The announcement was made at HANNOVER MESSE 2026, where they showcased PacXplorer, a high-tech packaging machine from Uhlmann that serves as both an industrial demonstrator and a development platform.

PacXplorer: Connected Production in Industrial Practice

Developed through collaboration within Factory鈥慩, the PacXplorer brings together digital twins, condition monitoring, smart services and interoperable production solutions within a collaborative data ecosystem. Factory鈥慩 is a lighthouse project funded by the German Federal Ministry for Economic Affairs and Energy as part of the Manufacturing鈥慩 initiative. Its objective is to establish a decentralized data space for the capital goods industry, enabling secure and interoperable data exchange across companies and industries for equipment manufacturers and operators alike.

The machine is integrated into 麻豆原创 system landscapes and operated live. It demonstrates how industrial data can be used in a sovereign, interoperable and cross鈥慶ompany manner not as a theoretical model, but in real production operations. This creates transparency regarding asset condition, utilization and performance while laying the foundation for new data鈥慸riven services.

Service as a Key to Resilience

The value of this approach becomes particularly clear in service operations. Where production, data and operations are tightly interconnected, service plays a decisive role in ensuring asset availability, productivity and stable customer relationships. One often underestimated lever is spare parts service: delays lead directly to downtime and economic losses, especially in volatile market and supply situations. At the same time, these processes remain heavily manual in many industrial companies.

麻豆原创 and Uhlmann are deliberately advancing the further development of this area. An AI鈥憇upported process assists throughout the entire workflow from handling incoming inquiries and clarifying missing information to identifying the correct spare part and generating quotations. The approach integrates into existing 麻豆原创 service and sales processes and is closely aligned with real鈥憌orld business operations. The objective is fast, reliable and scalable customer service.

鈥淭oday, industry is less concerned with cost optimization than with decision鈥憁aking under uncertainty,鈥� says Dominik Metzger, President and Chief Product Officer, 麻豆原创 Supply Chain Management, 麻豆原创 SE. 鈥淲ith 麻豆原创 Business AI and integrated production and service solutions, we move decision鈥憁aking directly into business processes. This allows companies to identify risks early, respond with greater flexibility and remain operational even under unstable conditions.鈥�

Rethinking Value Creation Together

The collaboration between 麻豆原创 and Uhlmann illustrates a fundamental shift in industry: resilience is not achieved through additional buffers, but through better, faster and more-connected decisions across the entire value chain. Companies that manage their production and service processes in a data鈥慸riven way can respond more flexibly to change and secure their competitiveness over the long term.

Beyond HANNOVER MESSE, 麻豆原创 and Uhlmann will continue their innovation partnership. Following the event, the PacXplorer will be operated at the S.Factory in 麻豆原创 Experience Center Walldorf, serving as a platform for customers, partners and co鈥慽nnovation to continuously advancing industrial transformation.

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Dana Roesiger, +49 6227 7 63900, dana.roesiger@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

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 2025 Annual Report on Form 20-F.
漏 2026 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.

Image copyright: 漏Uhlmann Group

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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%.

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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.

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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.

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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.

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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.

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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.

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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.

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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 .

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麻豆原创 Business AI for industries

Tender Analysis Agent
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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.

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

A great way to break through that roadblock is to listen to leaders who jumped in early to use AI to transform outcomes. , a managing director of Finance in the Global IT division at Accenture, is one of those people.

The professional solutions and services company employs nearly 780,000 employees across 52 countries, who work with 350 partners to serve over 9,000 clients. The idea of transformation at Accenture鈥檚 scale might be intimidating to some, but not Lambert. He鈥檚 leading an聽ongoing transformation聽of Accenture鈥檚 finance function, which he calls 鈥渢he heartbeat鈥� of the company.

The results he鈥檚 achieved鈥� including saving the finance team a combined 57,000 hours annually by having AI generate narrative summaries for reporting鈥攕hine a spotlight on what鈥檚 possible. And he鈥檚 just getting started.

I had a chance to speak with him about how he became a leader in AI-driven transformation, and what others can learn from his achievements. This is a lightly edited version of our conversation

Q: As you know, innovating with AI is about reshaping how a business delivers value. But not every business leader is leading the charge. Some are watching and waiting. Why did you roll up your sleeves and decide to be on the forefront?

A: Taking a leadership position on AI is important to keep moving forward and shaping new services and capabilities. For example, across a company our size, even though we鈥檙e hyper focused on emerging technologies, we can find small problems across our technology landscape. There are processes and data living in different places and silos develop over time. Most large companies have this challenge. But those are valuable processes, and the business data we have is especially valuable. AI opens up new opportunities to bridge those gaps and deliver more end-to-end outcomes, so that our finance function can meet the growing business expectations of our stakeholders.

For many companies, the key to getting impactful results from business AI is to start with one function that鈥檚 central to business performance. Why was finance the right place for you to begin, and what did you want to achieve?

I always say finance is the heartbeat of our organization. I heard one of our global IT leaders use that phrase, and while it was inspirational, it also made me think, 鈥淟et鈥檚 not accidentally cause a heart attack for the organization.鈥�

Jokes aside; he was right. Your transactional and operational data flows through finance, and management decisions sit on top of it. Starting there gave us the ability to make end-to-end impact across processes that touch procurement, liquidity, forecasting, receivables, and more. And 麻豆原创 gives us a digital core where all that transactional data is harmonized.

The bottom line is that finance is the natural starting point if you want to move from reactive reporting toward more proactive, AI-driven insights that you can use to help move the business forward. So, we set out to unify data and transform finance processes in a way that scales across the whole value chain.

Cash and liquidity are so important in the finance function, and to an entire company. But managing it requires bringing together data, forecasting, and decision-making across many teams. How did AI help?

If finance is the heartbeat of a company, cash and liquidity are the lifeblood of your systems. Here鈥檚 a great example: Accenture engages in a lot of acquisitions, and we run operational cash in 50-plus countries, so it鈥檚 easy for decisions to default to historical, manual reviews. That鈥檚 what was happening at Accenture before a forward-thinking leader stopped by and asked if we could apply machine learning to the problem. Great leaders often ask great questions, and that one really got us thinking.

[AI] freed up 20% of our idle cash, which we could then move into global operations to fund acquisitions and strategic growth.

Eli Lambert

We took inspiration from retail: how stores treat inventory based on discounts and sales. If you treat cash like stock, you can apply those same learning models to figure out how much you really need to hold onto at any point in time. That鈥檚 how we built what we call 鈥淚ntelligent Cash.鈥� It brings all the business data together into a single data mart, a repository for structured data for a specific department or line of business, and uses machine learning to generate recommendations that our teams can act on.

AI is so good at this, and here鈥檚 what鈥檚 incredible: It freed up 20% of our idle cash, which we could then move into global operations to fund acquisitions and strategic growth. Now what used to take months, or even more than a year to build, we can now do it in days or weeks because 麻豆原创鈥檚 data cloud brings [麻豆原创] Datasphere, Databricks, and our machine-learning workloads into one place. The result is faster decision-making, better visibility, and much more accurate forecasting.

I love hearing about how you were able to use gains, delivered through strategic AI innovation, and then channel those gains into a high-value activity for the organization.聽 I know you also worked on receivables, something that impacts cash flow and customer relationships. What pain points did you face, and how did automation and machine learning transform the process?

Receivables were highly manual compared to payables. Clearing was inconsistent, and reconciliation took a lot of time because payments often come incomplete or with partial data. Anyone who works in or near finance knows exactly what I鈥檓 talking about. So, we co-developed on the 麻豆原创 platform a machine-learning-based receivables solution. It more than doubled the automation rate for receivables processing and tripled automatic reconciliation, about a 300% improvement.

As part of that, we introduced high-confidence, one-click matching recommendations that reduce errors and cut down the manual work. We saw a seven percent uplift in auto-clearing with a cash application scheduler built on the 麻豆原创 platform that delivers matches about 77% faster. All of that adds up to a more efficient receivables process, improved cash-flow visibility, and better productivity for the team.

In a global organization like Accenture, reconciling financial data and surfacing meaningful insights can be a huge amount of work. You turned to generative AI to help, which is really smart. What led you to that approach, and how is it changing your team鈥檚 day-to-day experiences?

We were dealing with balance sheet reconciliations across 50-plus countries, and the process was decentralized. I know a lot of companies face this problem. So, first, we moved everything online. Then we brought in machine learning and generative AI to analyze cost categories, summarize data, and surface important shifts.

[Our] Intelligent Financial Advisor, built on the 麻豆原创 platform, can generate narrative commentaries that are so accurate that over 90% are simply approved with little or no revision. That鈥檚 saved about 57,000 hours globally. Our teams can focus on higher-value analysis instead of manual reconciliation.

Eli Lambert

We then deployed an Intelligent Financial Advisor built on the 麻豆原创 platform that can generate narrative commentaries that are so accurate that over 90% are simply approved with little or no revision. That鈥檚 saved about 57,000 hours globally, just in controllership work, and helped us move to a three-day global close instead of five. The insights come faster and clearer, and the teams can focus on higher-value analysis instead of manual reconciliation. It鈥檚 also helping create more consistent roll-ups across regions and letting us use our talent more strategically.

I鈥檓 hearing this theme of not only measurable business gains from outputs, but the ability to better allocate time from manual, rote tasks to ones that deliver far more value for the business. That also applies to planning and forecasting. How did you bring AI into that part of the finance function?

Our planning work had grown too complex. Remember, we鈥檙e a large-scale, multifaceted global business. So, we replaced old models with 麻豆原创 Analytics Cloud, which gives us multi-year planning models enhanced by AI.

We applied it first to merger and acquisition modeling, where accuracy really matters. It lets us model very complex data sets and helps our finance team collaborate more easily across the business. The results have been more accurate forecasts, reduced risk of errors, and much better collaboration between executives and practitioners. Early results were strong, and that encouraged us to expand AI use in planning more broadly.

What advice do you have for leaders who are not as far along in using AI to supercharge business results?

First, start with a high-impact function tied to real outcomes. Then focus early on data quality and harmonization; it鈥檚 the foundation for everything that comes after. Then get your cadence right and your team working together. Hone in on the use cases that really matter to you鈥攖he best vendors can help you identify those鈥攁nd make sure to get the help you need from those vendors and their partners.

Use AI to spur growth. At Accenture, we鈥檝e been able to use AI to save significant cash in one area, which we then invest in another, high-growth process鈥攁cquisitions in our case. That鈥檚 how you use AI to really rethink your business and move it to the next level.

Eli Lambert, on advice to other enterprises

As you go, take a crawl-walk-run approach: start slow then increase the pace of scale and adoption over time. Be sure to invest in change management and upskilling as you go to spur learning and adoption. And partner closely with technology providers and system integrators who鈥檝e been there before. That accelerates everything.

The final suggestion I have is to use AI to spur growth. At Accenture, we鈥檝e been able to use AI to save significant cash in one area, which we then invest in another, high-growth process鈥攁cquisitions in our case. That鈥檚 how you use AI to really rethink your business and move it to the next level. And that鈥檚 possible today in ways that were not, even five years ago. Seize that opportunity.

I couldn鈥檛 agree more with Lambert. AI really does provide an opportunity to re-imagine entire business processes for greater impact.

To keep exploring what鈥檚 possible, at Accenture. Then see more AI use cases in and across all your , including procurement, supply chain, manufacturing, and more.

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

ANYbotics, a Swiss robotics company, has stepped into this space with a vision to shape a safer future for industrial inspection, one where robots operate as autonomous members of the inspection team, running inspection operations integrated into plant maintenance workflows.聽

This vision is embodied in the company鈥檚 鈥淎NYmal鈥�: a four-legged inspection robot designed specifically for heavy industry.

Unlike general-purpose robotics platforms, ANYmal is engineered to operate in 鈥渂ig, dirty, dusty, and dangerous鈥� environments, says Nicole Zingg, director of Technology Partnerships at ANYbotics. Places where stairs, corrosion, heat, and unreliable connectivity are the norm, not the exception.

But hardware, Zingg says, is only one part of the puzzle that makes ANYmal indispensable to customers.

Inspection robotics is about data

鈥淲e build a hardware platform,鈥� Zingg explains, 鈥渂ut inspection robotics is really about data that is consistent and trustworthy.鈥�

ANYmal autonomously navigates industrial sites to collect data that goes beyond what a human can collect alone. Beyond just visual inspection, its sensors also collect multi-modal data, including thermal imaging, ultrasonic leak detection, gas concentration detection, acoustic anomaly detection, and more. The observations are fed into what ANYbotics calls 鈥渋nspection intelligence,鈥� which transforms the collected data into actionable operational insights. The result is higher uptime, longer asset lifecycles, and, most importantly, safer working conditions for humans.

ANYmal can make a huge impact on operations. One offshore wind customer, Zingg says, has used ANYmal to manage all inspections and has eliminated the need to send personnel to a remote platform for months. When human intervention was eventually required, ANYmal鈥檚 data from prior inspections made all the difference. The customer already knew exactly what was wrong, which expert to send, and what equipment to bring鈥攁voiding costly and risky trial-and-error site visits.

Yet for ANYbotics, delivering insights is not enough if those insights are not integrated in the software systems customers use.

鈥溌槎乖� is where ANYbotics needs to be native鈥�

Through extensive user research, ANYbotics discovered that many plant operators, maintenance managers, and field service teams already run their daily operations in 麻豆原创. Work orders, asset histories, performance trends, and decisions all flow through 麻豆原创 systems. 鈥淚f customers are using 麻豆原创, 麻豆原创 is where ANYbotics needs to be native,鈥� Zingg says.

Meanwhile, 麻豆原创鈥檚 Project Embodied AI was looking for robotics companies to partner with. The project focuses on extending the impact of 麻豆原创 Business AI into physical operations by enabling robots to autonomously perform complex tasks with an understanding of the broader business context.

It was clearly a perfect fit and has delivered advantages for both companies.

On the system side, a continuous, unbroken digital thread connects ANYbotics insights from industrial inspections to data in 麻豆原创 systems, helping inform key business and operational decisions across the organization.

For end users, embedding ANYmal directly into familiar 麻豆原创 workflows can also help ease adoption, since introducing robotics into already stretched industrial workforces can trigger anxiety. Concerns about job security, workflow disruption, and complexity are common, but embedding ANYmal directly into familiar 麻豆原创 workflows can help reduce that friction, Zingg explains.

Treating robots as part of the workforce

The first major integration point was聽. Rather than sending only human technicians, customers can now dispatch work orders directly to ANYmal as they would to any other field team member. The robot then autonomously executes inspection tasks, gathers data, and reports the results directly back into a company鈥檚 麻豆原创 system.

From there, the integration expanded into asset-related scenarios and is now moving toward broader enablement via 麻豆原创 Business Technology Platform (麻豆原创 BTP), with the goal of allowing robot-generated data to land wherever customers need it in their 麻豆原创 landscape.

The ambition is not to force humans to adapt to robots, but for robots to adapt to human workflows. 鈥淎NYmal has to put data in the 麻豆原创 system, just like human team members,鈥� Zingg notes. ANYmal becomes another worker in the same operational system of record.

Project Embodied AI in practice

This combination of ANYbotics robotic technology with 麻豆原创 bridges the gap between physical operations and enterprise applications and tangibly reflects the goal of Project Embodied AI.

On the 麻豆原创 side, AI agents operate on ANYmal鈥檚 robotic systems to execute physical tasks, such as safety inspections.

On the ANYbotics side, ANYmal is a physical object that moves through space, perceives its environment, and acts within real-world constraints. ANYmal uses 麻豆原创 historic and time-series data to inform decisions while at the same time remaining fully autonomous even in environments with no connectivity.

It鈥檚 important to note, Zingg stresses, that ANYbotics has control over ANYmal鈥檚 behavior and inspection execution, while 麻豆原创 has control over the business context such as work orders, asset data, or operational priorities. It is the 麻豆原创 business context that informs how ANYmal鈥檚 insights are consumed and acted upon while ANYbotics controls ANYmal鈥檚 physical interactions.

Scaling safely and responsibly

Today, more than 200 ANYmal robots are already in productive use worldwide, with inspection deployments in heavy-industry environments that would otherwise require constant human exposure.

Safety remains central to ANYbotics. Each deployment includes extensive testing and an on-site field engineer who helps ANYmal learn and validate its environment and trains customer teams on safe operational procedures. While ANYmal is built to work independently, humans remain firmly in the loop.

