原创 Build solutions!

We鈥檙e thrilled to announce new Joule-powered AI capabilities for 麻豆原创 Build Process Automation and 麻豆原创 Build Apps. These enhancements complement the previously announced AI capabilities in and 鈥攅mpowering developers of all skill levels to build more efficiently by leveraging comprehensive, AI-infused developer tools to deliver precise, contextualized outcomes powered by purpose-built, 麻豆原创-centric AI models. This can free up time for developers to be more productive, creative, and proficient in accelerating ABAP, Java, JavaScript, and visual tool-based application development and automation of 麻豆原创 processes.

Let鈥檚 look at how Joule can unlock new levels of productivity:

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鈥淭he latest AI features across 麻豆原创 Build solutions provide developers with a powerful tool kit to build and extend business applications across both 麻豆原创 and non-麻豆原创 systems.鈥�

Holger Mueller, Principal Analyst & VP at Constellation Research, Inc.

Comprehensive developer assistance for all 麻豆原创 development needs

Joule can understand 麻豆原创 development framework intricacies, anticipate developers鈥� needs, offer intelligent suggestions, and automate repetitive, mundane tasks like documentation and sample data generation. It can enable developers across low-code, pro-code, and automation projects to be more productive, creative, and proficient in accelerating apps or extensions for business applications like 麻豆原创 S/4HANA.

Key capabilities include:

• Application creation: Generate code, UI, data models, and sample data across 麻豆原创 programming models for Java, JavaScript, and ABAP, using Joule
• Code optimization: Refactor code, create unit tests, and generate code explanations, summarizations, and more with natural language queries and intuitive actions with Joule
• Process and workflow automation: Generate automation workflows and business rules using natural language queries

鈥淚n utilizing generative AI, 麻豆原创 Build Code offers our joint clients easier integration capabilities and a streamlined developer experience for cloud application development, boosting overall productivity and driving tangible value.鈥�

Chip Kleinheksel, Global 麻豆原创 Chief Technology Officer and Principal, Deloitte Consulting LLP

Contextual and precise results with purpose-built LLMs

Joule uses purpose-built large language models (LLMs) specifically tailored for 麻豆原创 workloads, such as our ABAP LLM, which can power code predictions and explanations. Developers can derive precise, contextualized results鈥攍ike code snippets or explanations鈥攆aster and more efficiently. Joule can also provide developers with real-time, context-aware support for code completion and optimization, as well as automation pipeline creation that understands the customers鈥� application environment, development project artifacts, and 麻豆原创-specific syntax.

Key capabilities include:

• Predictive code completion based on context, comments, and project heuristics
• Code explanations of core data services (CDS) view entities, classes, interfaces, and functional modules
• AI-powered assistance for documentation, best practices, and new concepts
• Workflow development and decision assistance based on processes, API specifications, and connected systems

Integrated AI tooling for seamless development

Developers can now enjoy a fully AI-infused development environment. Joule’s capabilities are integrated within 麻豆原创 Build development tools, including ABAP, to help ensure a smooth, cohesive AI-enhanced experience. This AI integration helps eliminate the headache of switching between development and AI tools and can generate actionable insights and outputs within a single place so developers can focus on what they do best鈥攂uilding innovative solutions.

Key capabilities include:

• Joule support for 麻豆原创 Fiori apps, 麻豆原创UI5 guided development, and more in 麻豆原创 Build solutions
• Joule integrated inside 麻豆原创 Business Application Studio and ABAP development tools for Eclipse for all Java, JavaScript, and ABAP-related development tasks
• Joule integrated into 麻豆原创 Build Process Automation project canvas for generation and summarization of processes, decisions, forms, and more, right in place using natural language

Road map and future enhancements

Our commitment to AI-driven innovation for developers is unwavering. Over the last year, we鈥檝e unveiled groundbreaking capabilities across our portfolio: Joule in , , , , AI agents embedded deep within 麻豆原创 Business Suite processes, and more. 

Looking ahead, we have a complete road map of cutting-edge features, including optimizing business logic, automating documentation, and enhancing data protection and AI compliance. To enable an agentic journey, developers will be able to develop custom AI agents tailored to their specific needs. Additionally, as customers continue to adopt 麻豆原创 S/4HANA Cloud, we plan to simplify the migration journey with enhancements that can meticulously analyze legacy code, provide clear code explanations, and suggest code optimizations. This will help ensure customers have a smooth, intelligent transition to the cloud alongside 麻豆原创鈥檚 clean core guidelines.

