This year at 麻豆原创 Sapphire, we shared our vision for the Autonomous Enterprise — the next evolution of how businesses run, where AI agents execute critical workflows so people can focus on innovation, customer value, and business growth.

This vision comes to life through a reimagined Joule Work, evolving from an AI assistant into the central workspace for enterprise AI. We also introduced the 麻豆原创 Autonomous Suite, bringing AI agents and assistants across core business functions to execute complex workflows with human oversight. With 麻豆原创 Business AI Platform, customers and partners can build, manage, and govern AI agents. And by expanding Industry AI, we’re delivering AI grounded in deep business context and domain expertise to solve industry-specific challenges.

Customers are already benefiting. IT division, Bosch Digital, integrated 麻豆原创 Joule for Developers directly into their coding workflows. Developers saw a 20% increase in productivity using Joule to automate routine coding tasks and optimize code. Joule also generates test cases, speeding up unit testing by 15% to 20% and freeing senior developers for high-value tasks. , the country鈥檚 leading airport operator, defines safety thresholds, service levels, and playbooks, and its agent, Smart Network for Operative Winter (SNOW), executes them. The SNOW agent is a winter operations system that integrates real-time weather, runway, and operations/maintenance data to automatically orchestrate work at Patagonian airports. The agent has improved runway safety, cut direct costs by 16%, and reduced administrative effort by 90%.

built a tool using  so its clients can better handle international tax rules by developing and managing their own custom AI agents and solutions. This way, PwC鈥檚 clients can focus on strategy while AI handles tax. PwC鈥檚 tool helped one pharmaceutical company handle VAT on international transfers 60% more efficiently.

Another customer, , a global fashion retailer, used an AI agent, built on 麻豆原创 Joule, to cut HR process cycle times by 40% to 60%. The agent helps employees quickly handle HR transactions, such as leave requests and payroll queries, through natural language conversations. Reducing time spent on administrative tasks allows HR teams to focus on strategic talent management. These are just some of the customers getting value. There are many more.

Now let鈥檚 dive into the releases from Q2 2026.

Please note that this article covers only AI offerings released from April 1, 2026, to June 30, 2026.

Joule

Joule Work
麻豆原创 Early Adopter Care program (registrations closed)

redefines how people interact with and execute end-to-end business processes. As the user engagement component of the Joule solution, it moves the user experience beyond fragmented, transactional interfaces toward a unified, intelligent way of working across 麻豆原创 and non-麻豆原创 systems. Its dynamic workspace adapts to users’ intent, helping them focus on outcomes rather than spending time finding information. And because it can delegate execution to AI, users will no longer need to coordinate work across multiple application interfaces manually.

Joule Work will allow users to express in natural language what they want to accomplish, triggering to coordinate teams of Joule Agents that will surface the right insights and automate routine work across business domains and systems to achieve the goal. This happens in intent-driven, adaptive workspaces built in real time that keep teams focused on driving decisions and impact. Joule Work can help reduce manual handoffs, shorten cycle times, and enable teams to turn decisions into actions faster. A key function of Joule Work is to connect users with Joule Assistants, which are like smart teammates organized by function. These assistants use context to intuit people鈥檚 intent and act by coordinating the appropriate Joule Agents across the business. Joule Assistants understand organizations deeply and can automate complex tasks within and across functions, freeing employees to address more strategic work.

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Joule Work mobile app
General availability

Employees who use 麻豆原创 on the go can rely on the Joule Work mobile app to interact with 麻豆原创 applications in natural language on their smartphones or tablets. Joule is integrated directly into the app, so a simple chat can surface the latest figures, help complete approvals or maintenance tasks, and support work across areas such as sales, HR, and supply chain processes without having to navigate multiple mobile apps. On iPhone and iPad, users can even start by saying 鈥淗ey Siri, ask Joule in Joule Work,鈥� then speak their question, which is passed straight to Joule for a response. This gives organizations a single, mobile-enabled entry point to Joule capabilities and lets employees gain insights and act on tasks across their 麻豆原创 solutions using everyday language.

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Voice for Joule
麻豆原创 Early Adopter Care program (registrations closed)

A new partnership with LiveKit delivers intelligent voice for Joule, extending the experience beyond the keyboard and into settings where work happens. This partnership helps advance 麻豆原创’s vision for the Autonomous Enterprise. With LiveKit, 麻豆原创 customers can use real-time voice capabilities in Joule and access reliable, always-on conversational AI. This brings voice AI to a full range of roles, devices, and environments, putting Joule within reach of employees whose work is done away from a keyboard.

Enhancements for Joule
Multi-system support for 麻豆原创 S/4HANA Cloud Editions

Joule now supports connecting multiple 麻豆原创 S/4HANA Cloud Private Edition systems or clients and multiple 麻豆原创 S/4HANA Cloud Public Edition systems within a single Joule formation.