A glimpse into the future

As industries face labor shortages and aging workforces, undocumented expertise can all too often be lost. With autonomous inspection robots such as ANYmal, this knowledge is captured and turned into programs that can run day in and day out across multiple sites. The captured data flows into 麻豆原创 to become organizational intelligence that survives any workforce turnover.  

ANYbotics鈥� partnership with 麻豆原创 shows that this combination of robotics and enterprise software is moving swiftly from the experimental stage to real-world implementation.

In the future, industrial inspection will be powered by AI, not as disembodied dashboards or isolated machines, but as an integrated intelligent system where physical robots and digital workflows in 麻豆原创 systems operate as one.

In that future, robots like ANYmal are no longer novelties. They are coworkers, albeit mechanical four-legged ones, quietly extending human capability into places humans were never meant to go. These robots, together with 麻豆原创, are shaping for a future where dirty, dangerous, and dusty industrial inspections are being transformed into business insights.

Top image courtesy of ANYbotics

Once closed, the acquisition will strengthen 麻豆原创 Business Data Cloud (麻豆原创 BDC)鈥攊ntegral for 麻豆原创’s AI-First and Suite-First strategy鈥攁nd accelerate the evolution of 麻豆原创 BDC to a fully interoperable enterprise data platform for enterprise-wide agentic AI. It will provide customers with the tools they need to unify, cleanse and harmonize data across sources for superior enterprise-wide agentic AI.

“Reltio is a natural fit with 麻豆原创,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. 鈥淎cquiring them will further improve our position as a leading business AI provider, combining 麻豆原创 and non-麻豆原创 data to deliver data context that business AI requires. AI cannot reach its full potential when data is fragmented across business units, platforms and domains without connection or context.鈥�

By integrating Reltio after closing the acquisition, 麻豆原创 will make customers’ enterprise data fully AI-ready. Customers will be able to rely on trusted, high-quality data across 麻豆原创 and non-麻豆原创 sources that Joule and Joule Agents use to deliver faster time-to-value for business AI.

Reltio鈥檚 platform helps organizations manage and govern structured and unstructured enterprise data from start to finish. Its AI-based entity resolution identifies and merges related records from different formats and applications into one reliable 鈥済olden record鈥� system of context. Its cloud-native, AI-first design supports a single, consistent view of customers, products, suppliers, locations and employees across both 麻豆原创 and non-麻豆原创 applications. Customers running AI tasks will benefit from increased reliability and consistency of data, bundled in a single source of truth, improving business AI. With that, customers can trust that AI results are correct, and AI-interactions are resolved fast.

鈥淛oining forces with 麻豆原创 presents a tremendous opportunity for us to accelerate our mission,鈥� Reltio Founder and CEO Manish Sood said. 鈥淓nterprise AI needs trusted context that is open and interoperable across the heterogeneous IT landscapes our customers run. This combination accelerates our ability to deliver Reltio as the system of context across 麻豆原创 and non-麻豆原创 environments, while maintaining continuity for our customers and our partner ecosystem.鈥�

Reltio’s data cleansing, unification capabilities and agent-driven workflows will work alongside 麻豆原创 Business Suite applications to improve decisions, reduce integration complexity and deliver trusted, consistent data critical for successful business processes and AI use cases. Low latency delivery and support for the Model Context Protocol (MCP) enable real-time, multiagent workflows across 麻豆原创 and non-麻豆原创 environments, allowing AI agents, such as a procurement agent, to assess supplier risk and trigger actions almost instantly using trusted, real-time data. Reltio offers prebuilt, industry-specific 鈥渧elocity packs鈥� that include data models, rules, matching logic and integrations, and solutions tailored to sectors like life sciences, healthcare and financial services.

By integrating Reltio after closing the acquisition, 麻豆原创 intends to accelerate its customers’ ability to govern and expose master data as trusted and context-rich data products across multiple sources that serve both traditional analytics workloads and AI agents. Reltio will become a core capability within 麻豆原创 BDC, with a flexible commercial model where customers can purchase Reltio as a separate solution or with other 麻豆原创 products. The Reltio portfolio will also remain available as a standalone offering for the foreseeable future.

The transaction is expected to close in Q2 or Q3 of 2026, subject to customary closing conditions, including regulatory approvals.

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About Reltio

Reltio is a leader in data unification and management, delivering cloud-native, AI-native master data management (MDM) to help enterprises create trusted data and unlock context intelligence for analytics, automation, and agentic AI. Designed for complex, multi-vendor environments, Reltio helps organizations unify, cleanse, harmonize, govern, and activate core data from multiple sources in real time鈥攁cross 麻豆原创 and non-麻豆原创 systems. The Reltio Data Cloud uses advanced entity resolution, continuous data quality, and relationship intelligence within an intelligent data graph to connect data across systems and reveal the full context behind customers, products, suppliers, and other key business entities. This enables organizations to reduce data friction, improve operational execution, and accelerate time to trusted decisions. For more information, visit .

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鈥�.

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鈥淭here鈥檚 so much data; I would say in esports, too much data,鈥� said Thom Valks, partnerships manager at Team Liquid, referring to the 1 trillion points of data his company deals with. 鈥淗ow do you figure out what the right questions are to ask? And then how do you get quick answers to those questions? That was the main problem.鈥�

Founded more than two decades ago, Team Liquid has become a global powerhouse in professional gaming.

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鈥淲e鈥檙e the biggest esports organization in the world,鈥� Valks said. 鈥淕aming is a huge industry, a billion-dollar industry nowadays. And esports is at the tip of the pyramid. People come to watch with thousands in stadiums like normal sports. And we are the best team in the world at it.鈥�

Before partnering with 麻豆原创, Team Liquid relied on spreadsheets and manual analysis.

鈥淲e were doing everything in Excel and manually combing through the data, which turned out to be really not doable,鈥� Valks explained. In 2018, the team began working with 麻豆原创 Business Technology Platform (麻豆原创 BTP), connecting directly to game publishers鈥� APIs for League of Legends and Dota. This allowed analysts to build dashboards and streamline data processing.

The impact was immediate: 鈥淏efore we partnered with 麻豆原创, I think we had something like four or five analysts per game. If we can off source that to a tool and focus on really important data questions, that鈥檚 way more beneficial. And I would say the last year or so with AI, it鈥檚 really taken a next step.鈥�

Now, Team Liquid is taking its relationship with 麻豆原创 one step further by turning to Joule to sort through the data and make decisions even faster.

鈥淛oule has taken the data that we have in our database and you can now ask it: 鈥楩ind me the best hero to play against this team over the last six months.鈥� It will turn out an answer that actually makes sense. That’s revolutionary for us.鈥�

Looking ahead, Team Liquid hopes to expand access to Joule across the organization. 鈥淚f we can get Joule to everyone, it really innovates their gameplay,鈥� Valks said. 鈥淭hat鈥檚 something our competitors should be really afraid of.鈥�

Matt Dillman is a senior videographer at 麻豆原创.

Now, however, many economists and policymakers view AI as a potential catalyst for reversing that slowdown. AI鈥攅specially the rise of generative AI and AI agents鈥攊s widely expected to shape the next phase of productivity growth in advanced economies, including those in the U.S. and Europe.

The key question for business leaders is not whether AI will matter, but how large the productivity gains will be, how quickly they will materialize, and which region will benefit most.

Productivity growth

The (OECD) estimates that AI could raise annual labor productivity growth in advanced economies by roughly 0.4 to 1.3 percentage points, depending on adoption intensity and sector exposure. These gains would be meaningful because even an additional half percentage point of annual productivity growth compounds significantly over a decade.

However, the OECD and other economists stress that outcomes depend heavily on complementary investments in digital infrastructure, workforce training, and organizational change, rather than on technology alone.

Between 1995 and 2019, U.S. labor productivity grew at 2.1% annually compared to one percent in Europe. This disparity arose in part because companies in the U.S. invested more aggressively in information, communications, and technology while those in Europe were constrained more by regulatory and other factors.

Expectations for AI-driven productivity gains remain generally stronger in the U.S. than in Europe. suggests that widespread adoption of generative AI could raise U.S. labor productivity growth by around one to 1.5 percentage points per year.

Several structural factors support this view. The U.S. has a deep technology ecosystem, global leadership in AI research and venture capital, and a large, digitally intensive services sector, including finance, professional services, and IT, where generative AI tools can be rapidly deployed.

Agentic AI

In both Europe and the U.S., AI agents represent a particularly important development. Unlike earlier automation tools that handled isolated tasks, AI agents鈥攍ike Joule Agents from 麻豆原创鈥攁re designed to plan, reason, and execute multi-step workflows. For example, an agent might manage customer service tickets, draft responses, query databases, escalate issues, and update systems鈥攁ll with limited intervention.

In knowledge-based industries, this kind of workflow automation could significantly raise output per worker. But rather than replacing entire occupations, AI agents may reduce time spent on repetitive administrative and 鈥渓ong-tail鈥� tasks, enabling workers to focus on higher-value analysis, strategy, and interpersonal activities.

Despite stories about failed corporate AI projects, which can typically involve bolt-on or stand-alone AI pilots rather than a more integrated, holistic approach, recent evidence from the U.S. suggests that productivity gains are already emerging in some sectors. For example, financial institutions have reported significant efficiency improvements in back-office operations through AI deployment.

Similarly, experimental studies in professional services show that generative AI can increase output quality and speed, particularly for less experienced workers, effectively narrowing skill gaps within teams.

European outlook

The outlook for productivity gains in Europe from AI is more mixed. According to a recent the medium-term gain in productivity from the AI alone would vary considerably across countries, and for Europe as a whole would be rather modest: about 1.1 percent cumulatively over five years.

But with pro-growth reforms, the IMF suggests that much bigger gains are possible over the longer run. Like the OECD, the IMF emphasizes that regulatory frameworks, labor market structures, and the pace of technology diffusion will strongly influence outcomes.

Several structural differences shape Europe鈥檚 trajectory and the size of what has been called the 鈥淎I growth dividend.鈥� First, AI adoption among small and midsize enterprises (SMEs), which form a larger share of the European economy than in the U.S., tends to be slower. Second, Europe鈥檚 digital market remains more fragmented across national boundaries, languages, and regulatory systems, which can complicate scaling technology platforms. Third, the European Union has taken a more precautionary regulatory approach to AI governance. While this may reduce certain risks, it could also dampen short-term productivity gains if compliance burdens slow deployment.

Europe鈥檚 strengths

That said, Europe has strengths. It leads in advanced manufacturing and industrial engineering, sectors where AI-driven optimization, robotics, and predictive maintenance can raise capital productivity. In these areas, AI agents embedded in industrial systems could significantly enhance supply chain efficiency and reduce downtime.

In addition, as 麻豆原创 executives have pointed out, Europe has an enormous repository of structured business and manufacturing data, which is essential for reliable and effective AI systems as well as trust in AI Agents.

If AI adoption accelerates in manufacturing and energy systems and if European companies seize the opportunity to build advanced AI agents and apps using their business data, Europe could see much more robust medium-term productivity gains. As an example, 麻豆原创’s internal use of AI tools has already significantly improved its own developer productivity.

Labor flexibility

A critical factor in both the U.S. and Europe is labor market adjustment. Historically, the U.S. labor market has demonstrated greater flexibility, with higher rates of job switching and occupational mobility. This flexibility may facilitate faster reallocation of workers into AI-complementary roles, amplifying productivity gains, though this could be offset by more effective existing workforce retraining.

As the (BIS) has noted, AI鈥檚 productivity effects are unlikely to be automatic. Productivity gains from AI depend on complementary investments in skills, management practices, and digital infrastructure. The BIS warns that without these, AI tools may produce only marginal efficiency improvements.

The historical lesson from past general-purpose technologies, such as electricity and IT, is that productivity surges occur only after organizations redesign processes to exploit new capabilities and take a holistic rather than piecemeal approach toward implementation.

No AI bubble

While some investors have expressed concerns about an AI bubble, total AI spending in the U.S. is still below one percent of GDP. Joseph Briggs, senior global economist at Goldman Sachs, notes that this is well below historical infrastructure cycles. For comparison historical infrastructure investments such as IT spending, railroads and canals typically represented between two and five percent of GDP.

Like these previous investment waves AI, particularly agentic AI, is likely to generate significant productivity growth and a corresponding boost to GDP in those regions and sectors that seize the AI opportunity.

Over decades, our customers have built powerful digital foundations on 麻豆原创 to run end-to-end business processes across their enterprises鈥攐ften extending and customizing these systems to support their unique business needs. Now, many are entering the next phase of transformation: modernizing their 麻豆原创 landscapes to unlock the full potential of AI.

As companies move to cloud-based 麻豆原创 environments and clean-core architectures, they are preparing to embed intelligence directly into business processes. This enables new forms of automation, with AI agents that operate across enterprise systems and execute increasingly complex tasks.

Modernizing these systems while introducing AI at scale is a significant undertaking. It requires technologies that integrate with existing applications, operate reliably within mission-critical workflows, and meet the governance standards enterprises demand.

That鈥檚 why, over the past few years, we have partnered with to combine advanced AI technology with deep business context. Our goal is to help organizations accelerate modernization and apply AI across the applications and processes key to their success. This collaboration will be showcased at NVIDIA GTC.

Building the foundation for enterprise-grade AI

Through our collaboration with NVIDIA, we are accelerating the entire life cycle of enterprise AI鈥攆rom model development to high-performance runtime execution鈥攁nd powering AI scenarios across our portfolio. ,  which consists of open libraries such as and , helps accelerate large-scale model training across distributed RL environments. It enables teams to build and refine enterprise-grade AI models faster.

Models are hosted through  and , where our customers and partners leverage those best suited to their use cases. microservices optimize inference performance, and we have observed up to a 20% improvement compared to another popular open source serving engine. Enabled by NVIDIA GPUs and NVIDIA NIM, the increased performance allows organizations to combine advanced AI models with trusted 麻豆原创 business data and processes to ensure that AI operates within the workflows that drive business operations.

Modernizing the business logic that runs the enterprise

AI models trained on 麻豆原创 knowledge and accelerated using NVIDIA technologies are already helping customers tackle some of their most pressing modernization challenges. For example, evolving business logic embedded in the 麻豆原创 systems that run their operations.

For decades, organizations have extended 麻豆原创 applications with custom ABAP code that reflects how their businesses operate. That logic captures years of operational knowledge across finance, supply chain, service processes, and more. But modernizing these environments for the cloud and preparing them for the next generation of AI-driven innovation can be complex.

To help accelerate this journey, 麻豆原创 developed . a foundation model trained exclusively on real-world ABAP code and the business logic used across 麻豆原创 environments. The solution incorporates specialized models for code-related tasks, including StarCoder2 for code completion, and Codestral for deeper code understanding and explanations. These models are served through NVIDIA NIM microservices to deliver high-performance inference.

brings these capabilities into the developer experience, helping teams analyze existing ABAP code, understand how customizations interact with core business processes, and generate new code when needed. By making decades of embedded business logic easier to interpret and update, we help organizations accelerate modernization and preserves the knowledge that makes their operations unique.

Connecting AI to business operations

The collaboration between 麻豆原创 and NVIDIA also explores how AI can operate within enterprise workflows to help organizations apply intelligence across both physical operations and complex planning environments. One emerging area is embodied AI, in which intelligence extends beyond software systems into the physical world. By combining AI reasoning with sensors, robotics, and enterprise data, organizations can connect real-world observations directly with digital business processes.

For example, predictive maintenance alerts from can trigger robotic inspections that analyze equipment using thermal, visual, and acoustic signals. These signals are evaluated alongside asset histories and maintenance records to identify potential issues. then orchestrates follow-up actions through , prioritizing work orders and guiding technicians with the right operational context. By linking physical-world insights with enterprise workflows, organizations can turn physical-world signals into coordinated enterprise actions.

The same principle applies to complex planning environments. Supply chains today must manage a constantly shifting web of constraints, from supplier availability and transportation disruptions to evolving customer demands. With NVIDIA, we are exploring technologies, such as NVIDIA Metropolis and NVIDIA Cosmos, to bring the latest AI advancements into warehouse management, safety, and asset inspection.