These new features will help empower developers to build more innovative, efficient, and secure workflows and applications. Stay tuned for more AI-driven innovations!

Get started for free

Don鈥檛 wait to transform your development experience! You can take advantage of our Joule for developer capabilities today at no charge for a limited time.

• Activate the  of ABAP AI capabilities
• Access the  free trial
• Explore Joule for developers with our 

We can鈥檛 wait to see how developers leverage the new Joule capabilities in 麻豆原创 Build solutions.

Happy coding!

Michael Ameling is general manager and chief product officer for 麻豆原创 BTP and a member of the 麻豆原创 SE Extended Board.

Retailers are looking at new technology tools like AI to help them move into new channels and discover new growth streams, enter new markets and find new ways to engage with consumers, and work with suppliers to find efficiencies in their supply chain, Kristin Howell, 麻豆原创鈥檚 global vice president of Retail Solution Management, said.

鈥淭here is a tremendous market out there for retailers to utilize AI and improve their business processes,鈥� she said during an open theater session at the 麻豆原创 booth during the show.

Over two days, retailers who came to the 麻豆原创 booth spoke about the challenges they face, talked about data, data management, and the opportunities presented by AI, and heard about how new solutions and services from 麻豆原创 tailored specifically to the retail sector can help them become more efficient and serve their customers better.

麻豆原创 officially launched the at the show. The new solution helps centralize operational data and can integrate finance, procurement, and merchandising processes.

“Whether you’re a franchisee with a handful of stores or the biggest retailer out there, there’s a certain level of complexity that comes with running any retail business, especially with consumers who expect a very flexible fulfillment experience,” Howell said during a press briefing. “In order to really fulfill these expectations profitably and meet the needs of these consumers, we believe that this retail-tailored ERP solution is going to make the difference for them.”

麻豆原创 also announced plans to bolster its retail offerings with two new tools鈥攁 refreshed loyalty management cloud service and a generative AI assistant designed to give store employees and consumers an easier way to find what they need.

麻豆原创 S/4HANA Cloud Public Edition retail, fashion, and vertical business is available immediately, while the shopping assistant, which is based on听, 麻豆原创鈥檚 unified copilot, will be released during the first half of 2025.听

The shopping assistant is designed to make recommendations and help shoppers find what they are looking for more easily while also helping store associates close sales. Because it can be integrated into the retailer鈥檚 ERP system, users can discover specific information, like the current availability of stock.

The new loyalty management application takes data from 麻豆原创 S/4HANA Cloud and applies AI to create profiles around customers and their shopping behavior and preferences.

Howell identified the customer experience in retail, including product recommendations and helping consumers search, 鈥渁s areas where retailers can start consuming AI.鈥� She also expects retailers to be early adopters of AI tools to help with their pricing strategies and to use generative AI copilots, including 麻豆原创鈥檚 offering, to ask questions and get answers immediately鈥攁bout inventory for example鈥攚herever they are.

While it’s still early days in terms of adoption, almost every retailer presenting in the 麻豆原创 booth theater at the show said they are preparing to implement AI tools and some said they are already testing AI tools in specific use cases. And 麻豆原创鈥檚 retail team made it clear at the NRF show that 麻豆原创 is ready to help.

The 鈥淎I Has a Seat in the C-Suite鈥� , conducted by Wakefield Research and sponsored by 麻豆原创, polled 300 C-Level executives at companies with at least $1 billion in annual revenue in the United States. Additional findings included:

• 74 percent of executives place more confidence in AI for advice over their family and friends.
• 55 percent of executives work at firms where AI-driven insights have replaced or frequently bypass traditional decision-making. This is especially true for companies with $5 billion or more in revenue.
• 48 percent of executives use generative AI tools daily; 15 percent use AI multiple times per day.

鈥淢ost executive decisions are based on a combination of the data, how they feel and discussions they’ve had with people they trust,鈥� said Jared Coyle, chief AI officer for 麻豆原创 North America. 鈥淲hat this data tells us is that AI is part of that trusted inner circle.鈥�

For a majority of the executives surveyed (52 percent), AI is trusted most to analyze data and make recommendations for decision-making. Executives also have confidence in AI to spot risks or issues they hadn鈥檛 previously considered (48 percent) and to offer alternate plans (47 percent). They鈥檙e also using AI in a multitude of other ways, including: enhancing product development (40 percent); supporting budget planning (40 percent); and performing market research (40 percent).