Work seamlessly across different 麻豆原创 S/4HANA environments through one unified Joule interface, increasing flexibility and efficiency for organizations operating multiple systems. Administrators enable this feature by configuring system-specific destinations with naming conventions, including additional systems in the Joule formation via System Landscape, and mapping system identifiers in the Joule Admin Center.

Developers can build custom capabilities that leverage data and functionality from multiple back-end systems. Business users access and execute processes across all connected systems naturally within their workflow.

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Autonomous SCM

麻豆原创 Digital Manufacturing, AI-assisted production engineering
General availability

Production engineers can analyze error logs to identify root causes and generate resolution instructions for production processes using 麻豆原创 Digital Manufacturing. The feature also enables engineers to extend production processes via script tasks generated based on natural language input.

Organizations can reduce error analysis time for production process errors by 20%, reduce error analysis time for connectivity errors by 20%, and cut the time to handle a production process or connectivity error from 4.5 to 3.6 hours — while improving operating time from 92% to 92.92%.

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

Quality managers can generate clearer and more structured initial descriptions of complex issues using 麻豆原创 Digital Manufacturing. By reducing bias and subjective language, a more balanced and factual representation of the problem at hand is created. Users can also refine and rephrase initial rough descriptions, facilitating more effective follow-up and thorough investigation, and translate descriptions into different languages.

This offers organizations an up to five percent improvement in the efficiency of quality engineers during issue handling and resolution, and an up to 10% reduction in errors during problem handling.

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Autonomous Finance

Project Billing Price Verification Agent
Beta release

Billing specialists can quickly identify mismatches between agreed prices and billing amounts using the Project Billing Price Verification Agent in the manage project billing application of 麻豆原创 S/4HANA Cloud Public Edition.

The agent identifies the relevant contracts and statements of work for the related customer project, extracts key pricing data, and compares them with the values in the project billing request. It highlights discrepancies, provides context, and suggests corrective actions.

Organizations can reduce time spent resolving price discrepancies by 75%, cut revenue leakage from undetected incorrect billing by 75%, and improve cash flow while reducing days sales outstanding by fewer billing cycle delays.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted localized business data management
General availability

Accounts receivable managers can access and explore localized financial and logistics data through Joule using natural language, without leaving their daily workflows. The capability enables users to run complex reports using natural language instead of manual selection screens, and instantly filter, navigate, and explore results with AI-supported context awareness. This way, finance teams can reduce the amount of training effort required and increase productivity and confidence across the organization.

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Autonomous Spend

Expense Automation Agent
General availability

Expense Automation Agent helps employees who submit business trip expenses by creating a first draft of their expense reports. It automatically collects and adds transactions, fills in relevant fields using contextual information and past behavior, and lets employees quickly review and adjust before submission. Customers can reduce manual data entry, shorten report completion time by up to 30%, and allow employees to focus more on their core work.

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麻豆原创 Ariba Contracts, AI-assisted contract creation from documents and prompts
General availability

Contract managers who create and manage large volumes of agreements can use AI鈥慳ssisted contract creation from prompts to start new contracts more efficiently. The feature lets users enter a simple natural-language prompt directly in the contract creation flow, then proposes contract header fields in seconds for review and confirmation before finalization. Organizations can reduce the effort required to initiate contracts, provide a guided in鈥慶ontext experience, and build a scalable foundation for future AI capabilities while maintaining clear human oversight of each contract.

麻豆原创 Fieldglass, AI-assisted SOW worker role recommendations
General availability

Procurement specialists who manage statements of work can now define suitable worker roles more quickly. This feature applies generative AI to the SOW context, including scope, outcomes, and timelines, to propose relevant roles that users can review and refine. Organizations benefit from faster, more consistent SOW authoring, improved fit鈥憈o鈥憇cope, and clearer, better-governed worker role definitions.

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麻豆原创 Ariba Invoicing, AI-assisted multi-model data extraction
General availability

Procurement and accounts payable teams working in 麻豆原创 Ariba Invoicing can rely on multi鈥憁odel data extraction to capture invoice information more accurately. The feature leverages the latest large language models in the content extraction service to interpret and extract key invoice data, enabling a smoother capture process. Organizations gain a more reliable and efficient invoice processing experience, with improved data quality that helps reduce manual corrections and downstream errors.

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Concur Travel, AI-assisted policy rule generator
麻豆原创 Early Adopter Care

Travel program administrators who manage Concur Travel policies can set up and adjust travel rules more efficiently with the policy rule generator. By pasting existing policy text into an AI-based rule generator, they can automatically produce multiple rule classes and rules in a single step, then apply them via a guided wizard. Organizations save time on policy implementation, reduce configuration errors, and promote more consistent, compliant travel policies across their programs.