Together, we are also bringing new capabilities to  that combine agent-based reasoning with the  GPU-accelerated optimization engine. This enables planners to simulate complex supply chain scenarios and evaluate alternatives with more speed and accuracy. By integrating advanced optimization with 麻豆原创鈥檚 supply chain planning capabilities, organizations can dynamically model constraints, adapt plans as conditions change, and make more confident decisions in increasingly complex environments.

Collaboration with large-scale 麻豆原创 customers helps identify real operational bottlenecks, paving the way for AI-driven solutions. . The Taiwan-based global electronics manufacturer and manufacturing solutions provider will work with 麻豆原创 to develop AI-powered innovations for manufacturing and supply chain operations.

By combining 麻豆原创鈥檚 enterprise applications and business context and Foxconn鈥檚 manufacturing expertise, organizations can enhance operational efficiency, increase resilience, and advance decision-making across complex production and supply networks.

Experience agentic AI at NVIDIA GTC

麻豆原创 is enabling Joule Agents across its application portfolio, helping organizations automate tasks and coordinate complex workflows within business processes. At NVIDIA GTC, visitors will see how these capabilities are extended using  on to build agents tailored to specific enterprise scenarios.

And because 麻豆原创鈥檚 AI architecture is model-agnostic, organizations can bring their own models into these workflows, in addition to those deployed through 麻豆原创 AI Core. The hands-on experience at NVIDIA GTC will demonstrate how organizations can build AI-driven workflows that operate directly within the enterprise systems that run their business.

It all happens at , taking place March 16-19, 2026. Join us to see how 麻豆原创 and NVIDIA are helping organizations modernize enterprise systems, accelerate AI adoption, and move toward the AI-native enterprise:

• Attend our session: on Tuesday, March 17, from 2:00-2:40 p.m.
• Visit the 麻豆原创 booth, #2001, to explore agentic AI in action, participate in hands-on vibe-coding with Joule Studio, and witness next-generation enterprise automation

.

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

This has led to a 鈥淭erminal Renaissance,鈥� a return to text-in, text-out interaction.

For many applications, text works, letting users express intent naturally with no onboarding. However, text struggles to convey structured data that is common in business, and without real-time updates, static text results lose relevance the moment they鈥檙e generated.

Structured data is easier to digest when users can filter, sort, and visualize it鈥攖hat is why graphical user interfaces (GUIs) excel at presenting structured data and guiding users through complex workflows. But GUIs are expensive to build and rigid, forcing generic, one-size-fits-all solutions that struggle to provide the fluid, tailored experiences users now demand.

Text is flexible but limited; GUIs are robust but rigid. Generative UI is the unmet need between them and the new frontier for business software.

From static dashboards to dynamic workspaces

Imagine a procurement manager investigating a supply chain disruption. Instead of navigating five different applications and manually cross-referencing data, she asks: 鈥淪how me the suppliers at risk in Southeast Asia and model alternative sourcing scenarios.鈥�

This request sets agents to work behind the scenes. They gather and analyze live data, simulate outcomes, and calculate the projected impact of every alternative. Execution agents are also pre-positioned and ready to act on command.

The user doesn鈥檛 have to deal with any of this complexity. For them, a dynamic interface materializes in seconds鈥攏ot a generic dashboard, but a purpose-built mission control center. Interactive maps highlight affected regions and supply chain graphs update in real time. As the user tweaks parameters, risk scores adjust instantly. Embedded controls stand ready to trigger purchase orders or notify suppliers, enabling the user to decide and execute. Collaboration is simplified; colleagues can join a living workspace: no briefing decks, no context-setting calls.

This is the future: a business suite where a user鈥檚 intent defines their interface and their decisions drive action. To get there, we are combining Joule and Joule Agents with our vision for generative UI. This is not just about on-demand dashboards; it鈥檚 about steering a business with interfaces that adapt to each user’s role, context, and tasks. This is 鈥渧ibe coding鈥� for enterprise operations: shifting focus from syntax to intent.

We are entering an era where AI constructs UIs on the fly, allowing users to engage with them immediately. Generative UI marks the transition from static software suites to 鈥渂atch size 1鈥� applications that act like ephemeral control centers tailored to a specific problem.

Challenges and 麻豆原创鈥檚 answers

Delivering an intent-driven business suite at enterprise scale requires addressing complex realities. We are building generative UI because we understand its promise and its perils鈥攁nd we have unique assets to bridge that gap.

Accuracy

Large language models (LLMs) can produce plausible but incorrect outputs, or 鈥渉allucinate.鈥� A consumer chatbot that hallucinates a movie plot is tolerable; a procurement system that misrepresents supplier terms has real consequences. Our generative UI approach addresses this by visualizing data directly from systems of record with transparent lineage. Grounding the UI in real-time, trusted data is our first defense against inaccuracy.

Trust

If every interface is generated on the fly, how do users know it is reliable? Trust is built on consistency and predictability. Our generative UI is built on the familiar and proven architectural grammar of 麻豆原创 Fiori for lists, dashboards, and workflows. The content is bespoke and the structure is consistent and familiar, so users can always judge and adjust with confidence.

Complexity

Enterprise systems are sophisticated and unique. They are built over decades, encoding massive domain knowledge and business logic. Generative UI builds on Joule鈥檚 existing integration and orchestration capabilities, which already connect to systems across a landscape and coordinate agents to execute complex workflows. Generative UI leverages this foundation, letting users interact with deeply integrated processes through simple interfaces while Joule handles the orchestration underneath.

Why this matters now

The expectations set by consumer AI are real, and the gap between what employees experience at home and what they use at work is widening.

The future of enterprise software isn’t chatbots bolted onto legacy screens. It’s bespoke mission control鈥攊nterfaces that materialize around a user鈥檚 intent, grounded in live data, executed by agents, and governed by the user.

With that, we鈥檙e reimagining how work gets done.

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

Headquartered in Nuuk and 100% owned by the Government of Greenland, Royal Greenland is modernizing its 麻豆原创 platform and moving from on premise to cloud ERP in order to future鈥憄roof core processes and unlock embedded AI across its 麻豆原创 business applications.

鈥淲e are moving from our existing setup to 麻豆原创 Cloud ERP and 麻豆原创 Business Data Cloud because we want access to the capabilities you can consume on a cloud platform,鈥� said Lars Bo Hassinggaard, CIO at Royal Greenland for more than 25 years.

The company brings high鈥憅uality wild鈥慶aught fish and shellfish from the North Atlantic and Arctic Ocean to consumers worldwide. It has been running 麻豆原创 since 1998 but is now embarking on its most significant transition to date: migrating 麻豆原创 ERP Central Component to 麻豆原创 Cloud ERP while simultaneously elevating its business intelligence (BI) landscape into 麻豆原创 Business Data Cloud and later transforming BI into 麻豆原创 Datasphere.

The project follows the structured RISE with 麻豆原创 framework, which consolidates platform transformation, operations, and the innovation cycle into one contract.

Lean, selective data transition: 90% fewer data to move

As part of the migration, Royal Greenland is reducing its data volume significantly using the 鈥淟ean Selective Data Transition鈥� method.

鈥淲e are keeping 10 years of data and cleaning up, so we avoid outdated company codes and historical data that no longer create value,鈥� Hassinggaard explained. 鈥淲e鈥檝e achieved a 90% reduction in what needs to be stored and migrated. The method combines data analysis, scoping, and standardized mapping objects in a guided process, ensuring that Royal Greenland only carries forward what is truly necessary, making the financials of the transformation more predictable and avoiding unnecessary complexity.鈥�

Technology first, innovation next

Go鈥憀ive is planned for March 1, 2027. The year 2026 is dedicated to the platform lift itself. From 2027, Royal Greenland will begin building business鈥慸riven improvements on top of the standardized core鈥攆or example, new user interfaces and process optimization using small AI agents within finance and administration.

鈥淩oyal Greenland and 麻豆原创 have worked together since 1998, and we look forward to getting started on the technical part of the platform uplift this January,鈥� Hassinggaard shared. 鈥淲e鈥檙e keeping the transformation as simple as possible for now and will use 2027 to activate the benefits, such as improved data analysis, better user experience, and more efficient work processes.鈥�

Royal Greenland is following a classic waterfall approach and has already established a 鈥済olden shell鈥� as the basis for further configuration and retrofitting.

麻豆原创 is responsible for implementing the cloud solution, which will run on Microsoft Azure, initially in Sweden, with the option to move later to a Danish data center. External advisor Spektra Analytics has supported contract validation.

From in鈥慼ouse experiments to standardized, 鈥渃onsumed鈥� AI

Although Royal Greenland has already successfully experimented with its own AI solutions, including vision鈥慴ased projects in production, the strategic direction ahead is to leverage embedded, standardized AI data products from 麻豆原创 and models built on the 麻豆原创 Business Data Cloud and its semantic data layer.

鈥淲e are a company that prefers to tap into existing AI solutions rather than invent them ourselves,鈥� Hassinggaard said. 鈥淚t鈥檚 far more efficient for us. There is no reason for us to spend resources reinventing what 麻豆原创 already provides. The initial focus will be on process optimization within administrative functions such as finance鈥攕mall AI agents that can streamline daily work.鈥�

Advice to others: Allocate more time, and understand your method

Hassinggaard is clear that the RISE with 麻豆原创 contract, methodology, and preparation work require time and organizational maturity. His advice to other companies facing a similar cloud ERP decision: 鈥淒o it thoroughly鈥攁nd allocate more time than you think. Study the methodology, pricing, and contracts. And bring a competent advisor on board.鈥�

Ellen Vig Nelausen is an integrated communications expert for 麻豆原创 Regional Communications.

Together, the companies plan to create the digital backbone for a sovereign, interoperable and AI-supported healthcare system. The solutions will combine the expertise of Fresenius, one of the world鈥檚 largest healthcare companies, with future-oriented 麻豆原创 technologies and meet high requirements for data sovereignty, security and regulatory compliance. The plan is to provide an open, integrated and data鈥慸riven digital health ecosystem that enables hospitals and medical facilities worldwide to use AI securely and to handle health data responsibly.

Digital sovereignty for healthcare

麻豆原创 and Fresenius plan to jointly build an individual, scalable healthcare platform that enables connected, data-driven healthcare processes. Based on this, the companies will develop joint, future-oriented and AI-supported healthcare solutions to sustainably increase quality, transparency and efficiency across the entire care chain and set new standards for digital innovation in the healthcare sector. The foundation will be proven 麻豆原创 technologies and products such as 麻豆原创 Business Suite, 麻豆原创 Business Data Cloud (麻豆原创 BDC), 麻豆原创 Business Technology Platform (麻豆原创 BTP) and 麻豆原创 Business AI. These core elements help create a unified, compliant, open and expandable base for the more-secure exchange and use of data as well as for operating AI models in a controlled environment.

Together, the companies also plan to build a sovereign, European solution for an integrated healthcare ecosystem that supports the integration of modern hospital information systems (HIS) based on 麻豆原创鈥檚 鈥淎nyEMR鈥� strategy. Interfaces based on open industry standards such as HL7 FHIR will enable the more-seamless connection of HIS, electronic medical records (EMRs) and other medical applications.

鈥淲ith 麻豆原创鈥檚 leading technology and Fresenius鈥� deep healthcare expertise, we aim to create a sovereign, interoperable healthcare platform for Fresenius worldwide. Together, we want to set new standards for data sovereignty, security and innovation in healthcare. Thanks to 麻豆原创, Fresenius can harness the full potential of digital and AI-supported processes and sustainably improve patient care,鈥� says Christian Klein, CEO and Member of the Executive Board of 麻豆原创 SE.

鈥淭ogether with 麻豆原创, we can accelerate the digital transformation of the German and European healthcare systems and enable a sovereign European solution that is so important in today鈥檚 global landscape. We are making data and AI everyday companions that are secure, simple and scalable for doctors and hospital teams. This creates more room for what truly matters: caring for patients,鈥� adds Michael Sen, CEO of Fresenius.

As part of the joint transformation project, both companies plan to invest a mid three-digit million euro amount in the medium term to consistently drive the digital transformation of the German and European healthcare system through the use of digital and AI-supported solutions.

The partnership is implemented through various forms of collaboration. These include joint investments in startups and scaleups, joint technological developments and close cooperation within coordinated governance structures between the two companies.

Visit the . Get 麻豆原创 news via  and .

Media contact:
Dana Roesiger, +49 62277 7 63900, dana.roesiger@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

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.聽 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 2026 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.

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.

Its advanced refrigeration, air conditioning, and heat pump technologies keep supermarket shelves, hotel rooms, and hospital operating theaters at the right temperatures, whatever the ambient temperature is. Its compressors are essential for storing medicines, preserving perishable goods in shipping containers, and processing frozen foods. And if that isn鈥檛 impressive enough, its technology keeps ice hockey players gliding across the ice and breweries fermenting yeast for your beer.

The company is a longstanding RISE with 麻豆原创 customer and, like 麻豆原创, is constantly innovating its products to stay ahead. Christian Stenzel, vice president of Organization and IT at BITZER, has a clear vision for an 麻豆原创 strategy that prioritizes integration and rapid adoption of AI: 鈥淥ptimizing business processes is as important as product innovation at BITZER.鈥�

The 麻豆原创 Research and Innovation team is equally committed to keeping 麻豆原创 ahead by exploring new technologies and one team is currently dedicated to Project Embodied AI. Embodied AI combines artificial intelligence with a physical form, such as robots, that can perceive and act in the real world. Embodied AI agents take this a step further: extending the impact of into physical operations by making robots cognitive.

To explore potential use cases where cognitive robots could bring value, the Project Embodied AI team invited a select group of forward-thinking leaders and innovation professionals from 麻豆原创 customers to join its Physical AI and Cognitive Robots Exploration Council. And BITZER was one of them.

鈥淒emand-driven production is key in our business,鈥� said BITZER’s Stenzel, who immediately saw the potential value in using robots to meet demand fluctuations.

Running on (麻豆原创 BTP) and , already in place, BITZER already had the ideal software landscape to serve as a proof-of-concept test ground.

Before deployment, NEURA鈥檚 , one of Europe鈥檚 most advanced humanoid robots, was virtually trained for the pick-task use case on NVIDIA Isaac Sim software.

A new benchmark for intelligent automation

This proof of concept for Project Embodied AI sets a new benchmark for intelligent automation in warehouses, Stenzel said. The results highlight:

• Seamless integration: 麻豆原创 EWM connected directly with physical warehouse operations, no costly middleware required.
• True autonomy: Robots performed pick-tasks independently, demonstrating advanced task-level autonomy.
• Agility and flexibility: Robots could enable demand-driven production, operating 24/7 to meet shifting needs.
• Reliable processes: Orders of materials were automatically created, demonstrating how operational mistakes could be minimized.

A decisive step forward

Dr. Lukasz Ostrowski, head of Embodied AI and Robotics at 麻豆原创, heralded this proof-of-concept as a decisive step forward: 鈥淭he proof of concept at BITZER is great first step for experiencing firsthand how the impact of 麻豆原创 Business AI can be extended into physical operations. Further proofs of concept are planned as Project Embodied AI continues to assess the business value of embodied AI for customers.鈥�

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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.聽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.聽

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?聽

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.

This is where 麻豆原创 and the 麻豆原创 partner ecosystem make a decisive difference.

Together, we help customers translate AI strategies into meaningful outcomes by pairing partner industry expertise with聽麻豆原创 Business AI, which brings hundreds of purpose-built, domain-rich capabilities embedded across 麻豆原创 applications. These capabilities help automate processes, elevate decision-making, and enhance employee productivity across the enterprise.

麻豆原创 Business Technology Platform (麻豆原创 BTP) amplifies this foundation by giving customers the ability to integrate, extend, and build AI-powered solutions in a scalable and secure environment.

Across industries, 麻豆原创 and our partners are helping customers unlock real value from AI. The examples below show how organizations are already achieving tangible impact today.

Driving efficiency with AI-powered process automation

Manual, repetitive processes remain one of the biggest barriers to operational excellence. The 麻豆原创 partner ecosystem plays a critical role in helping customers uncover these inefficiencies and redesign them with AI-driven automation.

For frozen-food manufacturer聽FRoSTA, 麻豆原创 partners聽sovanta AG,聽and聽Amista聽identified invoice processing as a major bottleneck. By orchestrating the workflow using聽麻豆原创 Build Process Automation聽and extracting, interpreting, and validating data through聽麻豆原创 Document AI, the partners were able to . Invoices that once required several minutes of manual effort now flow through the system in under a minute, with roughly 60 percent fully automated. Employees can redirect their attention to higher-value work, such as resolving exceptions and collaborating with suppliers.