And the benefits of AI extend beyond the office: 39 percent of executives feel they experience a better work-life balance because of AI; 38 percent report improved mental well-being; and another 31 percent claim to experience reduced stress.

Coyle noted that many businesses still struggle with building a foundation of reliable data critical for this kind of trust because of misalignment between IT and business functions, integration challenges across systems or even concerns with the quality of the data itself.

鈥淭he only way to ensure reliable business data for AI is to have one common semantical data layer for your business,鈥� he said.

To that end, Coyle points to the 麻豆原创 Business Data Cloud solution, the company鈥檚 latest fully managed SaaS data management solution that unifies all 麻豆原创 and third-party data throughout an organization. By connecting data from every part of the business and harmonizing it more easily and quickly than ever before, 麻豆原创 Business Data Cloud can help customers make more impactful decisions faster and fuel reliable AI.

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2025 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

As a cornerstone of our Business Transformation Management portfolio, 麻豆原创 Signavio solutions help empower companies to view transformation not as an isolated project, but as an ongoing capability. With 麻豆原创 Signavio solutions, companies can constantly analyze, improve, and monitor their processes, therefore establishing continuous loops of value realization.

By harnessing the power of generative AI, the 麻豆原创 Signavio portfolio is poised to help organizations drive efficiency, enhance the user experience, and reduce barriers to entry for expert disciplines such as process mining and modeling. At the same time, new generative AI and copilot capabilities enable organizations to further accelerate the time to accrue value while working to the best of their potential.

Through this intuitive and user-friendly approach, users across an organization can receive rapid insights and recommendations that can accelerate and inform decisions, with questions asked in natural language serving as a starting point.

Text to process

What if, when building your process models, you didn鈥檛 have to start from scratch? On March 3, 2025鈥攆ollowing the integration to 麻豆原创鈥檚 co-pilot Joule; the release of the 麻豆原创 Signavio solutions, AI-assisted process analyzer capability; the release of text to insights and text to widget features, which are available via a beta program; and the introduction of the 麻豆原创 Signavio solutions, AI-assisted process recommender and performance indicators recommender鈥斅槎乖� Signavio released the process modeler, text to process capability.

The 麻豆原创 Signavio solutions, AI-assisted process modeler, text to process capability can quickly transform textual descriptions into Business Process Model Notation (BPMN) diagrams鈥攖he standard language of process modeling. In other words, this new capability can simplify and expedite process modeling, helping customers accelerate the initial creation of process diagrams and potentially redefine the way companies document their processes.

Reduced process modeling time

Process modeling for an enterprise can cost hundreds of thousands of dollars annually when factoring in the time it takes to collect inputs, then create or update hundreds of process models.

By leveraging the 麻豆原创 Signavio solutions, AI-assisted process modeler, text to process capability, the time taken in building models can be reduced significantly, helping to accelerate the initial phase of creation and allow users more time to fine-tune and perfect their models.

Support for non-technical users

By simply describing processes in plain language, non-technical users can also contribute to process modeling and improvement, as the process modeler, text to process capability can then translate these descriptions into technical process models.

This means organizations can quickly tailor and implement processes through text prompting, making process modeling ever more accessible and inclusive.

Enhanced collaboration

The AI-assisted capability can enhance collaboration by simplifying complex process descriptions and turning them into visual models. This helps improve cross-team collaboration by helping ensure a common understanding of what elements constitute a specific process model, reducing uncertainty and potential miscommunication.

The simplification of process descriptions and development of visual models also helps make model editing more flexible and responsive, which in turn helps ensure the continuous improvement of models, supported by the ability to save and refine them in 麻豆原创 Signavio Process Manager.

AI for the world of process

The process modeler, text to process capability is the latest example of how 麻豆原创 Business AI in 麻豆原创 Signavio solutions is designed for the process world, helping everyday business users as well as process modelers and experts contribute to process analysis and improvement simply by using everyday language to interact with 麻豆原创 Signavio solutions.

To discover how you can drive faster time to value and transform your business more effectively with generative AI as part of the 麻豆原创 Signavio portfolio, join our and find out more about the new generation of AI-enabled business transformation management solutions.鈥�

Lucas de Boer is global marketing program lead for 麻豆原创 Signavio.