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Autonomous CX

Order Reliability Agent
Beta release

The Order Reliability Agent helps customer service and order management teams stay on top of order issues consistently. The agent continuously monitors orders in 麻豆原创 Order Management Services, detects risks such as failures or delays, and either takes automated corrective action or presents clear recommendations and root-cause insights for staff to review. Companies can cut the time spent analyzing and handling exceptional orders by around half. The agent can also reduce customer churn related to fulfillment problems by about 20%, helping create a more reliable order experience.

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

Key account managers who plan trade promotions in 麻豆原创 Revenue Growth Management can set up promotions more quickly. When they enter a promotion name in the relevant account context, the system proposes key details such as dates, promotion type, duration, and sell鈥慽n timing based on master data, historical promotions, and past user edits. Organizations can shorten promotion setup time by up to 75% and reduce data鈥慹ntry errors and rework by around 30%, improving both efficiency and consistency in promotion planning.

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麻豆原创 Revenue Growth Management, AI-assisted deal sheet generation
General availability

Key account managers can quickly turn promotion data into retailer-ready deal sheets. Starting from a single promotion, the feature fills in system-of-record fields, applies appropriate PDF or Excel templates, and checks that required information is present before the document is created. This helps organizations produce consistent, audit-ready deal sheets in seconds, reduce formatting and data-entry errors, and give account teams more time to focus on customer negotiations rather than document preparation.

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Joule with 麻豆原创 Order Management Services
Beta release

Operations managers and order management teams using 麻豆原创 Order Management Services can rely on Joule to handle everyday operational questions and tasks through simple natural language. By enabling conversational access to key data and actions across areas such as order processing, orchestration, sourcing, availability, returns, and flows, Joule provides real-time, role-aware guidance directly in the flow of work. Organizations benefit from faster access to relevant transactions and insights, can act earlier to prevent issues from escalating, and support smarter, more timely decisions that save both time and operational cost.

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麻豆原创 Engagement Cloud, email campaign duplication
麻豆原创 Early Adopter Care program

Marketing teams can duplicate existing email campaigns to speed up everyday execution. When a marketer copies a previous campaign, email campaign duplication carries over layout, branding, and technical settings, so they only need to update content such as copy or offers. This helps organizations reduce campaign setup time, keep branding and formatting consistent, and limit repetitive configuration work and related errors across channels.

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麻豆原创 Business AI Platform

Build

Joule Studio
麻豆原创 Early Adopter Care

The new Joule Studio gives product teams, architects, and developers a single place to extend, build, and integrate AI experiences from business intent through to production-ready solutions. It starts from the outcomes you want to achieve, uses your own processes and data for context, and connects out of the box across your application landscape. At the same time, it can generate product requirements and technical specifications from your company-specific context, apply eval-based, data-driven guardrails to AI coding assistants under 麻豆原创-managed enterprise controls, and remain open so you can work with third-party or 麻豆原创 models in the development environment that fits your needs.

There will be a migration path from the original Joule Studio to the new version to help customers transition without disruption.

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麻豆原创 S/4HANA custom code migration agent
General availability

ABAP developers and migration teams moving from 麻豆原创 ECC to 麻豆原创 S/4HANA can use the 麻豆原创 S/4HANA custom code migration agent to automate the complex, time-consuming process of migrating custom ABAP code from 麻豆原创 ECC to 麻豆原创 S/4HANA. Delivered as an agentic AI capability in 麻豆原创 Joule for Developers, ABAP AI, the agent runs 麻豆原创 S/4HANA readiness checks via ABAP test cockpit across entire custom code packages, interprets the findings, categorizes issues, and applies a mix of deterministic quick fixes and AI-based code changes with confidence scores, while recording all updates in transport requests for full traceability. High-confidence fixes are applied automatically, and lower-confidence proposals are added as comments for developer review, so teams retain control over final code quality while spending far less time on object-by-object analysis, freeing capacity for higher-value design decisions and overall migration governance.

and .

Contextualize and Reason

Generative AI hub, enhancements

The generative AI hub in the 麻豆原创 AI Core infrastructure integrates with hyperscaler-agnostic operations to improve accuracy and support enterprise-wide adoption of business AI.

Batch API enabling processing of high鈥憊olume foundational model (FM) workloads
Developers and platform teams working with 麻豆原创 AI Core can use the batch API to process high-volume foundational model workloads more efficiently. By submitting large collections of non-urgent AI requests as a single input file, they can run jobs asynchronously in the background. At the same time, 麻豆原创 AI Core writes results to an object store, ensuring real-time, fast, and responsive user experiences. This improves scalability for high-volume processing, simplifies the developer experience across different models and providers, and ensures fair, predictable throughput so that large jobs do not block smaller ones.