This is the power of pairing partner expertise with 麻豆原创 Business AI and 麻豆原创 BTP solutions: Organizations quickly shift from isolated task automation to connected, intelligent workflows that scale across departments and regions. What begins as a single use case becomes the foundation for a broader automation strategy鈥攁ccelerating processes, reducing manual effort, and tightening the connection between data, people, and decisions.

Accelerating innovation by making AI accessible to every team

As demand for AI grows, many organizations face a familiar hurdle: the scarcity of specialized AI talent. Partners in the 麻豆原创 ecosystem help close this gap by combining their industry knowledge with tools in 麻豆原创 Business AI and 麻豆原创 BTP that make it easier for teams across the business to experiment, prototype, and deploy AI solutions at speed.

A strong example comes from Aspen Pumps, which partnered with NTT DATA聽to . Using low-code capabilities from聽麻豆原创 Build to design and orchestrate workflows and 麻豆原创 AI Core to power AI models, the team rapidly developed a series of automation bots鈥�12 in total. These now streamline activities such as invoice validation, order routing, and even interpreting CAD drawings to accelerate quote creation. Many proof-of-concept initiatives were completed in under a week, demonstrating how accessible innovation becomes when intelligent capabilities are built directly into the tools teams already use.

By lowering the barriers to experimentation, 麻豆原创 and partners help organizations innovate faster and more confidently. Teams can explore new ideas, test them safely, and scale what works鈥攚ithout waiting for scarce technical resources or lengthy development cycles. Innovation becomes a daily practice, not a specialized activity reserved for a few.

Building a future-ready foundation with scalable, extensible architecture

As AI becomes more deeply integrated into business operations, leaders are prioritizing platforms that will scale with them, not constrain them. This is where 麻豆原创 partners help customers design architectures that can evolve with changing market needs while preserving the stability of their core systems.

Steel manufacturer聽Al Ghurair Iron and Steel (AGIS)聽offers a powerful example. Working with聽Deloitte, the company using 麻豆原创 Business AI embedded in 麻豆原创 S/4HANA Cloud, private edition, combined with the integration and extension capabilities of 麻豆原创 BTP. A planning cycle that once required 15 minutes of manual coordination now takes less than five. The solution has been replicated across multiple locations, and more than 400 calculations are now automated, giving teams more time to analyze results and optimize operations rather than manage spreadsheets.

When 麻豆原创 Business AI and 麻豆原创 BTP come together with partner expertise, companies gain a foundation they can rely on as their AI ambitions grow. They can scale new capabilities across plants, regions, or business units; extend processes without disrupting mission-critical systems; and seamlessly connect 麻豆原创 and non-麻豆原创 environments into a cohesive, intelligent landscape.

Turning AI potential into business transformation

These stories demonstrate what becomes possible when customers, 麻豆原创, and our partners work together: faster processing, smarter decisions, empowered employees, and architectures built for long-term agility and growth.

With the combined strength of the 麻豆原创 partner ecosystem, the domain-rich intelligence of 麻豆原创 Business AI, and the extensibility of 麻豆原创 BTP, organizations can move beyond pilots and embed AI where it matters most: in the daily processes and decisions that run their businesses.

Learn more about what’s possible for your business with 麻豆原创 Business AI at .

From decades of customer support defined by reaction to calls, tickets, or queues, to the evolution of proactive support with pre-AI digital platforms, to the current AI-powered ecosystem that is redefining how support teams strategize, operate, and deliver resolutions. AI-enabled support anticipates needs, predicts failures, and delivers instant, seamless resolutions at scale.

And most importantly, this shift is as transformational as it is technological.

Keeping pace with transformation

As customers navigate complex and ambitious transformation projects, whether it鈥檚 moving to the cloud, scaling AI, or modernizing complex operations, there is always a quiet mandate: systems supporting critical business processes must run smoothly because the costs of downtimes have never been higher.

For businesses, uninterrupted operations are non-negotiable. 麻豆原创鈥檚 AI-driven support can anticipate issues before they arise, helping to ensure critical processes run smoothly, even during high-volume peak events. 麻豆原创 uses 麻豆原创 Business AI to help prevent issues proactively, working to ensure a smooth experience by avoiding system outages, platform scalability issues, data overloads, or service overloads. During the peak sales event of Cyber Week 2024, 麻豆原创 achieved 100% uptime for 麻豆原创 Commerce Cloud customers. As the Cyber Week 2025 numbers come in, we already have delivered 100% uptime and improved GMV for global sales events like Singles Day (GMV reached 鈧�7,108.72M, or +180.2% YoY, with 6,315.99K orders, or +46.4% YoY) and El Buen Fin (GMV hit 鈧�12,341.70M, or +13.18% YoY, and 10,385.74K orders, or +32.24% YoY).

Scaling self-service with AI

Structured knowledge and curated content enable 麻豆原创 to build AI and AI agents with high confidence levels. Today, over 82% of customer issues are addressed via self-service. This allows users to get instant resolution to issues or bridge knowledge gaps they face during the use, implementation, and continuous improvement of 麻豆原创’s solutions.

AI in instant response and resolution

When it comes to delivering instant response and resolution in customer support, the impact of AI-integrated services is remarkable. When 麻豆原创鈥檚 Auto Response Agent is highly confident of the solution, based on the underlying data and knowledge, it can deliver highly relevant solutions that can save customers significant time and effort. Additionally, the first contact resolution rate for cases answered automatically by the agent is at par with what human-human support interactions achieve.

Supporting 麻豆原创 Business AI

麻豆原创 Business AI supportability is all about making AI real for customers through the right systems that drive successful adoption. As 麻豆原创 delivers AI capabilities across its portfolio, we enable customers to have the right support when they encounter issues in early deployment.

As customers scale AI across their organizations, we have concrete processes and tools to help support them, so they can deploy new AI with the utmost confidence. For example, the Incident Solution Matching service is integrated with 麻豆原创 Joule for Consultants, allowing efficient support information retrieval and helping to eliminate the hassle of searching through vast amounts of 麻豆原创 documentation.

Empowering support engineers with AI

AI is not just transforming customer outcomes, it鈥檚 also transforming how our engineers and experts deliver precision and speed, freeing them from logistical tasks so they can focus on support requests that need specialized attention. Thanks to 麻豆原创鈥檚 AI-integrated self-service offerings, we鈥檙e able to instantly resolve customer issues four out of the five times they come to us.

AI-powered solution recommendations in self-service can eliminate the need for at least 10% of the cases being created. This is a big win for human-generated knowledge being delivered by AI-generated tools. Every third case gets submitted with an AI-recommended product component for optimal routing and faster processing.

In 麻豆原创鈥檚 multi-location, multilingual, global setup, standardized communication is key. Around 10% of responses by support engineers take advantage of 麻豆原创鈥檚 AI-assisted language optimization services.

There鈥檚 more. We have agentic case resolution, AI-assisted creation of 麻豆原创 Knowledge Base Articles, and automatic error categorization, covering use cases that help our engineers deliver their best work with greater accuracy and higher quality.

And, of course, 麻豆原创 runs its own products and solutions, serving as a first reference for our customers. As Dr. Benjamin Blau, 麻豆原创鈥檚 Chief Process and Information Officer, puts it: 鈥淭his is ‘麻豆原创 runs 麻豆原创’ in action. As customer zero, we validate every AI innovation in real-world complexity before it reaches you. We鈥檝e architected this multi-agent AI on our own 麻豆原创 Business Technology Platform, including the 麻豆原创 AI Core foundation, and our service and support data lake. Agentic case resolution is a blueprint for enterprise-grade, responsible AI, proving the power and maturity of the 麻豆原创 Business AI portfolio, empowering customers with faster resolutions for an elevated experience.鈥�

Will AI replace support teams?

Short answer: No.

To elaborate, let鈥檚 take the example of an AI agent that automatically responds to customers. 麻豆原创鈥檚 instant response and resolution are only activated when the system is very confident with its response. Our commitment to the relevant, reliable, and responsible use of AI helps ensure that there鈥檚 no experimentation with customer cases that deserve hands-on attention from engineers and experts. The legacy of trust that 麻豆原创 has earned over 50 years of industry leadership, which is also trusted by 90% of Fortune 500 companies, drives this rigor applied to AI.

What does this mean for our engineers? Any move to augment our work with AI is not about replacing people. It鈥檚 about freeing time, energy, and creative space to focus on high-impact tasks that need critical thinking and human insight. AI amplifies human expertise. Customers benefit from this blend of machine intelligence and human insight, ensuring every solution is relevant and responsible.

It鈥檚 also important to highlight that 麻豆原创 is a growth company. The use of technology helps us deliver what customers expect from support teams and build ongoing knowledge that feeds AI systems for intelligent decision-making, also meeting the future demands of AI-augmented support.

Yes, the world is witnessing role reductions across the industry with the adoption of AI in business workflows, but we also see the emergence of critical new roles that help us navigate the current reality. How many of us had heard of AI trainers or carbon accountants 15 years ago?

These are exciting times for innovation. 麻豆原创鈥檚 partnerships, such as our collaboration with Databricks and Snowflake, empower developers to turn business data and AI into real business outcomes.

We鈥檙e truly at the crossroads of innovation and transformative tools that can turn imagination into impact. 麻豆原创鈥榮 Chief Technology Officer, Philipp Herzig, summarizes it perfectly: 鈥淎I is transforming business at every level, but it鈥檚 people who turn transformation into progress. With 麻豆原创 Business AI, we鈥檙e combining the best of human ingenuity and machine intelligence to deliver impact that matters.鈥�

Stefan Steinle is executive vice president and head of Customer Support & Cloud Lifecycle Management at 麻豆原创.

The system was developed by 麻豆原创 Japan and INSPIRATION PLUS, a venture from Oita University focused on disaster prevention.

EDiSON, which runs on 麻豆原创 Business Technology Platform, exemplifies how intelligent enterprise technology can be harnessed to address global challenges such as cyclones (typhoons) and floods. It integrates diverse types of information, including real-time, visual meteorological data and historical data records, to drive predictive insights and smarter operations assisted by 麻豆原创 Business AI and machine learning.

These predictions offer authorities a vital tool for delivering faster response times and mitigating damage in the event of a natural disaster. This includes forecasting terrain damage, dispatching emergency services to affected areas and supporting decision-making in issuing evacuation advisories. The Solomon Islands initiative is envisioned as a blueprint for other small island developing states, showcasing how cutting-edge technology can democratize disaster resilience.

鈥淓DiSON represents a leap forward in how science and technology can empower vulnerable communities,鈥� UNESCO Chief of Disaster Risk Reduction Soichiro Yasukawa said. 鈥淏y integrating AI and real-time data, we are not only improving early warning capabilities but also building a foundation for long-term resilience and sustainable development.鈥�

The project, part of UNESCO鈥檚 Disaster Prevention Strengthening Program, will be operational in 2026. It aims to establish a scalable, data-driven model for disaster preparedness and responses of small island nations that face the increasing severity of natural disasters driven by climate change. The Solomon Islands, located in the South Pacific Ocean, face frequent threats from earthquakes, tsunamis, cyclones, droughts and flooding. EDiSON will serve as a transformative solution to enhance national preparedness and response capabilities.

EDiSON integrates static and real-time dynamic data from government, municipal and private sector sources. The system delivers predictive insights and real-time visibility into emerging disaster risks. This empowers authorities to issue timely evacuation orders and make informed decisions that protect lives and infrastructure.

Why EDiSON? Proven Performance and Scalable Sustainability

鈥淭his project exemplifies 麻豆原创鈥檚 commitment to using technology to empower resilient communities,鈥� said Sophia Mendelsohn, chief sustainability and commercial officer at 麻豆原创 SE. 鈥淓DiSON is a powerful example of how our cloud platform and AI capabilities can be tailored to meet the needs of communities facing real-world challenges. We鈥檙e proud to support UNESCO in bringing this innovation to the Solomon Islands and beyond.鈥�

UNESCO鈥檚 selection of EDiSON was driven by the system鈥檚 proven track record in Japan鈥攁 country renowned for its advanced disaster management systems. The system鈥檚 ability to overcome traditional barriers such as fragmented data, limited analytical capacity and underutilization in field operations makes it especially valuable for resource-constrained nations such as the Solomon Islands. EDiSON鈥檚 modular design helps ensure scalability and adaptability, enabling governments to deploy sophisticated disaster management tools without requiring extensive budgets or technical expertise.

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Lesa Plingen, +49 622 776 9000, lesa.plingen@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

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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This month at , we announced a wave of 麻豆原创 Business AI innovations all built on the same technology foundation that powers our that we are now delivering to our customers and partners, allowing them to add even more value in the future.

We showed how the future of enterprise software is built on an AI-native architecture, powered by 麻豆原创 app, data, and AI foundation. With this approach, we are enabling a platform shift across the tech stack in a non-disruptive fashion, empowering developers to work faster and smarter using the frameworks and tools of their choice.

麻豆原创 HANA Cloud and 麻豆原创 Business Data Cloud: powering our AI-native future

麻豆原创 HANA Cloud is the database for 麻豆原创鈥檚 AI-native software architecture and the foundation of our broader data fabric strategy. At 麻豆原创 TechEd, we announced new AI capabilities for 麻豆原创 HANA Cloud that spur AI innovation.  

For example, Model Context Protocol (MCP) support for 麻豆原创 HANA Cloud is now generally available. This provides direct access to rich multi-model engines. Agents can be grounded in full enterprise data context: navigating relationships across customers and suppliers, understanding geographic dependencies through spatial data, and performing semantic searches through vector embeddings — all within a single in-memory engine.  

We鈥檙e also expanding 麻豆原创 HANA Cloud knowledge graph engine capabilities (Q1 2026) so customers can automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. What used to take weeks of manual modeling can now happen automatically in minutes. But that鈥檚 not all. We鈥檙e also enabling agentic memory in 麻豆原创 HANA Cloud. With long-term memory, AI agents can memorize past inputs and decisions — learning and remembering just like humans — and become continuously smarter.

These advances show that 麻豆原创 HANA Cloud is truly powering an AI-native future. .

Bringing together the power of 麻豆原创 BDC and Snowflake

We are bringing the power of Snowflake together with 麻豆原创 Business Data Cloud (麻豆原创 BDC), calling it 麻豆原创 Snowflake. This partnership enables zero copy data sharing with Snowflake via 麻豆原创 BDC Connect.

Enterprises already using Snowflake today can leverage 麻豆原创 BDC Connect to integrate their existing instances of Snowflake with 麻豆原创 BDC, giving them seamless, real-time access to combined, semantically rich 麻豆原创 with 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 in H1 2026. Find more information here.

麻豆原创-RPT-1: a new category of AI models

One of our most exciting announcements at 麻豆原创 TechEd was the launch of our first enterprise relational foundation model 麻豆原创-RPT-1, pronounced: 鈥渞apid one.鈥�

Businesses run on structured data. But large language models (LLMs) struggle with a general understanding of table structures and associated semantics. This requires the use of machine learning, or 鈥渘arrow AI,鈥� for tasks like classification, regression, and more. But classical machine learning necessitates training a model on each task, which easily can lead to hundreds of separate models.

麻豆原创-RPT-1 puts them all into one single, pre-trained model that understands relational business data and predicts business outcomes. Unlike language, image, or video models, 麻豆原创-RPT-1 accurately predicts business based on tabular data such as payment delays, supplier risks, upsell opportunities, customer churn risk, and more.

We believe that 麻豆原创-RPT-1 is a super capable foundation model today. It provides up to 2x better prediction quality compared to narrow models and 3.5x better prediction quality as compared to LLMs. .

麻豆原创-RPT-1 comes in three versions. 麻豆原创-RPT-1-small is for super-fast predictions and 麻豆原创-RPT-1-large is for highest accuracy. Both will be generally available in Q4 2025 in the generative AI hub in AI Foundation. 麻豆原创-RPT-1-OSS is the open-source version, available in Hugging Face and GitHub.

You can test 麻豆原创-RPT-1 today with your data or our use case data samples via no-code UI or via API in the new 麻豆原创-RPT-1 playground, an intuitive and interactive space to test for free and open to everyone and .