The study revealed that 麻豆原创 Build achieved a remarkable 3x increase in speed of development and a 59 percent reduction in development effort compared to traditional custom development methods. These findings underscore the potential of 麻豆原创 Build in streamlining development processes and enhancing developer productivity.

The benchmark study evaluated 麻豆原创 Build and custom development approaches across critical dimensions, including development time, cost, and ease of use. The methodology involved a hands-on assessment and analysis of deploying applications using both methods. 麻豆原创 Build, a comprehensive platform for business application development and automation, showcased its ability to empower organizations to create enterprise-grade applications through its integrated suite of pro-code, low-code and AI capabilities from its Joule for developers integration.

Key findings from the study include:

• 3x faster project delivery: Projects reach completion in less than half the traditional timeframe through streamlined development workflows, automated service implementation, and integrated testing capabilities.
• 30% boost in development tasks using AI-assistance: The integrated AI assistant streamlined operations and tasks to provide broad value across the development process, with outstanding results at data modeling and synthetic data creation.

These results highlight the substantial business value achieved with 麻豆原创 Build. By accelerating development timelines, reducing costs, and enhancing developer productivity, it enables organizations to deliver business-critical applications faster and more efficiently. This translates to quicker time-to-market, improved agility, and increased competitiveness.

During the hands-on assessment, GigaOm analysts identified capabilities and characteristics that stand out and support 麻豆原创 Build advantages when compared to the custom development method:

• Unified development environment: 麻豆原创 Build provides a cohesive developer experience integrating coding, testing, and deployment tools, streamlining the development process.
• AI assistance: 麻豆原创’s AI copilot Joule offers code suggestions, query optimization, and problem-solving support, reducing coding time and improving code quality.
• Pre-built integrations: Out-of-the-box integrations with 麻豆原创 business applications and third-party services simplify complex system integrations.
• Visual modeling tools: Intuitive interfaces for data modeling and business process design enable rapid prototyping and reduce coding requirements.
• 麻豆原创 Cloud Application Programming Model: The architectural foundation of 麻豆原创 Build application development automatically implements enterprise-grade development standards and best practices, enforcing consistent patterns for security, scalability, and compliance.

According to GigaOm鈥檚 field analyst: 鈥淔or teams seeking to improve their development processes, 麻豆原创 Build offers a practical and efficient solution to address common challenges, such as lengthy development cycles and skill gaps. Its unified environment and automation features allow practitioners to focus on delivering business value, rather than managing technical overhead.”

GigaOm鈥檚 benchmark confirms that 麻豆原创 Build can accelerate development timelines and reduce effort compared to traditional custom development methods. By combining a unified development environment, AI assistance, and pre-built enterprise integrations, 麻豆原创 Build empowers development teams to deliver secure, scalable applications faster and more efficiently.

To explore these findings in depth, and watch the webinar, “,” where we dive into GigaOm鈥檚 methodology, discuss the outcomes, and answer questions on transforming your development strategy.

Sid Misra is vice president of Product Marketing for 麻豆原创 Build at 麻豆原创.

As we dive into 2025, 麻豆原创 is already making waves in the spend management arena. Building on last year’s momentum, we are constantly innovating our market-leading solutions so you can reduce costs, mitigate risks, improve collaboration, and make sure every spend decision is aligned with your business strategy to help drive your business forward.

Q4 Breakthroughs: Highlighting Our Latest Innovations

It was an honor to collaborate with so many of you last year. When your business is at its best, so is ours, and this mutual partnership is what fuels our commitment to innovation. In Q4, our solutions鈥斅槎乖� Ariba, 麻豆原创 Business Network, 麻豆原创 Concur, and 麻豆原创 Fieldglass鈥攎ade significant strides, particularly in 麻豆原创 Business AI. Here are just a few highlights:

• : Now generally available, this solution can provide a single source of truth for all payment and supplier data, enhanced with AI-enabled spend classifications and supplier insights. It helps streamline spend processes, cut procurement costs, manage supplier risks, and track sustainability goals.
• Generative AI in 麻豆原创 Business Network Discovery: We鈥檝e introduced generative AI capabilities to help accelerate supplier search and improve network catalog product descriptions and summaries with .
• AI flight recommendations in Concur Travel: This new feature can suggest policy-compliant flight options based on user preferences, loyalty programs, available inventory, and other factors.
• Joule, 麻豆原创鈥檚 AI copilot, got cozy in 麻豆原创 Fieldglass solutions this past quarter with the introduction of , including:
  • Interactive guidance for creating and scheduling new reports through natural conversation, helping to navigate report creation, searches, and data insights
  • Quick answers to issues or questions with concise and easy-to-digest summaries of relevant information and helpful links to learn more
  • AI-assisted job posting and statement of work template selection, recommending the most relevant one and pre-filling data fields to save you time

These innovations align perfectly with the findings. The study highlights data and analytics reporting as the top priority for procurement transformation, a need we鈥檙e addressing head-on with our AI-enhanced solutions.