Inference observability service: centralized logging and feedback for generative AI workloads
Teams running generative AI workloads on 麻豆原创 AI Core can use the inference observability service to monitor, analyze, and systematically improve model outputs. The service centrally records prompts, responses, and key context with controlled overhead, lets developers and users rate the quality of each response, and attaches lightweight feedback. It also supports labels and filters so interactions can be easily discovered and exported as datasets for fine鈥憈uning, prompt engineering, and benchmarking. Organizations gain standardized transparency into prompt and response quality, reduce costs and effort by replacing ad hoc logging with a unified, compliant feedback channel, and accelerate iterative improvement using structured inference data stored in S3 or metadata-only mode, and managed via REST APIs for labels, feedback, and record retrieval.

Speech-to-speech
The availability of speech鈥憈o鈥憇peech (S2S) recognition helps agent and app developers build natural, end鈥憈o鈥慹nd voice experiences into 麻豆原创 applications.

New models available
New models are supported, including Gemini 3.1 Flash Lite, Claude Opus 4.7, GPT Realtime and Mistral Small, GPT 5.4, GPT 5.4-nano, and GPT 5.3-Codex.

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麻豆原创 Joule for Consultants, enhancements

Custom knowledge grounding connects 麻豆原创 Joule for Consultants to a separate grounding service that indexes organizational content via 麻豆原创 AI Core. It enables Joule to securely index and reference an organization鈥檚 methodologies, policies, templates, and delivery standards alongside 麻豆原创鈥慶urated knowledge. By grounding responses in company鈥憇pecific documentation, consultants can receive more accurate guidance that aligns with established ways of working across projects and engagements.

Expert workspace introduces personalized 鈥渆xperts鈥� that help tailor guidance for specific projects, domains, or workstreams. Context is retained across conversations, so users can switch between initiatives while preserving project-specific knowledge.

and .

麻豆原创 Document AI enhancements

Model selection
This new feature allows you to choose the large language model (LLM) used for document processing. The Default LLM reflects the best-performing model at any given time, while additional models such as Gemini 2.5 Flash and GPT-5 are also available. The list of supported models is updated frequently to ensure access to the latest advancements.

New standard document types
麻豆原创 Document AI workspace and OData V4 APIs now support three additional standard document types: learning certificate, order confirmation, and traffic violation notice. This expands the range of business documents that can be processed out of the box, reducing the need for custom configurations.

Configuration of document-level confidence ranges
麻豆原创 Document AI now supports configurable document-level confidence thresholds, making it easier to assess extraction quality at a glance. Custom confidence ranges 鈥� low, medium, and high 鈥� can be defined on the configurations tab of a schema version. When documents are processed, the overall confidence score is displayed in the document header with color-coding: red for low, orange for medium, and green for high confidence.

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麻豆原创 Domain Models

are AI models trained on 麻豆原创 domain knowledge, including code, data, metadata, business processes, architectural knowledge, and documentation. When customers initiate a query or want to create code, the models are designed to provide results firmly grounded in the 麻豆原创 context instead of relying on generic internet knowledge. Combined with context graphs and agents, the models bring deep 麻豆原创 knowledge to Joule, Joule Studio, Joule Agents, and 麻豆原创 applications.

麻豆原创 Domain Models will help:

• Create custom extensions in 麻豆原创 S/4HANA Cloud Public Edition and 麻豆原创 Ariba: Developers in Joule Studio can use specialized models for 麻豆原创 S/4HANA and 麻豆原创 Ariba to understand and generate clean core-compliant code from natural language.
• Query information in 麻豆原创 S/4HANA Cloud Public Edition and 麻豆原创 Ariba: Customers can use natural-language prompts in Joule to access customer data that is grounded in the underlying data models and the business context.

These capabilities will help create clean core extensions while preserving 麻豆原创 standards and governance. 麻豆原创 Domain Models are running under the hood of Joule and Joule Studio and are not directly exposed to customers.

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Govern

麻豆原创 AI Agent Hub enhancements

麻豆原创 AI Agent Hub gives organizations a single control pane for all AI agents, LLMs, and MCP servers across the enterprise. Featuring automated AI asset discovery across major platforms, including Microsoft, Google, AWS, and now ServiceNow and 麻豆原创 AI Core, alongside structured governance assessments and a verification badge that integrates directly with runtime solutions to control which agents and MCP servers are approved for use.

Looking ahead, we will expand into runtime observability and governance, identity and access control, agent-in-process mining, and workforce impact mapping to make the AI Agent Hub the central command center for AI governance at scale.

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Process Consulting Agent
General availability

Process owners, analysts, and operational leaders can turn process data into clear, practical insights without needing specialist analytics skills with the Process Consulting Agent. Users can ask questions in natural language, and the agent retrieves and analyzes relevant process information through a multi鈥慳gent system, returning structured findings along with suggested next steps. Organizations can cut the time spent searching complex data per artifact by up to 90% and reduce the effort to analyze, design, model, and monitor processes by around five percent, helping teams move more quickly from insight to action.