We are continuously adding new capabilities to AI Foundation and models to the generative AI hub, empowering developers to experiment with orchestration tools and leading models to scale AI development and productization across 麻豆原创 and non-麻豆原创 environments. For example, Perplexity is now generally available in the generative AI hub, so users can correlate business data with external data from the internet. Evaluation Services and Prompt Optimizer, in close collaboration with NotDiamond, are now also generally available in AI Foundation, freeing up users to adopt the most appropriate model for their use cases without the need for rewriting prompts. .

Digital sovereignty made in Germany, for Europe

Digital sovereignty is becoming increasingly important, reflecting the need for regional AI services that align with local regulations, standards, and values. As an example, Europe will benefit from its own strong, trustworthy infrastructure to support innovation, data protection, and ethical AI.

AI Foundation, including various models and all the services we offer, is already available on our own cloud infrastructure. As a next step, we are expanding our 麻豆原创 Cloud Infrastructure offering in our 麻豆原创 data center in Walldorf, Germany, to Deutsche Telekom through the Industrial AI Cloud project, providing secure, high-performance infrastructure for AI innovations across public institutions, defense, and society. 麻豆原创 delivers 麻豆原创 Cloud Infrastructure, 麻豆原创 Business Technology Platform, and applications 鈥� including our AI Foundation with frontier AI from Mistral, Cohere, and others 鈥� on Telekom鈥檚 Munich data center. Both companies uphold the highest standards of data protection, security, and reliability.

This marks a milestone as more European companies join the Industrial AI Cloud project, advancing applied AI across Europe with trusted, business-embedded solutions that unlock the full potential of industry data. See the announcement here.

Enabling customers to build, extend, share, and orchestrate AI agents

To help manage Joule Agents and Joule skills, we have introduced the concept of AI Assistants 鈥� role-based AI teammates, accessed through Joule 鈥� like a financial assistant that brings together agents for cash collection, treasury, and more. We will provide AI Assistants in Joule for every core business role, offering our users an agentic experience like never before.

Out-of-the-box Joule Agents are powerful, but we know that every company has unique requirements. We believe AI should adapt to users鈥� systems, not the other way around, so we are enabling them to use Joule Studio to extend 麻豆原创鈥檚 pre-built agents with custom fields, tools, and reasoning logic while retaining all the deeply grounded integration capabilities 麻豆原创 provides. Joule Studio also provides low-code tools to build custom agents that integrate with all other Joule Agents, Joule skills, and 麻豆原创 BDC.

Using a low-code approach, users can build Joule Agents visually with natural language and drag-and-drop. But we also want to meet the needs of developers who want ultimate flexibility. Our pro-code approach gives developers the freedom to build agents using the agentic framework of their choice 鈥� for example, LangGraph, CrewAI, Google鈥檚 Agent Development Kit, and more. 麻豆原创 Cloud SDK for AI now supports agentic development, ensuring these pro-code agents can be seamlessly integrated and giving developers the best of both worlds: deep integration and full flexibility.

No matter how you want to build agents, an important question is how to integrate them into the larger ecosystem beyond 麻豆原创. We鈥檙e making Joule Agents fully compatible with the agent-to-agent (A2A) protocol soon, so agents can discover and collaborate with each other.

A2A exposes rich semantics describing an agent鈥檚 capabilities, allowing both 麻豆原创 and third-party agents to work together seamlessly. We are collaborating with partners 鈥� AWS, Google, Microsoft, ServiceNow, and more 鈥� to standardize this protocol for full interoperability. This capability will allow Joule to orchestrate tasks across multiple agents, both 麻豆原创 and non-麻豆原创, increasing automation and productivity across the enterprise. Read more here.

To manage and govern agents across the enterprise, is now generally available, providing centralized control of 麻豆原创 and non-麻豆原创 agents. In addition, is available now for tracing agent actions, benchmarking against KPIs, and identifying bottlenecks or opportunities for agents to further improve business.

No 麻豆原创 TechEd without ABAP news

The ABAP journey continues with 麻豆原创-ABAP-1, which will be available in the generative AI hub in Q4 2025. Trained on ABAP code, it is designed to build ABAP AI use cases, enabling developers to build smarter, custom AI solutions in modern ABAP code. .

In addition, ABAP Cloud development is coming to Visual Studio (VS) Code. The new ABAP Cloud extension for VS Code delivers a streamlined, file-based development experience with built-in AI assistance. Powered by an ABAP language server, it will initially support 麻豆原创 Fiori UI service development and expand to additional ABAP Cloud scenarios over time. This brings ABAP development into the same environment where developers already build with UI5 and CAP. General availability is planned for Q2 2026. .

What鈥檚 next: embodied AI and quantum

麻豆原创 TechEd is always an opportunity to look to the future. This year, that future includes not just humans, but also autonomous devices, including humanoid robots.

By integrating Joule Agents natively with robots, 麻豆原创 is bringing business logic into the physical world, enabling a wide range of autonomous devices to operate with enterprise context. We highlighted our strategic partnerships with robotics companies and system integrators to serve customers like Sartorius, Bitzer, and Matur Fompak, demonstrating how our expanding physical AI ecosystem enables robots to understand business processes and execute complex tasks autonomously.

Early proof-of-concept deployments show Joule successfully integrated with 麻豆原创 business applications and autonomous systems across asset performance, logistics, field services, and warehouse operations. While still in the pioneering stage, these implementations illustrate how 麻豆原创 is extending Joule to serve both human users and autonomous devices, shaping the future of enterprise AI.

Read more about the partnerships and implementations here.

AI is a new compute paradigm that changes everything. But there is another compute paradigm on the horizon: quantum computing. It鈥檚 early days, but 麻豆原创 is driving the future of enterprise computing with a vision to help businesses get ready for quantum computing.

麻豆原创 is not building quantum hardware; instead, we are focusing on creating quantum algorithms for business applications. These solutions are simple to deploy 鈥� on when needed, off when not 鈥� and are designed to be hardware-agnostic, collaborating with partners such as IBM to ensure seamless integration without re-platforming. This approach will enable organizations to unlock operational efficiency and drive better business results at enterprise scale.

I couldn鈥檛 be more excited about what鈥檚 next for our customers鈥� future as we bring 麻豆原创鈥檚 AI-native architecture to life.

Philipp Herzig is CTO of 麻豆原创.

The IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of technology and suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each supplier鈥檚 position within a given market. The Capabilities score measures supplier product, go-to-market and business execution in the short-term. The Strategy score measures alignment of supplier strategies with customer requirements in a three to five year timeframe. Supplier market share is represented by the size of the icons.

According to the IDC MarketScape, 鈥淎I-enabled tools are revolutionizing field service management, transforming reactive operations into predictive excellence.鈥�

麻豆原创 was recognized for the following strengths:

• End-to-end field service management offering as part of the full enterprise suite: 麻豆原创 Field Service Management is a fully integrated component of the 麻豆原创 Business Suite, enabling end-to-end business process execution across planning, logistics, operations, finance, and customer service. It connects seamlessly with core 麻豆原创 solutions such as 麻豆原创 S/4HANA, customer experience, asset management, and supply chain management, ensuring that service delivery is fully aligned with enterprise-wide processes. This deep integration eliminates silos, enables real-time collaboration across departments, and supports consistent, efficient service execution across the entire value chain.
• AI innovations and generative AI capabilities: 麻豆原创 Field Service Management is infused with AI and generative AI to simplify and accelerate service delivery. 麻豆原创 is able to support generative summaries of equipment history, work orders, and past service activities. 麻豆原创 has established an embedded AI copilot for field service that enables users to execute commands, automate actions, and retrieve context-aware insights using conversational language with the benefit of boosting productivity and responsiveness across the service life cycle. 麻豆原创 also has a robust auto-scheduling engine designed for complex, high-volume service operations.

Commitment to continuous innovation

Field service organizations face growing complexity, workforce shortages, and rising customer expectations that demand smarter, faster, and more connected service delivery. 麻豆原创 continues to lead the market by integrating AI-driven insights, intelligent automation, and end-to-end connectivity across its portfolio.

麻豆原创 remains focused on enabling customers to:

• Boost technician and dispatcher productivity
• Drive customer-centric and revenue enabling operations
• Reduce operational costs and accelerate complex workflows via intelligent automation and AI
• Provide a connected and extensible platform for field service

麻豆原创 is proud to be recognized by the IDC MarketScape as a Leader in AI-enabled field service management. We remain committed to helping our customers run their service operations smarter, safer, and faster 鈥� combining data, applications, and AI to deliver measurable business outcomes and exceptional customer experiences.

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Ryan Jones is product marketing manager for Operate and Service at 麻豆原创.

*Doc #US52967825e, September 2025

Early results in proof-of-concept applications of 麻豆原创鈥檚 robotics initiative, Project Embodied AI, demonstrate up to 50 percent reductions in unplanned downtime, up to 25 percent improvement in productivity, and significant reductions in operational errors across manufacturing, warehouse automation, and quality inspection.

These results are among the reasons why 麻豆原创 has expanded its Embodied AI ecosystem through partnerships with leading robotics companies and robotic enablement partners, as announced this week at 麻豆原创 TechEd. This builds on the recently announced collaboration with NEURA Robotics and NVIDIA to drive the future of physical AI.

The Embodied AI initiative extends the impact of into physical operations by making robots cognitive: able to autonomously execute complex tasks while understanding the broader business context in which they work. This empowers enterprises to faster adapt to changing operational environments.

麻豆原创 is uniquely positioned to deliver these innovations because of its decades of experience with business applications deeply integrated into the processes that power the modern enterprise. This allows 麻豆原创 customers to integrate robotics into the same business functions seamlessly, in a way no other company can. The result of our new robotics partnerships includes new proof-of-concept applications of embodied AI that demonstrate the business value and return on investment of our approach.

Cutting-edge experiments demonstrate measurable productivity gains

, a leading name in refrigeration, air conditioning, and heat pump technology, teamed up with 麻豆原创 and NEURA Robotics to revolutionize warehouse logistics. In a recent pilot proof-of-concept, BITZER鈥檚 warehouse became a testing ground for one of Europe鈥檚 most advanced humanoid robot, , which was able to perform pick-tasks on its own in real time.

The tasks are selected by embodied AI agents. The process also integrates 麻豆原创鈥檚 business logic from through (麻豆原创 BTP). Prior to its warehouse deployment, 4NE1 was trained virtually using NVIDIA’s Isaac Sim software. This ensured the robot was fully prepared for real-world operations. By integrating embodied AI into warehouse operations, BITZER could reach 24/7 utilization and a high level of responsiveness.

The technology can add to human expertise, stepping in during demand fluctuations and peak periods. It also complements regular shifts with flexible and scalable support. This ensures operations remain agile and efficient, even under varying workloads. Thanks to a single source of truth, orders can be expanded or cancelled in near real time, as robots execute changes almost instantly. This improves reaction times and enables BITZER to maintain high service levels while optimizing the use of resources.

鈥淲e are excited to join the Embodied AI initiative with 麻豆原创 and NEURA. We believe this collaboration will enhance our operational efficiency and drive innovation in our processes.鈥�

Christian Stenzel, Vice President of Corporate Organization and IT, BITZER

Transforming warehouse operations at Sartorius

Imagine stepping into a warehouse in which intelligent machines work side-by-side with humans. The first proof of concept for embodied AI at shows it is possible and marks a milestone in the journey to next-level logistics.

鈥淪o far, like many others, our focus was on fixed automation, in which specialized equipment handles only a single task. Now we鈥檙e making automation intelligent, and far more dynamic, to help us navigate a fast-moving world.鈥�

Steffen Dietz, Manager of Business Process Management in Operations and Supply Chain, Sartorius

The proof of concept, also delivered through the partnership with 麻豆原创 and NEURA Robotics, demonstrates how cognitive robots can support manual workstations in an advanced warehouse environment. Here, the humanoid robot 4NE1 was trained with Sartorius products in NEURA Robotics鈥� lab. The solution builds on an 麻豆原创 S/4HANA migration and 麻豆原创 Extended Warehouse Management (麻豆原创 EWM) rollout in May, which established the foundation for leveraging the latest capabilities from 麻豆原创.

The result boosts efficiency and enhances operational resilience. 鈥淲e鈥檙e really happy to help spearhead this new age together with 麻豆原创 and NEURA,鈥� Steffen Dietz, manager of Business Process Management in Operations and Supply Chain at Sartorius, shared.

Optimizing automotive production at Martur Fompak

, a global leader in automotive seating systems, teamed up with  and 麻豆原创 to explore how humanoid robots could transform field operations workflows.

Humanoid offers robots that provide cost-effective industrial automation and warehouse solutions, with modular designs that enable configurations for logistics operations, asset monitoring, and scalable field service applications.

Together the team is testing how cognitive robotics can support picking and packing operations at the company鈥檚 30 production plants across various continents and countries.

The early exploration connects Humanoid modular robots with 麻豆原创 solutions to execute workflows such as component retrieval, tray loading, and precise placement into production containers. 麻豆原创鈥檚 embodied AI agents provide context awareness around production orders and component variants.

“麻豆原创’s AI platform gives our robots intelligence to adapt and scale with enterprise needs, which creates flexible automation.”

Artem Sokolov, Founder and CEO, Humanoid

Initial findings demonstrate the value in automating repetitive and ergonomically demanding tasks, such as unpacking parts, handling trays, or supporting kitting processes. These experiments will be the foundation for a broader transformation in which humanoid robots participate in 麻豆原创-driven manufacturing environments and logistics processes.

Robotics company partners

Building upon these successes, 麻豆原创 announced the following additional partnerships:

AgiBot

Agibot creates general-purpose embodied robot products and an application ecosystem. The company delivers a complete product portfolio and deploy across all major application scenarios.

“Our 麻豆原创 partnership transforms industrial automation by combining humanoid capabilities with enterprise intelligence that understands business context,” said Peng Zhihui, founder of .

.

ANYbotics

ANYbotics provides a full-stack autonomous inspection solution that combines autonomous robotics with inspection intelligence.

“Integrating this continuous flow of inspection intelligence with 麻豆原创 makes operations not only autonomous but truly intelligent, where issues are predicted, understood, and prevented before they affect production,鈥� said Dr. P茅ter Fankhauser, CEO and co-founder of .

.

Booster Robotics

Booster Robotics provides T1 humanoid robots for warehouse operations and field maintenance.

“Our humanoid platforms, with 麻豆原创’s intelligence, creates an adaptive automation foundation that understands business processes and operational context,” said Cheng Hao, CEO of .

.

Galbot

Galbot’s fully autonomous, general-purpose humanoid robots have been deployed across a wide range of applications, including industrial, logistics, retail, and healthcare sectors. Powered by proprietary vision-language-action models, the Galbot G1 autonomously performs complex tasks such as precise parts sorting, industrial bin handling, and end-to-end pharmacy operations. These models enable Galbot robots to rapidly adapt to dynamic environments, ensuring high precision and efficiency even in challenging real-world conditions.

“Our collaboration with 麻豆原创 marks a key milestone in transforming how robots understand and operate within enterprise environments. By integrating business context awareness into our robots, we’re creating automation that seamlessly adapts to shifting operational priorities in real time,” said He Wang, founder and CEO of .

.

Humanoid

Humanoid offers reliable HMND 01 humanoid robots that provide cost-effective industrial automation and warehouse solutions, with modular designs that enable configurations for logistics operations, asset monitoring, and scalable field service applications.

“麻豆原创’s AI platform gives our robots intelligence to adapt and scale with enterprise needs, which creates flexible automation,” said Artem Sokolov, founder and CEO of .

Unitree Robotics

Unitree Robotics provides advanced quadruped Go2 robots for warehouse navigation and asset inspection, plus G1 humanoids with human-like dexterity for logistics operations, alongside industrial B2 models for outdoor facility maintenance.

“麻豆原创 embodied AI agents will revolutionize enterprise autonomous operations from warehouse management to predictive maintenance across facilities,” said Wang Xingxing, CEO and founder of .

.

Robotics enablement partners

麻豆原创 also introduced the following robotics enablement partners to connect humanoid and mobile robots, optimize intralogistics, streamline inspections, and orchestrate physical assets enabled by 麻豆原创 Business AI and automation technologies:

Capgemini

Capgemini explores the value that can be derived from the convergence of advanced technologies such as agentic and multi-agent AI systems, humanoid robotics, reinforcement learning, spatial computing, real-time 3D environments, and conversational AI. and 麻豆原创 are jointly exploring physical AI to help organizations gain a competitive edge.