New Customer Stories and Honors

We built our solutions to elevate spend management from the most mundane part of your day to the most strategic. But don鈥檛 just take my word for it. Discover how companies like , , , and leverage 麻豆原创 solutions for better control and business resilience.

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And if customer stories aren鈥檛 enough, how about customer reviews?

Every quarter, G2 publishes Grid^庐 and Index Reports that rate products based on feedback collected from the user community, along with data compiled from various online platforms and social media networks. In December, G2 announced its Winter 2025 Reports, with 麻豆原创 spend management solutions topping the leaderboards:

• : Leader in Procure to Pay, Strategic Sourcing, and Supplier Relationship Management
• : Supply Chain Business Networks
• : Leader in Expense, Travel & Expense, and Invoicing
• : Leader in Vendor Management

In the , 麻豆原创 moved up to sixth place on G2鈥檚 top 10 companies list. In the Winter 2025 G2 Reports alone, 麻豆原创 Ariba, 麻豆原创 Business Network, 麻豆原创 Concur, and 麻豆原创 Fieldglass won 107 awards across multiple categories. Only 4% of software and services on G2 receive a Leader badge, making this recognition truly special!

Media and Analyst Accolades

Our innovations continue to garner industry recognition. Here are a few key highlights:

• won the  in the Procurement/ERP Software category from Supply & Demand Chain Executive.
• 麻豆原创 Ariba was inducted into Spend Matters鈥� for being listed on its “50 Providers to Know” list for 10 years or more.
• Over the holidays, 麻豆原创 was named a Leader in the .* The report is based on IDC MarketScape鈥檚 comprehensive assessment of 麻豆原创 and feedback from our customers. Explore the findings and why 麻豆原创 was recognized in this article from my colleague Baber Farooq.
• 麻豆原创 Concur received the , which bases its Top Rated awards solely on customer feedback. Over 1,500 verified praised 麻豆原创 Concur for its positive user experience, clear budget visibility, mobile receipt capture, time-saving features during usage and reimbursement processes, seamless integration with productivity tools, and the convenience of its mobile app.

See you at 麻豆原创 Concur Fusion

We鈥檙e thrilled to announce that the 麻豆原创 Concur Fusion event is back in 2025 and will be held in beautiful Seattle, Washington. As the premier travel and expense event, 麻豆原创 Concur Fusion offers over 200 learning opportunities, access to experts and consultants, and hands-on training to help you unlock the full potential of your 麻豆原创 Concur solutions. It鈥檚 an experience you can鈥檛 miss.

Looking Ahead

As we move further into 2025, we remain committed to delivering innovation that addresses your most pressing business needs. We鈥檙e excited about the possibilities that lie ahead and look forward to partnering with you to drive your business forward. Whether it鈥檚 through our AI-enhanced solutions, our comprehensive spend management suite, or events like 麻豆原创 Concur Fusion, we鈥檙e here to support your success every step of the way.

Thank you for your continued trust and partnership. Here鈥檚 to a transformative and successful 2025!

*IDC MarketScape: Worldwide SaaS and Cloud-Enabled Direct Spend 2024 Vendor Assessment, #US52734424e, December 2024

Jeff Collier is chief revenue officer for 麻豆原创 Intelligent Spend and Business Network.

At 麻豆原创, we鈥檝e harnessed the power of artificial intelligence (AI) and other data-driven technologies to revolutionize customer support, turning it into a seamless, efficient, and value-added experience.

The Evolution of the Knowledge Economy

Beyond resolving everyday challenges, we continue to serve our customers as true business partners, collaborating with them to help them achieve their broader business goals. While we live in a knowledge economy, where economic value is derived from that knowledge and how we apply it, this paradigm is changing. As humans, our role in the economy is evolving as AI systems increasingly replicate human cognitive skills — retrieving and using the right knowledge at the right time.

In this new paradigm, success will be determined not by how much you know, but by how effectively you can allocate and manage resources to get work done. In customer support, this means moving from simply resolving issues to orchestrating AI tools and human expertise to deliver optimal outcomes.