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Enterprise Content Research Agent
General availability

Enterprise architects and portfolio managers can quickly find and understand architectural information through the Enterprise Content Research Agent in 麻豆原创 LeanIX. By querying inventory data and related documentation across sources such as 麻豆原创 LeanIX, Confluence, and SharePoint, the agent highlights missing fields, supports gap analysis, and helps keep records complete and consistent, while leveraging MCP Server tools as needed. This reduces the time spent on informational searches and navigation, simplifies data management tasks, and supports stronger governance over architecture data across the landscape.

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WalkMe solutions, AI knowledge indexing
General availability

Digital adoption and enablement teams can use AI knowledge indexing to make internal documentation easily available to WalkMe鈥檚 AI services in a controlled way. The feature processes connected knowledge sources, such as web pages and files, extracts text content, and converts it into secure vector embeddings, enabling WalkMe鈥檚 contextual AI assistance to ground guidance in company policies, wikis, and procedures rather than generic models. Organizations can improve real-time compliance outcomes and see a 21% increase in procurement policy adherence, while giving employees faster, policy-aligned answers directly in their workflows.

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WalkMe solutions, AI knowledge referencing
General availability

Digital adoption teams and application owners receive app guidance that aligns with their company鈥檚 policies and standards with WalkMe鈥檚 AI knowledge referencing. When certain conditions are met, such as editing a specific field or completing a form, the feature retrieves relevant content from connected internal documentation so tools like AI SmartTips or chat can compare user input with best practices and provide tailored feedback. This allows organizations to anchor AI assistance in trusted company information and help employees access the right policy or governance details when needed.

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WalkMe solutions, pinned AI
General availability

Operations, HR, finance, and other business teams now benefit from on-screen assistance exactly where they enter data or complete tasks, using WalkMe鈥檚 pinned AI. By attaching AI smart tips to input fields and AI Launchers to specific elements, the feature provides contextual guidance in place, grounded in company knowledge sources, so users can continue their work without switching applications. Organizations can improve data quality across key forms and workflows, reduce errors and rework, and see measurable gains such as a 41% improvement in data quality.

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WalkMe solutions, on-demand AI
麻豆原创 Early Adopter Care program

Employees working across line-of-business applications can turn to WalkMe鈥檚 on-demand AI for quick answers or step-by-step support without leaving their current screen. Through a conversational in-app menu that travels with users across applications, they can ask questions, retrieve company knowledge, and trigger automations or Smart Walk-Thrus, keeping guidance and execution closely connected. Organizations benefit from faster access to trusted information and a measurable impact on quality, including up to a 41% reduction in time spent correcting ERP-related business tasks.

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麻豆原创 LeanIX solutions, AI-assisted enterprise architecture decision management
General availability

Enterprise architects and architecture review boards get faster, more consistent decisions with enterprise architecture decision management in 麻豆原创 LeanIX solutions. By providing context, such as transformation diagrams or landscape changes, they can ask the AI to generate a draft architecture decision entry that includes the relevant background, decision, and implications for stakeholders to review and approve. This reduces manual data extraction and authoring effort, streamlines collaboration on approvals, and helps ensure architecture decisions are documented and concluded in a timely, traceable way.

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麻豆原创 LeanIX solutions, AI-assisted fact sheet calculations
General availability

Enterprise architects and workspace admins using AI-assisted fact sheet field calculations in 麻豆原创 LeanIX solutions can quickly turn plain-language business rules into working calculations. When they describe the rule they need, the feature generates readable, commented code that is aware of their fact sheet types, fields, relations, and enums. Hence, calculations align with the actual workspace configuration. This helps teams move from a business question to a usable metric in minutes, increase self-service configuration, reduce reliance on JavaScript skills, and speed up the delivery and maintenance of calculated fields that downstream reports and views depend on.

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麻豆原创 LeanIX solutions, AI-assisted automation creation
General availability

Enterprise architects and workspace admins can transform plain-English workflow descriptions into working automations with AI-assisted automation creation in 麻豆原创 LeanIX solutions. When they describe the review, update, or governance flow they need, the feature generates the appropriate triggers, conditions, and actions with field mappings aligned to the current workspace configuration. This lets teams build and scale automations themselves, increasing EA productivity, reducing reliance on technical experts, and making it easier to keep key processes such as onboarding workflows and lifecycle checkpoints consistently automated.

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麻豆原创 Cloud ALM, AI-assisted document summary
General availability

Document summary helps project teams and engineers understand long documents more quickly. Within the documents application, users can trigger an AI-generated summary, review and edit it in a separate window, and then apply it as a persistent summary section in the document. This shortens the time spent manually reading and extracting key points, supports faster comprehension of complex engineering content, and enables quicker decisions without leaving the document workflow.