Cyberwave 

Cyberwave connects 麻豆原创 systems to the physical world through its Physical AI platform, which integrates robots, sensors, and digital twins into enterprise workflows.

鈥淭ogether with 麻豆原创, Cyberwave turns enterprise data into coordinated physical action 鈥� bridging the gap between digital intelligence and real-world operations through Physical AI,鈥� said Simone Di Somma, founder of .

HCLTech

HCLTech provides automation expertise through its AI Force platform and 麻豆原创 integration capabilities, leveraging in collaboration with 麻豆原创 to accelerate generative AI-led robotics solutions.

“Our collaboration with 麻豆原创 enables cognitive robotics to seamlessly integrate with enterprise systems, transforming business operations through automation,” said Vijay Guntur, CTO and head of Ecosystems at .

KINEXON

KINEXON brings physical AI to day-to-day material flow management, helping customers scale mixed-fleet operations with a vendor-agnostic orchestration platform for autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and manual vehicles.

“Our collaboration with 麻豆原创 infuses business-driven agentic reasoning into real-world material movement planning and execution, maximizing utilization and throughput,” said Dr. Alexander Huettenbrink, co-CEO of .

Lighthouse

Lighthouse transforms business complexities into streamlined digital solutions, leveraging expertise across 麻豆原创 Intelligent Asset Management, 麻豆原创 Business AI, and 麻豆原创 BTP. 

鈥淓mbodied AI has huge potential for use cases, including asset and site inspection, health and safety, and quality inspection to deliver more resilient, flexible operations. We see major customer needs today, such as hazardous environments on offshore platforms in the oil and gas industry, utilities, and transportation,” said Urs Gehrig, managing director of Business Development at .

SinoSwissHub

SinoSwissHub is launching a regionally compliant, 麻豆原创-integrated orchestration platform for multi-robot fleets, with humanoids as the centerpiece.

鈥淲e don鈥檛 just connect robots to an 麻豆原创 system; we enable real-time physical data to reinvent processes and build adaptive, resilient value chains together with 麻豆原创,鈥� said Yuki Long, founder and CEO of and Aimbo Robotics.

Through these strategic alliances, 麻豆原创 continues to lead the evolution from traditional robotic tools to those that empower autonomous operations, informed by deep business context.

To explore how 麻豆原创 technology makes proofs of concepts possible in robotics, explore the . To get involved in 麻豆原创’s Embodied AI initiative, .

Dr. 艁ukasz Ostrowski is head of Embodied AI and Robotics at 麻豆原创.

Enabled by 麻豆原创 Business AI and built on 麻豆原创 Business Technology Platform, the assistant is already delivering faster response times, enhanced supplier experiences and smooth multilingual automation.

With 38 shows across global cities and a workforce of almost 4,000 artists and staff from 80 countries, Cirque du Soleil鈥檚 operations are as dynamic as its performances. Managing more than 70,000 supplier invoices annually鈥攅specially from tour-supporting vendors at residency shows鈥攈as placed increasing pressure on the accounts payable team. Nearly 40 percent of inquiries are from vendors seeking invoice status updates, and these inquiries were often delayed due to limited visibility and manual processing.

To address this, Cirque du Soleil turned to 麻豆原创 Business AI. The company鈥檚 new AI-enabled invoice assistant automates the triage-and-response process for invoice-related emails. It analyzes incoming messages in all languages, identifies the request type, extracts invoice details, determines the status of each invoice and even captures the sentiment of the email, prioritizing those that need attention more urgently. The assistant then generates a proposed response in English and French, significantly reducing the average handling time from 30 minutes to just two minutes per inquiry.

鈥淭he time-consuming research required to identify the payment status of an invoice and its reason was overwhelming,鈥� said Philippe Lalumi猫re, vice president of information technology, Cirque du Soleil Entertainment Group. 鈥淲e were looking for a more efficient way to handle this, and 麻豆原创 Business AI provided us with a simply stunning answer.鈥�

The assistant leverages 麻豆原创 HANA Cloud to store and process structured data derived from incoming emails, along with analysis results and generated responses. 麻豆原创 AI Core foundation supports intelligent automation, enabling the assistant to detect urgency, sentiment and even root causes of payment delays. This has drastically reduced manual workload and improved supplier satisfaction.

“As we partner with Cirque du Soleil on this transformative journey, it鈥檚 inspiring to see how technology is streamlining operations and focusing organizations even more on what they do best鈥攄elivering unforgettable experiences,鈥� said Dr. Philipp Herzig, chief technology officer and chief AI officer at 麻豆原创 SE. 鈥淭his is a perfect example of how data and AI can unlock both creativity and efficiency.鈥�

Key benefits include:

• Efficiency: Automation frees up employee time and accelerates response rates.
• Accuracy: AI minimizes human error and helps ensure timely, contract-compliant payments.
• Multilingual support: Bilingual capabilities enable inclusivity across Cirque鈥檚 global supplier base.
• Scalability: The assistant handles high volumes without additional resources.
• Enhanced experience: Standardized, timely responses foster stronger supplier relationships.

With this innovation, Cirque du Soleil continues to lead not only in the world of live performance but also in operational excellence. 麻豆原创 remains a trusted partner in this journey, helping the company scale its global footprint while staying agile and responsive.

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Lesa Plingen, +49 622 776 9000, lesa.plingen@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

Top image courtesy of Cirque du Soleil

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.

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.

Get started and deep dive into . We also have learning resources to help you get started .

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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.

Get started .

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.

Get started .

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%.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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%*.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started with .

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. .

.

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.

Get started .

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.

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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, 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.

According to a Gartner report, 70 to 80 percent of enterprise information lacks structure. This poses challenges for organizations that must unlock the potential and mitigate the risks of content to ensure data-driven decisions.

Take a simple, one-document example: It can cost up to $30 to process a single purchase order by hand. While this number seems small at first, it grows significantly when thousands of documents are processed every month over the years. And it doesn鈥檛 stop there鈥攅ach manual processing increases the risk of errors and potential loss of hours on the mundane job, hence missed opportunities. This leads to a high cost of running “business as usual” and a drag on innovation.

麻豆原创 Document AI: rescue business process

Manually processing documents is not just error-prone; it is also slowing down the response to market shifts, dragging down the creativity of skilled workers, and posing real threats to businesses.

麻豆原创 Document AI enables efficient and agile paperless business processes. AI-powered solutions can speed up business document processing by up to 70 percent through automating the extraction, classification, and processing of data鈥攊magine the boost in productivity, agility, and resilience.

This is not only theory. 麻豆原创 Document AI is enabling leaders to deliver reliable answers because it is grounded in the comprehensive and up-to-date training data of actual quality certificates:

• More than 180,000 annotated document pages
• Over 105 million annotated characters
• 28 countries in the data set
• More than half a billion unstructured documents processed each year

That is equivalent to approximately 8.5 years of manual information extraction and auditing, now available as a standard 麻豆原创 cloud product.

Take De Agostini Publishing as an example. With 麻豆原创 Document AI, the company is now saving around 500 hours per month, and more than 91 percent of purchase order-referred invoices are automatically processed. .

FRoSTA AG is one of the largest manufacturers of frozen foods in Europe. The company leveraged 麻豆原创 Build Process Automation together with 麻豆原创 Document AI, and it takes less than a minute to process聽an invoice from arrival to posting. Seventy percent of the invoices processed through automation are booked without any touch. What is even more interesting to note is that it took three months from project ideation to the go-live event. .

More than 34,000 customers are already using 麻豆原创 Business AI to transform the way they work.

From procurement and finance to HR and supply chain, 麻豆原创 Document AI is changing how work gets done. It is natively embedded in 麻豆原创鈥檚 key platforms, making it easier for leaders to orchestrate truly intelligent workflows.

The road ahead: leading with certainty

Leaders know that change is the only constant. Digitizing more paper is not the future of document management. It’s about using unstructured data to our advantage. Looking at the road map, 麻豆原创 Document AI will soon be able to handle even more types of documents. Enhancements such as vision-enabled information extraction, custom large language models (LLMs), and prompting are not too far off either.

Executive takeaway

Winning organizations do have one thing in common, and it is not the use of technology. They recognize that people drive business forward. By removing the manual burden, teams can be empowered to focus on what matters most: customers, strategy, and growth.

Leaders owe it to their teams to let them do what they do best, spending their time coming up with new ideas, making plans, and talking to customers. If employees are still buried in paperwork, it’s time to find out how much it really costs to wait. With 麻豆原创 Document AI, companies can develop the kind of flexibility and strength that today’s markets need.

Learn more about the benefits and new possibilities for business with .

Rashmi Kumari is a principal solution advisor at 麻豆原创.

Across the world, 95 percent of companies say growth is a priority for the year ahead. Their top focus areas鈥攊ncluding expanding market presence, broadening distribution through partners, and scaling operations鈥攕peak to leaders鈥� determination to create value in a climate of uncertainty and change.

In my engagements with customers, I see this reality every day. Companies everywhere want to grow, but they want to grow with confidence. They are looking for partners who understand their unique challenges, who support them with their long-term ambitions, and who can help them keep pace with rapid change.

Technology is central to this ambition. Nearly all respondents in the study rank simplifying work and improving processes alongside growth. Here, artificial intelligence stands out. Nine in 10 organizations have already made generative or agent-based AI a priority, and more than 70 percent have some form of AI in use. While concerns about data quality and talent remain, the message is clear: AI has moved beyond experimentation into the mainstream of how companies operate and unleash value.

From Frankfurt to Dubai to Singapore: How regional differences shape opportunities and risks

Regional differences tell a powerful story. In Europe, AI adoption comes with caution. Large enterprises put compliance, privacy, and transparency first, while many mid-market firms are still piloting solutions. In Asia-Pacific, the pace is different. Mid-market companies there already report strong AI use above global averages, and growth expectations run high. For them, AI is a way to seize advantage quickly in a fast-moving market.

These contrasts show why cultural intelligence matters so much for global leaders. Whether in Frankfurt, Singapore, or Dubai, I see how local realities, regulations, and expectations shape both risks and opportunities. In Europe, energy costs and geopolitical uncertainty drive supply chain strategies. In Asia-Pacific, digital adoption and market dynamism set a different pace.

Sustainability is another area where nuance matters. European companies place it near the top of their priorities, tracking or slightly exceeding global benchmarks. Asia-Pacific firms value sustainability but often rank it lower than growth and speed to market. Each is weighing trade-offs in its own context, creating exciting opportunities for 麻豆原创 to bring the most relevant technology, data, and practices to each region to help organizations achieve both economic and environmental goals.

The through-line in all of this is agility. Supply chain fragility, geopolitical conflict, inflation, and regulation continue to test even the best-run organizations. Technology can enable agility, but only if leaders embrace change themselves, rethinking processes, investing in skills, and building cultures of continuous learning and exploration. Security and ethical standards must also be the cornerstones of every AI conversation.

Turning AI potential into outcomes by centering value creation and integration

I believe this is a time for grounded optimism. The appetite for growth is real and the technology to achieve it is more advanced than ever. Innovation is accelerating at an extraordinary pace, with daily breakthroughs showcasing the expanding potential of AI.

There is a recent example that demonstrates AI’s ability to process multi-step tasks for over 30 hours. This achievement highlights not only the rapid evolution of AI, but also how increasingly accessible and capable these technologies are becoming.

However, as AI systems grow more autonomous and context-aware, organizations must recognize that true value doesn鈥檛 come from raw capability alone. To harness AI effectively, especially in enterprise environments, a consistent semantic layer is essential. It ensures alignment among data, tasks, and outcomes, enabling AI to reason reliably across systems and scale impact without losing coherence.

Companies must also move beyond simply adopting AI to actively testing and refining applications to gain a significant advantage. Equally important is a deliberate approach to managing the human element of a transformation, rooted in structured and human-centric change management.

Realizing AI鈥檚 true promise requires a fundamental shift in how people, applications, and data connect. Success relies on deeply connecting every part of an organization鈥檚 business, delivering end-to-end transformational value. A seamless, integrated suite provides insight and agility, whether responding to a problem or ensuring readiness when opportunity knocks.

This is where 麻豆原创 Business Suite is a game changer, integrating applications, data, and AI in a virtuous cycle that delivers tangible business outcomes. At our inaugural 麻豆原创 Connect event earlier in October, we showcased new applications, strategic data partnerships with Google Cloud and Databricks, and a new network of role-based AI assistants in Joule across every line of business.

Altogether, our marks the beginning of a new era powered by self-reinforcing AI, data, and applications. By keeping customer needs and value realization at the center and leading with innovation, businesses can not only navigate uncertainty, but build a more resilient, intelligent, and sustainable future.

Manos Raptopoulos is chief revenue officer of APAC, EMEA, and MEE, and a member of the Extended Board of 麻豆原创 SE.

Before diving into the heart of the keynote, Steinhaeuser invited 麻豆原创 solution area CMOs to deliver lightning-fast recaps of news from the various 麻豆原创 Connect event tracks. In just under two minutes each, they covered finance, procurement, supply chain, HR, and customer experience. From autonomous accounting and next-gen procurement to AI-driven talent acquisition and smarter customer loyalty, the message was clear: across every business function.

The real challenge: connecting priorities

As Steinhaeuser pointed out, 鈥淭he reality is each business area has its own unique priorities and, of course, all-important urgent matters.鈥� The real challenge is not just launching new features; it鈥檚 aligning processes, data, and teams to conquer uncertainty and achieve true customer focus. 鈥淪imply putting an [AI] agent on top of a broken process will solve nothing,鈥� he said.

The flywheel: AI, data, and apps in motion at 麻豆原创

So, how does it all work together? Enter the 鈥渇lywheel鈥� model: the dynamic cycle of AI, data, and applications that drives synergy across the enterprise. This is not just a theoretical approach. Steinhaeuser showed how 鈥溌槎乖� runs 麻豆原创鈥� using the flywheel model.

First, he said, 麻豆原创 uses 鈥渞ole-based AI assistants, powered by specialized agents, [to] support team members across all areas of 麻豆原创.鈥�

Next comes data. Earlier this year, 麻豆原创 became 鈥渃ustomer zero鈥� for (麻豆原创 BDC), connecting all enterprise data in a single layer to generate faster and better insights across financial, workforce, and sales planning. 鈥淲e’re excited to go live with the first set of intelligent apps, starting with People Intelligence,鈥� he added.

Finally, the app layer: 麻豆原创 has moved from 麻豆原创 ERP Central Component (麻豆原创 ECC) to and , through RISE with 麻豆原创. 鈥淭he 麻豆原创 Business Suite is where data is created and where AI delivers impact,鈥� Steinhaeuser said.

But processes continuously evolve with AI, he said, noting that business transformation management, powered by solutions like and , helps 麻豆原创 and its customers continually improve processes and architecture, with AI embedded everywhere. The company also uses to ensure employees stay informed and engaged at every step.

鈥淒riving 麻豆原创’s own transformation, I understand the challenges you face,鈥� Steinhaeuser said. 鈥淚 am convinced leveraging the flywheel of AI, data, and apps across the entire 麻豆原创 Business Suite is how we win together.鈥�

Embedded AI: tangible value, secure, and seamless

Brenda Bown, chief marketing officer of Business AI at 麻豆原创, took the stage to highlight how business AI is showing up in day-to-day work. 鈥淚’ve heard three consistent themes in conversations [with customers]: first, you want AI that can provide tangible value; second, that is secure and properly governed; and third, that works seamlessly across your teams and business. We’re here to deliver just that,鈥� she said.

Joule is now embedded in use cases in trusted 麻豆原创 applications and is making work faster and easier across the enterprise. 鈥淏y the end of this year, we will have more than 400 of these AI use cases,鈥� Bown said. Joule Agents automate tasks across departments, and the new agent builder in (generally available in December) helps customers extend, build, or customize their own agents. 麻豆原创 LeanIX AI Agent Hub and agent mining capabilities in 麻豆原创 Signavio provide governance and transparency for AI agents.

Bown noted that customers like Matur Fompack are using Joule in 麻豆原创 SuccessFactors to hire faster and improve career development. 鈥淭he results are phenomenal: a 48 percent reduction in HR process execution time and 40 percent faster employee development and career planning, and, most importantly, a better employee and candidate experience,鈥� she said.