AI, including generative AI, becomes a collaborative partner, enabling support teams to allocate resources efficiently and focus on higher-value tasks. Recognizing this paradigm shift, we go beyond resolving everyday challenges and serve our customers as true business partners, collaborating with them to help them achieve their broader business goals — as the world changes.

AI Is the Perfect Partner for Customer Support Transformation

At 麻豆原创, AI is built into core business processes of customers, connecting finance, supply chain, procurement, sales, marketing, human resources, and IT. Data-driven technologies such as AI, robotic process automation (RPA), and process mining elevate support experiences for our customers. They do it by simplifying support access, addressing complex scenarios using AI agents, and enhancing automation to increase efficiency while delivering personalized solutions, as well as taking advantage of system metrics and process insights.

The Customer Support & Cloud Lifecycle Management organization at 麻豆原创 also drives AI innovation to analyze process metrics collected from the customer鈥檚 systems to evaluate efficiency, bottlenecks, and opportunities for improvement; improve processes using domain-specific machine learning models; and build AI solutions that can be integrated into applications used in a business process or scenario.

Generative AI: Elevating Customer Support

Generative AI has been a game-changer for customer support. It empowers our support teams by enhancing the quality and speed of outcomes and enabling more personalized recommendations for customers. It also opens new possibilities for orchestrating AI services in combination with AI agents.

AI agents streamline support processes by automating time-consuming tasks, such as retrieving and assessing information, while enabling human-machine collaboration. This allows support professionals to focus on improving both customer satisfaction and operational efficiency.

Real-World Impact: AI Use Cases in Customer Support

麻豆原创 has developed more than 50 AI-driven use cases, showcasing the transformative power of AI in customer support. These include:

• Precise and fast generative AI-infused recommendations appear for customers while they type their requests. Customers also benefit from proactive recommendations on trending content and preventative recommendations like system health checks.
• Smart ticket routing ensures support tickets reach the right experts, quickly.
• Proactive issue identification detects and addresses potential problems before they escalate.
• Internal workflow enhancements deliver efficiency gains from workflows such as intelligent search, automated error categorization, clustering of tickets with the same root cause, or expert swarming for complex issues.

Other generative AI capabilities include summarizing tickets, assisting in knowledge creation, and improving communication with customers.

These advances not only elevate support experiences for 麻豆原创 customers, but also create significant efficiencies for our support engineers.

The 麻豆原创 Advantage

麻豆原创鈥檚 AI-driven support strategy is structured around three key pillars:

1. Capturing business opportunities with domain-specific AI models: By leveraging our domain expertise and historical data, we design machine learning models tailored to specific support challenges. These models enable precise and actionable recommendations.
2. Gathering real-world process insights: Using tools like 麻豆原创 Signavio, we capture and analyze detailed process insights. This provides a solid foundation for identifying improvement opportunities.
3. Building and integrating AI solutions: We integrate AI-driven solutions into existing workflows, ensuring seamless application and measurable impact. Process insights guide ongoing refinements and enhancements.

And the numbers speak for themselves: 麻豆原创鈥檚 AI support scenarios are called up more than 1 million times by our customers on an average day. More than 35,000 end users use our AI capabilities per month.

The Road Ahead: Human-Machine Collaboration in Support

The future of customer support lies in human-machine collaboration. By combining the analytical power of AI with human expertise, we can deliver unparalleled support experiences. AI agents will play a pivotal role in this transformation, assisting with things like ticket triage, data analysis, and troubleshooting, thereby enabling support teams to focus on strategic activities. As AI continues to evolve, these agents will become even more capable of providing real-time insights and proactive solutions to anticipate customer needs before they arise.

麻豆原创鈥檚 commitment to AI-driven innovation ensures that we remain at the forefront of customer support transformation. By continuously evolving our AI capabilities, we are setting the stage for a new era of value-driven, scalable, and efficient customer support.

But there is one thing that AI will never replace: the empathy, care, and passion of our support teams, ensuring every customer feels supported as we solve their challenges together. The future of customer support lies in blending AI鈥檚 analytical power with human expertise. By working together, we鈥檙e setting a new standard for customer success.

Thomas Saueressig is a member of the Executive Board of 麻豆原创 SE leading Customer Services & Delivery.
Stefan Steinle is executive vice president and head of Customer Support & Cloud Lifecycle Management at 麻豆原创.