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麻豆原创 Signavio solutions, AI-assisted context analyzer, text-to-event matching, and sentiment analysis
General availability

The context analyzer helps process owners and analysts match free text with process objects, such as sales orders or purchase requisitions, to the corresponding process events in event logs. The feature links free-text records such as survey responses, feedback, comments, and tickets to the corresponding process events, so qualitative experience data appears alongside operational logs. This enriches process mining with unstructured text, reduces manual mapping work, and improves process analysis accuracy by around 30%, helping teams pinpoint bottlenecks and experience issues more effectively.

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Jonathan von Rueden is chief AI officer for 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.

At the same time, the research also makes clear that ambition and vision are not enough.

The orchestration gap

Nearly half of the executives surveyed by IDC recognize the substantial benefits of end-to-end orchestration鈥攂ut many have yet to take decisive action. The true challenge lies not in understanding its value, but in bridging the gap between strategic intent and effective execution.

IDC surveyed C-level leaders across industries and regions. The message was consistent. Leaders understand the destination, but they want clearer guidance on the blueprint to execution. As the IDC white paper said, 鈥淎 majority of executives see value in an orchestrated supply chain and believe they must move in that direction, yet the precise steps are unclear, and they are not sure where best to start鈥攖hey need help.鈥�

That tension is familiar. Many organizations have made progress in operational silos, but far fewer have connected design, planning, procurement, manufacturing, logistics, and service into a truly coordinated operating model.

What orchestration really means

An orchestrated supply chain connects people, processes, and technology to provide agility and deliver continuous improvement, despite persistent disruption. Agentic AI is fundamentally reshaping orchestration, enabling systems to analyze, decide, and coordinate across functions in real time. From sourcing and procurement to planning, manufacturing, logistics, and delivery, the focus shifts from optimizing individual functions to achieving enterprise-wide alignment.

Traditional linear supply chain models were built for a more predictable world. Today鈥檚 reality is different. Geopolitical uncertainty, AI-driven disruption, climate pressures, regulatory complexity, and rising customer expectations are constant. Decisions made in one area now ripple quickly across the rest of the supply chain.

Orchestration addresses this reality by establishing a shared foundation of contextually relevant information, designing processes to operate together, and enabling systems that support end-to-end decision-making and execution. Technology plays a critical role, but orchestration ultimately depends on organizational alignment: clear roles, shared metrics, and coordinated processes. Instead of optimizing planning or execution in isolation, orchestration evaluates trade-offs based on their impact on the entire supply chain and the broader business.

Different leaders, shared outcomes

The IDC research also highlights how perspectives on orchestration vary by role. COOs focus on enterprise performance, CSCOs balance transformation with operational demands, and CPOs emphasize cost and risk exposure in direct materials, including mitigation strategies. Orchestration must deliver value across these perspectives while maintaining a unified, end-to-end view.

This diversity of perspective reinforces why orchestration matters. Success comes from respecting functional priorities without allowing silos to drive disconnected decisions, enabling coordinated decision-making that optimizes the whole, not just the parts.

Efficiency and agility, not trade-offs

Many executives perceive a trade-off between efficiency and preparedness, but orchestration changes the equation. With integrated data, shared context, and agile tools, companies can respond faster, reduce disruption response times, and make informed trade-offs鈥攄emonstrating that agility and efficiency can reinforce each other rather than compete.

As one procurement leader told in the IDC white paper, 鈥淲e have to be able to be both resilient and efficient, or at least be able to make informed trade-offs quickly. Right now, we have neither the necessary supply chain integration nor agile enough tools to be able to do that.鈥� Without integrated supply chains and shared context, that balance is difficult to achieve. When companies can identify issues earlier and respond faster, recovery times shrink, translating into lower costs, less expediting, and more reliable customer service.

The role of agentic AI

Agentic AI is emerging as a practical, transformational path to supply chain orchestration. AI-driven agents can monitor signals, evaluate scenarios, and recommend or initiate actions within defined guardrails. Across 麻豆原创 customer environments, AI delivers value in supplier onboarding, predictive maintenance, and rapid rebalancing of inventory or capacity. Leaders generally prefer AI as an advisor rather than a fully autonomous decision-maker, reflecting the continued importance of human judgment, accountability, and experience. Orchestration works best when AI strengthens decision-making while keeping people firmly in the loop.

Data, platforms, and the role of 麻豆原创 Supply Chain Management

Effective orchestration requires more than connectivity, it depends on harmonized data, coordinated processes, and contextual intelligence embedded where work happens. As supply chains extend across multi-tier supplier networks, logistics partners, and service providers, the challenge is no longer access to data, but making data usable, contextual, and actionable at scale.