For processes that require multi-step workflows and nuanced decisions, 麻豆原创 introduced a new generation of role-based AI assistants. 鈥淭hey know your role in the organization, because they are role and context aware,鈥� Bown said. These assistants tap into the right agents for the job, removing any guesswork and helping humans unlock new levels of insight and productivity.

She also showcased how agents collaborate across departments, automate workflows, and even extend 麻豆原创鈥檚 business logic to autonomous devices like robots. Early pilots with partners like NEURA Robotics are already showing Joule Agents planning and executing real work in the real world.

Data and intelligent applications: unified and actionable

Data is only valuable when it is actionable. Irfan Khan, president and chief product officer for 麻豆原创 Data and Analytics, highlighted 麻豆原创 BDC, which unifies enterprise data and powers intelligent applications. 鈥溌槎乖� BDC offers the most powerful foundation for connecting your existing data, building next-generation applications, and the ability to foster and deploy reliable AI,鈥� he said. And the new 麻豆原创 Business Data Cloud Connect solution enables secure, bi-directional data sharing with partners like Databricks and Google Cloud.

Intelligent applications bridge the gap between people and AI. They support smarter decisions and collaboration. 鈥淭hese applications learn from your data and include business simulations to support every business leader with smarter decisions,鈥� Khan explained. 鈥淚f we don’t have a reliable data foundation built around trust, having reliable and resilient data, it becomes very debatable whether or not AI will succeed.鈥�

From insight to action: transformation in practice

How do organizations turn strategy into action? Michael Ameling, president of 麻豆原创 Business Technology Platform (麻豆原创 BTP), demonstrated how 麻豆原创 Business Suite helps drive innovation by uniting core applications, data, and AI, all powered by 麻豆原创 BTP and Business Transformation Management solutions. 鈥淟et’s say you want to understand and improve a business process,鈥� he said. 鈥溌槎乖� Signavio lets you dive deep and understand every detail, and can suggest concrete actions. Then, use those insights to improve the process in 麻豆原创 Build by automating processes and building your own agents.鈥�

He demonstrated how 麻豆原创 BTP and the Business Transformation Management portfolio can help organizations connect systems, gain visibility, and automate processes. Tools including 麻豆原创 Signavio, 麻豆原创 Build, and 麻豆原创 Integration Suite are helping customers like Blue Diamond Growers streamline operations and accelerate transformation.

Services and support: accelerating innovation and realizing value

麻豆原创鈥檚 Anja Schneider, SVP and global head of Premium Engagement and Advisory, wrapped up this segment of the keynote by focusing on how the company鈥檚 services and support teams help customers realize the full value of their 麻豆原创 investments.

鈥淲e鈥檙e with you every step, like a personal trainer,鈥� she said, highlighting how 麻豆原创鈥檚 suite methodology, integrated tools like WalkMe and 麻豆原创 Cloud ALM, and expert guidance help customers realize the full value of their 麻豆原创 investments. She pointed to IBM鈥檚 transformation project as proof: working with 麻豆原创 MaxAttention teams and a clean core approach, upgrades went smoothly with low incidents for more than 150,000 users across 175 geographies.

Customer perspective: Southern California Edison鈥檚 journey

Real-world impact matters. Southern California Edison (SCE) SVP and CIO Todd Inlander shared how the utility company鈥檚 transformation journey with 麻豆原创 is helping modernize its foundational systems and optimize back-office processes. Facing unprecedented demand and environmental challenges, the company is leveraging 麻豆原创 solutions, including 麻豆原创 Business AI capabilities, to transform its operations.

鈥淲e need to adhere to our mission: to deploy safe, reliable, affordable power,鈥� he said. 鈥淲e can’t do that by doing things the way we’ve always done. We have to incorporate 麻豆原创. We’re using it to transform the way we work in our environment. We need to leverage AI because we don’t have enough humans to do all the work. We have to scale.鈥�

As SCE deploys 麻豆原创 Business Suite over the next year, it鈥檚 focusing on keeping a clean core and reducing customizations. 鈥淲hen we implemented ECC 15 years ago, about 66 percent of our enhancements were never used. We’re learning from that experience,鈥� Inlander said. He went on to note that SCE will use the 麻豆原创 deployment time to continue to transform its back-office operations. 鈥淲e’ll be integrating Joule and other AI solutions because doing things the way we’ve always done them and expecting a different outcome is the definition of insanity.鈥�

Steinhaeuser closed the keynote with a look to the future: 鈥淲e鈥檝e made great progress across all lines of business to deliver a unique experience for you鈥攚ith AI becoming your personal assistant, powered by data that defies boundaries and applications that take insight to action. The cross-capabilities you just saw now make the flywheel spin.鈥�

The future is here, and is powered by the synergy of AI, data, and applications. Every business can turn innovation into impact.

New research shows how business AI delivers ROI

To better understand the opportunity to produce returns on investment from AI, 麻豆原创 commissioned that was shared at 麻豆原创 Connect. In partnership with Oxford Economics, we surveyed 1,600 executives in medium and large enterprises across eight countries.

We found that today, on average, organizations are benefiting from a 16 percent return on AI investments鈥攁 number they expect to nearly double within two years. In addition to impressive financial returns:

• 94% of business leaders say AI is improving innovation within their organizations
• 87% say AI is improving customer engagement
• 78% believe AI agents have the potential to transform their business operations

New deep research and AI assistants in Joule expand what is possible

These innovations were engineered based on what our customers tell us they need: to act quickly, simplify complexity, and unlock better, data-driven decisions across the lines of business and processes that matter. But most of all, our customers need AI that drives significant, measurable business outcomes.

To help every organization accelerate returns on investment from AI, at 麻豆原创 Connect we announced powerful new capabilities for , which makes business data and the entire 麻豆原创 Business Suite immediately accessible through the power of a simple conversation. And because Joule is grounded in your company鈥檚 data, it understands context and delivers insights that are specific, actionable, and relevant to your business.

Deep research in Joule, announced at 麻豆原创 Connect, is a new capability expands what people can do within the Joule interface. It goes beyond quick answers to deliver strategic analysis, reporting, and synthesis in a single, connected experience. It brings together internal 麻豆原创 data and external intelligence so people can ask complex questions and receive comprehensive research and recommendations鈥攚ithout ever leaving Joule. The deep research capability in Joule will be available in beta this December.

We also unveiled the new concept of role-based AI assistants in Joule, built to partner with people in their specific roles. These assistants connect to the right Joule Agents for the job, removing guesswork so teams can unlock new levels of productivity and insight. Whether it鈥檚 a finance leader forecasting working capital, a recruiter evaluating headcount needs, or a planner adjusting inventory, AI assistants surface the right intelligence, at the right time, in the right context. In the background, Joule Agents get work done for you.

These innovations mark the next chapter in how people interact with enterprise systems, helping every role across an organization seamlessly move from inquiry to insight to action.

New Joule Agents autonomously get work done

To help enterprises further accelerate business results, we introduced 14 new Joule Agents at 麻豆原创 Connect. They help people coordinate, decide, and execute tasks with greater precision. Joule Agents are in finance, HR, procurement, and supply chain, in a way that only 麻豆原创鈥攚ith our deep expertise in these functions鈥攃an deliver.

For example, rather than navigating multiple systems or running countless manual checks to release an order, a production manager鈥攁 key role in the supply chain function鈥攚ill be able to turn to our Production Planning and Operations Agent, planned for general availability in the Q1 2026. They can simply ask Joule to do it, safely and in real time. The agent will validate and release orders when conditions are met, accelerating production start times and shortening order-to-delivery cycles.

And starting December 2025, with the general availability of , now in beta release, customers will be able to create and deploy custom Joule skills and Joule Agents tailored to their unique business needs. Agent builder in Joule Studio is your command center for designing, building, and deploying enterprise-ready custom Joule Agents using the same powerful 麻豆原创 technologies鈥攊ncluding 麻豆原创 Knowledge Graph for deep business context, 麻豆原创 Business Data Cloud for comprehensive data access across 麻豆原创 and non-麻豆原创 sources, and 麻豆原创’s central identity and authorization services to ensure responsible agent behavior. These capabilities empower every enterprise to extend, customize, and personalize 麻豆原创 Business AI solutions.

New embedded intelligence across 麻豆原创 applications

To help our customers move faster and make better decisions where work happens, we continue to bring intelligence directly into the applications they rely on every day. These embedded capabilities extend the same AI-driven guidance that powers Joule Agents into core 麻豆原创 solutions, enhancing user workflows with context, clarity, and automation. We will have more than 400 of these AI use cases by the end of the year.

For example, in , starting in February 2026, AI will orchestrate personalized interactions across HR, marketing, and service, bringing harmonized data, relevant context, and better business outcomes into every engagement. In the solution, planned for general release in the first half of 2026, AI will predict shortfalls and fulfillment risks, helping planners simulate and respond with speed and precision.

Additionally, the rebuilt 麻豆原创 Ariba source-to-pay suite, arriving in February 2026, brings a modern, cloud-native experience to every stage of procurement. Embedded AI guides people with intelligent recommendations, accelerates contract reviews, and surfaces supplier insights in real time. By simplifying sourcing decisions and improving compliance, it helps procurement teams strengthen supplier relationships and capture more value, faster.

Governing AI with visibility and control

As our customers continue to adopt these AI innovations embedded across their functions, we know they need transparency into how it operates, what it influences, and the value it creates. That is why we provide tools to give them the visibility they need to deploy AI with confidence and scale it responsibly.

麻豆原创 LeanIX AI Agent Hub helps CIOs and business leaders see their entire AI agents landscape at a glance. From one dashboard, they can understand where agents are deployed, what processes they touch, and how agents are performing. This allows teams to evaluate effectiveness, identify redundancies, and manage AI like any other enterprise asset: aligned to outcomes, governed by policy, and continuously optimized.

Complementing that, agent mining in gives organizations a powerful way to analyze how AI contributes to process performance. It reveals how AI agents decide and act, flags bottlenecks and non-compliance, and uncovers where automation adds value and how to fine-tune it for efficiency and impact. Together, these tools bring clarity to what has often been a black box: transforming governance from reactive oversight into proactive optimization.

What鈥檚 next for business AI

At 麻豆原创 Connect, we also shared a view into what鈥檚 coming and how our innovations will continue to redefine enterprise productivity. For example, we鈥檙e developing an outcome-driven user interface that adapts to context in real time. Instead of navigating menus or searching for data, people will simply express what they want to achieve, and the system will guide them through the right actions, insights, and tools.

We鈥檙e also extending Joule Agents beyond software into the physical world鈥攃onnecting your company’s business intelligence to robotics and industrial systems. This opens a new frontier for automation, combining state of the art electronics that utilize physical AI tools, such as computer vision and collision detection, with AI agents capable of reasoning through complex goals and planning multi-step workflows. this November to learn more.

Ready to start your AI journey?

We know AI is top of mind for most business leaders today. In fact, another finding from the research we commissioned with Oxford Economics is that 41 percent of tasks in global businesses will be supported by AI within two years鈥攗p from 25 percent today.

As you continue to explore what is possible with business AI, we鈥檒l keep innovating to deliver systems that are intelligent by design, trusted in operation, and, most important, measurable in their impact.

For us, it鈥檚 all about what you hope to achieve. We鈥檙e proud to partner with you on your AI journey. If you鈥檙e ready to take the next step, here are three things you can do right now:

• Learn how to bring the potential of AI into your organization by signing up for our .
• In our , get inspired about what鈥檚 possible by exploring how leading companies are transforming with AI.
• Watch 麻豆原创 Connect virtual sessions, , to see our latest innovations in action.

There鈥檚 more to come. Join us at on November 4 for the next wave of AI innovations that will transform the enterprise.

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

Against the backdrop of the event theme鈥�”Connect Everything, Achieve Anything: Agents, Data, and the Business Suite鈥濃�攖hey set out 麻豆原创鈥檚 vision for how 麻豆原创 Business Suite, which combines AI, data, and applications, can transform enterprises and deliver unprecedented business value to customers despite global macroeconomic uncertainties. 

Unique times

鈥淲e are living in very unique times,鈥� Alam said at the start of the keynote. 鈥淯nique in terms of the unpredictability we face from a geopolitical and macroeconomic perspective,鈥痑nd also unique in terms of the advancement in AI and the potential that carries for all of us.鈥�  

He added, 鈥淓ven the most significant challenges can be responded to, navigated, and鈥攚hen approached the right way鈥攖urned into opportunities. And that鈥檚 exactly where 麻豆原创 comes in. Because the best way to face uncertainty is with confidence that you can see what鈥檚 happening across your business and your network.鈥� 

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The CFO perspective 

His comments were echoed by CFO and Executive Board Member Dominik Asam in an onstage discussion with economist and Berkeley professor Ulrike Malmendier, during which they likened the role of the CFO in navigating today鈥檚 business uncertainties to that of co-piloting a modern jet. 

鈥淎I is the next supercycle and has what it takes to create an effective cockpit for the CFO, including recommendations about real actionable options all the way to autopilot for less critical tasks,鈥� Asam said. He also warned that standing on the sidelines of technological progress is 鈥渁 sure recipe for falling behind in competition.鈥�  

鈥淎s in prior tech supercycles, the entire competitive playing field is being completely reshuffled,鈥� he said.

New products

Building on this theme, Alam noted that while uncertainty is real and isn鈥檛 going away, it can be successfully navigated and turned into opportunities. To help customers achieve this, he announced several new and enhanced 麻豆原创 products. 

Among them, 麻豆原创 Supply Chain Orchestration is an AI-native application that uses a network knowledge graph to analyze real-time signals across a company鈥檚 multi-tier supply chain to detect risks and issues, such as extreme weather or tariffs. It then helps customers minimize disruptions by assessing the impact of these risks and suggesting alternatives to help minimize disruptions.   鈥淭hink of it like a GPS in your car which selects an alternative route to avoid traffic or tolls,鈥� Alam explained. In addition, he announced a major update to the 麻豆原创 Ariba solutions for source-to-pay suite, positioning 麻豆原创 Ariba as the most modern platform in the industry and the only truly AI-native source-to-pay solution鈥攁ll built on 麻豆原创 Business Technology Platform.

The human-AI partnership opportunity 

Turning to uncertainties over the future of work itself, 麻豆原创 Chief People Officer and Executive Board Member Gina Vargiu-Breuer, who is leading 麻豆原创鈥檚 own workforce transformation, was joined on stage by Ian Beacraft, founder and chief futurist of Signal and Cipher. 

鈥淎t 麻豆原创, we know firsthand that AI is everywhere, shattering norms and transforming the workforce,鈥� Vargiu-Breuer said. 鈥淎nd we as 麻豆原创 are boldly steering this shift, as requirements for our workforce are simply changing really fast.鈥�  

Vargiu-Breuer emphasized that a successful business AI strategy also depends on leveraging AI alongside human expertise and fostering what she described as 鈥渁 collaborative human + AI approach, rather than just automation.鈥�  鈥淏y integrating AI’s capabilities with human creativity, empathy, and judgment, we move beyond simple automation into real human-AI power couples,鈥� she said. 鈥淯ltimately, the future will favor those who embrace orchestration, delegation, and creative problem-solving.鈥�

Role-based AI assistants

Echoing this human-centric approach, Alam noted, 鈥淓veryone is talking about agents鈥攂illions of agents鈥攁nd agents taking over everything. We want to talk about people, the roles they play, and the tried-and-tested organizational constructs in place today that are running complex businesses across industries.鈥� 

Reflecting this, he said 麻豆原创 is making Joule deeply aware of the workstyle of the person it partners with, their role, and the business process context in which they operate. 鈥淭oday, we are introducing AI assistants, including a receivables assistant for your accounts receivable colleagues, a controlling assistant for your controlling colleagues, a demand Planning assistant for your demand planning colleagues, and an AI assistant for every role.鈥�   Each assistant has agents and AI tools at their disposal to help make the person it partners with smarter and more efficient, Alam explained.

Taking the receivables assistant as an example, he said it can handle collections and dispute resolution today and will soon also be able to help with fraud detection, invoice processing, and payment scheduling. 鈥淥ver time, we will continue to make this assistant even smarter by adding more agents and capabilities鈥攁ll designed to make the person in this role more effective.鈥�

Deep research and new intelligent applications

鈥淲hile efficiency and automation carry potential for great value for the organization, AI鈥檚 greatest strength is in unlocking insights and recommendations based on its ability to do deep research across vast amounts of internal and external data, which is hard for people to do,鈥� said Alam. To address this challenge, 麻豆原创 is introducing deep research in Joule, a capability that can research and analyze complex problems and deliver findings quickly and efficiently. 

Following additional announcements, including an expanded set of 麻豆原创 Business Data Cloud Intelligent Applications and an enterprise wide, multi-stakeholder engagement orchestration solution in 麻豆原创 Engagement Cloud, Alam closed out the keynote by reminding his audience: 鈥淭o create exponential value and to reach the global maxima for your enterprise, the whole matters.  And that鈥檚 what we are focused on: providing you with best-in-class applications, seamlessly and natively integrated across the breadth of finance, spend, supply chain, HCM, and customer experience.鈥� 

麻豆原创 Business Suite delivers unprecedented value

The unmatched value of 麻豆原创 Business Suite is that it brings together the power of best-in-class applications with a semantically rich harmonized data layer to power high-value AI in a singular seamless experience. It helps you manage uncertainty, evolve your workforce, and break down silos to create amazing customer value.

According to new research from 麻豆原创, employees using AI are saving 75 minutes a day 鈥� time that鈥檚 being reinvested into innovation, connection, and impact. 

But with economic volatility, shifting regulations, and a global skills crunch, organizations face a critical challenge: how to connect their people and their business in ways that drive agility, resilience, and growth. This isn鈥檛 just a moment of change; it鈥檚 a moment of unprecedented possibilities.

Unlocking new possibilities with 麻豆原创 SuccessFactors

is powering that transformation with trusted intelligence, operational strength, and innovations that turn disruption into advantage.聽With over 10,000 customers worldwide, we are privileged to work with the world鈥檚 leading brands and help them guide their people and their organizations through change.聽

The 麻豆原创 SuccessFactors HCM suite is a robust offering that connects all the pieces for an organization鈥檚 people strategy 鈥� from core HR and payroll, to talent acquisition and talent management, to people analytics, and beyond. 麻豆原创 Business AI is infused across our HCM suite, and 麻豆原创 Business Technology Platform (麻豆原创 BTP) enables our customers to expand and extend to meet their needs.聽

We are constantly investing in our solutions based on market signals, ensuring our customers have the tools they need to stay at the forefront of innovation. 

Today at Success Connect at 麻豆原创 Connect in Las Vegas, designed to elevate the employee experience, optimize operations, and deliver actionable workforce insights. 

Elevating the employee experience  

New Joule Agents  

Agentic AI is redefining the employee experience and transforming the way work gets done by automating routine tasks, accelerating decision-making, and unlocking new levels of productivity. Joule, 麻豆原创鈥檚 AI copilot, is embedded into enterprise-wide applications to deliver real-time intelligence and automation through a simple conversational interface.  

Joule currently supports 80 percent of the most-used tasks in 麻豆原创 systems, and we are continuously expanding its capabilities. Joule is available in 11 languages, and next month the first HR-focused Joule Agent 鈥� the Performance and Goals Agent 鈥� will be generally available, with many more to follow. This agent is designed to empower managers to lead high-impact performance conversations by providing tailored insights, goal progress updates, and personalized talking points.

We鈥檒l continue to release new agents that will continue to work behind the scenes to make managers, employees, and HR teams more efficient. Today, we announced the next four聽agents, available in 麻豆原创 SuccessFactors in the first half of 2026:聽

• The Career and Talent Development Agent, which automates succession planning and helps managers identify and develop future leaders
• The HR Service Agent, which serves as a direct point of contact for employees and reduces the amount of time HR staff spend answering routine questions
• The Payroll Agent, which helps employees better understand their pay by combining paycheck details with time data, enabling intelligent 鈥渆xplain pay鈥� scenarios such as highlighting unexpected overtime and suggesting follow-up actions
• The People Intelligence Agent, which connects the People Intelligence Insight application in 麻豆原创 Business Data Cloud with Joule and 麻豆原创 SuccessFactors, allowing managers and HR teams to ask questions in their own words and receive intuitive, accessible workforce analytics

Introducing the workforce knowledge network

Building on these new capabilities, we are also introducing a workforce knowledge network, a first-of-its-kind integration that brings third-party content from industry experts directly into Joule, delivering enhanced insights for employees.鈥� This is a major step forward in enabling agent-to-agent interaction in order to deliver the most relevant information in one seamless experience.

Content from leading HCM industry experts from G-P (Globalization Partners) and The Josh Bersin Company will flow directly into Joule. These integrations allow Joule to ingest third-party content and interact with various agents so employees can receive guidance that is grounded in real-world insights and trusted research.

For example, HR leaders can access G-P Gia, an HR agent developed by G-P, directly within Joule, providing access to expert global employment guidance. Additionally, they can ask Joule, 鈥淲hat are best practices for hiring engineers in a high-cost location?鈥� and Joule can respond with research-backed insights and recommendations provided by Galileo, a trained AI agent developed by The Josh Bersin Company, with over 6,000 users across more than 800 companies.

鈥淛oule offers a revolutionary technology to speed and simplify the lives of every business person,鈥� said Josh Bersin, CEO of The Josh Bersin Company. 鈥淲e are very excited to connect Galileo, a leading AI agent for HR, to all 麻豆原创 users and give them deep insights into all their human capital decisions.鈥� 

Optimizing Operations

Innovations in Core HR

Operational strength is the backbone of every great employee experience; it enables scale, consistency, and confidence, especially in times of change. That is why we continue to invest deeply in core HR.

With localization support across 104 countries and usage in 179, remains the industry鈥檚 most trusted foundation for global HR operations. And today we have announced that it鈥檚 getting even stronger:

• New
  Early adopter January 2026
  This new solution enables shift planners and supervisors in manufacturing and production to create smarter schedules aligned with real-time business demand and required skills, reducing administrative burden, helping to prevent costly overstaffing and understaffing, and maintaining compliance.
• New enhanced time-off capabilities in 麻豆原创 SuccessFactors Employee Central
  Generally available next month
  This enhancement allows our customers to meet country-specific and complex leave regulations in markets including but not limited to Australia, Germany, and the U.S., helping them stay compliant while simplifying processes for managers and employees.
• 
  Generally available now
  Announced earlier this year, our new HR service delivery solution extends the power of core HR by automating workflows, streamlining service requests, and freeing HR teams to focus on high-value, strategic work.

Delivering best-in-class insights

People Intelligence

Operational excellence lays the groundwork, but true transformation happens when data becomes insight. That is where comes in. in People Intelligence announced at 麻豆原创 Sapphire in 2025 are now generally available. People Intelligence transforms people, skills, and business data into actionable, AI-driven insights that help HR and leaders make better, more strategic decisions for the business and its people.鈥�

At Success Connect, we unveiled additional prebuilt insights for recruiting, learning, succession, career development planning, and performance and goals management. People Intelligence continues to expand, with more prebuilt insights for rewards and recognition, benefits, time management, and onboarding planned for May 2026. 

SmartRecruiters

麻豆原创 is also advancing the way organizations attract, recruit, and hire top talent. Last month, we acquired SmartRecruiters to build the future of AI-driven talent acquisition. At Success Connect, we showcased how this move strengthens our vision. By combining the scale of 麻豆原创 SuccessFactors, the power of 麻豆原创 Business AI, and the expertise of SmartRecruiters, we鈥檙e delivering an intelligent, end-to-end global hiring solution that simplifies recruiting and ensures every hire is aligned to business and workforce goals.

Where innovation meets impact 

Innovation in HR has entered a new era that is defined by connection. By uniting people, processes, and intelligence, organizations can move beyond incremental change to unlock unprecedented possibilities for impact, agility, and growth. With continuous advancements in AI, a trusted global foundation, and intelligence-driven insights, 麻豆原创 SuccessFactors is helping organizations meet today鈥檚 challenges head-on and shape the future of work with confidence.

To catch our Success Connect keynote replay and learn more about the latest innovations in 麻豆原创 SuccessFactors, .

Dan Beck is general manager and chief product officer for 麻豆原创 SuccessFactors.

AI, with already proven applications, can unlock insights to reduce global greenhouse gas emissions by . , over half of sustainability executives say one of their top actions in the next three years is expanding their use of AI to enhance ESG capabilities.

Most businesses have not yet realized AI鈥檚 full potential for sustainability. In fact, are using AI today to reduce carbon emissions. But those ready to do so will gain a decisive advantage that goes beyond emissions reduction. 麻豆原创鈥檚 ERP-centric approach enables organizations to deliver sustainability outcomes with applications, data, and AI embedded into . With sustainability reporting, data processing, automation, and strategic insights, AI can navigate your business through today鈥檚 climate challenges and ensure tomorrow鈥檚 competitiveness.

Power on, ethically and responsibly

Scaling AI solutions comes with considerable energy and water usage. To ensure net benefit, this needs to be part of return on investment conversations. With robust governance and renewables-backing however, AI is able to reduce more emissions than it generates.

All 麻豆原创 data centers are powered by 100% renewable energy and any emissions from use of third-party AI systems are calculated and included in the company鈥檚 Scope 3 emissions.

Used ethically and responsibly, AI can be the catalyst of your sustainable business transformation. Here are eight ways that businesses use 麻豆原创鈥檚 AI-powered systems to build their sustainable advantage.

Improve efficiency with automation

1. Compliance information processing

The for product compliance, AI-assisted compliance information processing capability can automatically extract compliance information from updated documents and map the information to compliance requirements.

This can reduce costs in product compliance disclosures, reduce penalties and fines in environmental management, and automate processes to reduce the risk of manual errors.

This helps turn a 50-minute task into a five-minute job and reduce processing and evaluation costs by 90%.

2. Declaration image analysis

With the , AI-assisted declaration image analysis capability, you can automatically extract data and information from sustainability declarations regardless of format.

This helps cut review time, eliminate manual error risk, and ensure your reports are ready for required external audits.

Without AI, it takes roughly five minutes to review, extract, and post information from declarations. With AI, it鈥檚 just 20 seconds.

3. Permit management

can read hundreds of pages in seconds, extract the compliance requirements, and propose clear tasks to meet permit requirements.

This AI-assisted capability can save days of permit review and interpretation, remove the need to hire external consultants, and lead up to an 80% reduction in environmental penalties and fines.

Your personal AI carbon consultant

4. Emission factor mapping

奥颈迟丑听, 麻豆原创鈥檚 AI-enhanced solution, users can calculate product and corporate carbon footprints. Where actual supplier emissions data is given, it can retrieve that information from 麻豆原创 Sustainability Data Exchange and other systems. When estimates are required, the solution can automatically find the most accurate emissions factors from databases and map those to products.

Audit-ready emission factor mapping can turn a 10-minute manual task into a two-minute verification.

5. Report generation

In the solution, you can generate comprehensive ESG reports in just a few clicks:

• Automatically generate reports that align with internal sustainability strategies and meet external requirements such as the Corporate Sustainability Reporting Directive (CSRD).
• Take data collection from a half hour to a half minute and report creation and drafting from 30 hours down to just five hours, all the while eliminating confusion and the risk of manual errors.

6. Carbon emissions analysis 

From reporting on today to planning for tomorrow, , 麻豆原创鈥檚 copilot, can take current carbon emissions data and return actionable insights that help reduce emissions and guide corporate sustainability strategies. 

By combining financial and carbon data, Joule can create carbon intensity KPIs and can be your ultimate corporate sustainability consultant.

The AI safety officer for your EHS team

7. Safety observation reporting

Complex safety reporting procedures dissuade employees from reporting potential hazards. With the 麻豆原创 S/4HANA Cloud Public Edition, EHS workplace safety, AI-assisted safety observation reporting capability, basic users can input safety observations in natural language, and the AI model can process that into a formal incident report, prompting the user for any missing details.

This can increase the likelihood that employees report safety hazards and helps prevent severe incidents by identifying potential safety issues in advance.

8. Safety instruction generation

Your AI safety officer can generate clear safety instructions for specific equipment based on the latest risk assessments and job hazard analyses.

With 麻豆原创 S/4HANA Cloud Public Edition, EHS workplace safety, AI-assisted safety instruction generation, the time and effort of manually prescribing and updating safety instructions can be dramatically reduced.

Solve today鈥檚 sustainability challenges while preparing for tomorrow

The right AI integration can ensure you future-proof your operations while shining a light on the path that drives competitiveness.

What sets 麻豆原创 apart is our suite-first, AI-first approach that helps ensure sustainability isn鈥檛 an add-on, but a strategic enabler that can deliver measurable outcomes at scale. 麻豆原创鈥檚 one sustainability data model can drive consistent reporting, deeper insight, and confident decisions across every sustainability process, product, and partner network.

With a responsible AI partner, businesses can realize measurable financial returns on AI investments and unlock sustainability benefits; automate manual-heavy paperwork; identify emissions hot spots and steer their business toward a decarbonized economy; and make environmental impact tracking visible to all lines of business based on a reliable single source of truth. With an integrated set of capabilities, solutions help businesses address their sustainability needs holistically and across topics. The result is speed, trust, and traceability, which turn sustainability into strategy, not just compliance.

Get in touch to find out how 麻豆原创 can help your business power on with sustainability solutions.

Monica Molesag is global head of Sustainability Communications at 麻豆原创.

Among the many announcements at 麻豆原创 Sapphire in 2025, the company unveiled new innovations, partnerships, and integrations that can deliver real-time, proactive assistance. For example, 麻豆原创鈥檚 AI copilot Joule is now available to users across 麻豆原创 and non-麻豆原创 systems. 麻豆原创 also expanded its agentic AI footprint across 麻豆原创 Business Suite by introducing Joule Agents for multiple use cases and an evolving AI Foundation as the AI operating system designed to simplify development, enabling developers to build, deploy, and scale solutions with ease.

The impact of AI on the delivery of customer support at 麻豆原创

As announced in Q2 this year, 麻豆原创鈥檚 simplified, tiered, services-and-support engagement model will be generally available in early 2026. Here, 麻豆原创鈥檚 customer support is a centerpiece of the Foundational Success Plan, delivered via the proven 麻豆原创 Enterprise Support offering included in every 麻豆原创 cloud solution subscription. The Foundational Success Plan can support in-house teams by helping to onboard and run solutions, keep business continuity, and drive ongoing value. It includes customer self-service options, application lifecycle management solutions centered around 麻豆原创 Cloud ALM, and preventative mission-critical support. With the plan, 麻豆原创 turns on Joule for a customer鈥檚 business and supports the team ramp-up with learning journeys for 麻豆原创 Business AI.

When it comes to customer support in general, agentic AI can redefine the support process by moving beyond scripted responses and basic automation. It can assess situations, make decisions, and take action鈥攐ften before the customer even knows there鈥檚 an issue. 麻豆原创鈥檚 customer support harnesses agentic AI to help deliver smarter assistance, faster resolutions, and a stronger human鈥搕ech partnership.

We focus on elevating support experiences for customers and improving support delivery for engineers by employing a combination of agents and assistants. For example, we use autoresponders and smart log analyzers to help process issues, while configuration advisors, language services, and proactive notifiers can guide customers toward self-service solutions. At the same time, our support engineers rely on co-pilots to help summarize cases, recommend solutions, escalate using intelligence, assist with communications, and create a continuous feedback loop for learning. For strategic customer support, we use tools like feedback collectors to help capture customer insights and channel recommenders to help ensure that every interaction is handled in the right channel. Together, these innovations can redefine support as faster, smarter, and more human.

The impact for customers

When it comes to 麻豆原创 Business AI, we build trust and create customer confidence by being relevant, reliable, and responsible. Unlike traditional AI that only suggests answers, agentic AI can reason, decide, and take action. For customers to feel confident, they expect accuracy, reliability, and transparency from the system.

As we support and guide our customers, we recognize that while agentic AI is a game-changer, it is not a magic pill. Coupled with ethical and responsible AI, real impact comes from 麻豆原创鈥檚 business expertise and a deep understanding of what our customers truly need. When knowledge is combined with AI to infuse autonomy and interoperability in our agents, we can unlock the ability to simplify processes, remove friction, and deliver experiences that feel effortless.

AI technology amplifies human insight and delivers delightful user experiences, but when it comes to business AI, it is our domain expertise that fuels 麻豆原创 Business AI into a tool for creating genuinely easy, productive, and meaningful experiences for our customers.

Stefan Steinle is executive vice president and head of Customer Support & Cloud Lifecycle Management at 麻豆原创.