The IDC research underscores that true end-to-end orchestration must span both internal operations and external ecosystems. Much of the most critical information鈥攔isk signals, capacity constraints, execution status鈥攍ives outside the enterprise. Without a common data foundation, organizations struggle to move from insight to action.

This is where plays a distinct role. 麻豆原创 brings together an end-to-end portfolio of supply chain applications, deeply integrated with ERP and line-of-business systems, and connected externally through . Planning, sourcing and procurement, manufacturing, logistics, and service operate as a coordinated system rather than isolated domains.

At the data layer, provides a normalized foundation that can harmonize operational, transactional, and network data. This shared context provides visibility, analytics, and AI. On top of it, embedded and extensible AI鈥攊ncluding agentic AI and Joule鈥攕upports orchestrated decision-making, helping to accelerate time to decision and time to recovery while keeping people engaged and in control.

Turning priority into practice

The move toward orchestrated supply chains is well underway, but progress remains uneven. Only a minority of organizations consider themselves close to full, end-to-end orchestration. Technology alone is not the constraint. Data readiness, clarity of outcomes, organizational alignment, and change management matter just as much.

Leading organizations start with clear objectives, invest in people alongside platforms, and build pragmatic road maps that prioritize time to value. Orchestration is not a single project. It is a progression that evolves as capabilities mature.

At 麻豆原创, our focus is on making orchestration practical and accessible. Through 麻豆原创 Supply Chain Management solutions and 麻豆原创 Business Network, we help organizations align teams, connect processes, integrate partners, and embed AI into core supply chain activities鈥攅nabling better decisions, faster execution, and sustained enterprise impact in a constantly changing world.

Hagen Heubach is chief marketing officer for Supply Chain Management at 麻豆原创.

IDC White Paper, sponsored by 麻豆原创, Orchestrating the End-to-End Supply Chain: Strategic Priority, Practical Reality, #US54385326-WP, April 2026

With the new data center in India complementing existing ones in Europe, the U.S., and Saudi Arabia, 麻豆原创 has dramatically strengthened the data federation capabilities of , linking together the procurement processes of businesses and their trading partners across the globe.

With this milestone, 麻豆原创 has delivered on a crucial promise made to a highly consequential set of customers in the Indian subcontinent and beyond. Later this year, the India data center will extend data federation capabilities for as well.

But what is data federation? And why is it so consequential for organizations in India and elsewhere?

Data federation assembles a unified view of data from disparate sources without physically moving or copying it. Trading partners can thus exchange goods and services across international borders while the data underlying those transactions remains stationary. By preserving the integrity of data where it resides, federation facilitates mission-critical operational processes on a global scale while achieving regulatory consistency with compliance requirements that arise at a national level. For example, if a buyer鈥檚 data resides in 麻豆原创 Business Network鈥檚 India data center but its supplier鈥檚 data sits in the U.S. data center, federation provides both parties with access to each other鈥檚 data without impinging on either nation鈥檚 policies governing the residency of that data. This becomes especially important as new legislation gathers pace around the world in response to rising concerns over individual privacy, national security and commercial sectors considered sensitive.

Enabled by , 麻豆原创 Business Network and its data federation capabilities are now built on the kind of modern, connected foundation required for the next era of cloud-based commerce. Beyond improved scale, resilience, and regional compliance, 麻豆原创 Business Technology Platform helps create the basis for agentic artificial intelligence, automation, richer analytics, stronger security, open extensibility, and seamless cross-麻豆原创 workflows and processes. The result is a network that can not only connect partners globally but also help customers to conduct business more intelligently, respond faster to change, and drive greater value from every interaction across procurement, supply chain, logistics, asset collaboration, and working capital management.

To collaborate with their trading partners on these and other core business processes, companies conducting business in India require a cloud-based platform that provides secure infrastructure for building resilient domestic supply chains while maintaining global connectivity, thus maintaining sensitive procurement, supplier, and manufacturing data within Indian jurisdiction. 麻豆原创 Business Network furthers these objectives with our newly launched data center in Mumbai, where data is localized in a manner compliant with (MeitY) guidelines, with a MeitY-empaneled cloud service provider.

While supporting compliance within an increasingly complex regulatory environment, data federation offers numerous technical advantages as well, especially in hybrid or multi-cloud environments. These benefits include cost efficiency, unified governance and security, and faster response times compared to accessing servers in distant regions. Yet the most valuable competitive advantage provided by data federation may be the most elusive: peace of mind for business leaders amid the ever-looming threat to supply chains posed by disruption.

To counter that threat鈥攚hether arising from geopolitical conflict, labor unrest, financial shock, natural disaster, or other upheaval鈥攂usinesses are turning increasingly to data federation and other cloud-based solutions to extend visibility and instill resilience across their operations and those of their trading partners. With the opening of our new data center in Mumbai, we are incredibly excited to strengthen our relationships with customers throughout India and accelerate the value available to them from 麻豆原创 Business Network.

For information on 麻豆原创 Supply Chain Management and how 麻豆原创 solutions are equipping enterprises with the AI capabilities needed to instill resilience, counter disruption, and foster collaboration, visit and .

J枚rn Keller is executive vice president and chief product officer of 麻豆原创 Business Network.

As discussed in a new whitepaper, , this perspective is grounded in interviews with supply chain leaders across six industries: automotive electronics and software, agricultural equipment, chemicals, global technology, automotive supply, and home appliances.

Their experiences reveal where companies are investing, where adoption challenges remain, and where the next wave of value is likely to emerge.

Supply chains are entering an era of permanent disruption

Four structural forces are reshaping global supply chains simultaneously: geopolitical instability, economic pressure, demographic shifts, and accelerated digital transformation.

Since 2017, relative to trade among closer partners, signaling growing fragmentation in global commerce. , while labor shortages and digital skill gaps continue to constrain operations.

Europe alone could face by 2028, and 63% of companies cite .

Together, these pressures are pushing supply chains beyond the limits of the traditional 鈥減lan-source-make-deliver鈥� model.

Companies are shifting from optimization to AI-enabled orchestration

Supply chains are increasingly viewed as strategic levers for resilience, service differentiation, and competitive advantage.

Across all six companies interviewed, each is investing in at least three forward-looking AI use cases in planning alone.

• A leading agricultural equipment company has deployed more than 1,000 AI agents to support orchestration, scenario planning, and value chain visibility. A global chemicals company is embedding AI across planning and scenario management while emphasizing explainability and trust.
• A home appliance company is applying AI selectively to improve forecasting, transport optimization, warehouse safety, and logistics costs.

The common theme: organizations are redesigning how the enterprise senses, decides, and acts.

Resilience is now defined by decision velocity

In today鈥檚 fragmented environment, resilience is no longer about static buffers. It is about how quickly companies can convert disruption signals into coordinated action across sourcing, production, planning, and logistics.

• An automotive electronics and software company centralized electronics ordering across roughly 30 plants and redesigned crisis-management processes, reducing disruption response times by approximately 95%.
• A global technology company adopted a regional 鈥渢wo-leg鈥� supply chain model, using inventory strategically to respond faster to disruptions.

The emerging differentiator is not forecast accuracy alone, but the speed from disruption detection to execution. Visibility remains important, but visibility without coordinated action is no longer enough.

Trust and governance are the biggest barriers to scaling AI

Despite rapid interest, . The challenge is not model accuracy alone; it is trust, explainability, fragmented systems, and manual overrides.

• One global chemicals company found that scaling AI depended less on technical performance and more on whether users could understand and trust the outputs. This led to stronger human-in-the-loop governance and progressive autonomy thresholds.
• A major automotive electronics company requires transparent, traceable AI reasoning before planners rely on AI-generated recommendations.

The path to autonomy will be incremental: companies will first augment human decision-making, then automate routine and semi-structured decisions as governance, trust, and data maturity improve.

The next frontier is the Autonomous Enterprise

The Autonomous Enterprise is an operating model where AI workflows, contextual business data, and embedded governance work together to anticipate disruption, coordinate action, and continuously improve performance.

The shift is moving from isolated copilots to coordinated agent-to-agent workflows spanning the supply chain.

In autonomous production environments, supplier reliability agents can monitor vendor risk while workforce orchestration agents align labor capacity with demand. Procurement agents execute sourcing decisions, and production planning agents dynamically rebalance schedules in response to changing conditions.

A similar pattern is emerging in asset management, where alert-processing, maintenance, warehouse replenishment, and goods-movement agents collaborate to resolve operational issues with minimal human intervention.

The business impact is significant. Agentic AI has by 20 to 30%, , and helped .

Collectively, these improvements mark the transition from reactive supply chains to systems that can increasingly anticipate, decide, and execute autonomously.

Building the autonomous supply chain

Capturing this opportunity requires three capabilities that remain fragmented in many organizations today:

• Organizational intelligence: The ability to detect patterns, anticipate risks, and reason across constraints
• Contextual data: Trusted operational data, business rules, workflows, and policies that ground AI decisions in enterprise reality
• Embedded execution: Integrating intelligence directly into workflows so actions can move from recommendation to execution without manual intervention

This creates a virtuous cycle: better data improves decisions, better decisions improve processes, and improved processes generate richer operational data over time.

Importantly, companies do not need to rebuild the enterprise from scratch. Deterministic systems of record remain essential for control, compliance, and auditability. The real transformation lies in rewiring how decisions are made and governed.

Organizations moving fastest are focusing first on high-value, high-frequency decisions such as forecasting, inventory optimization, disruption sensing, transport planning, procurement workflows, maintenance, and customer-service resolution.

The bottom line

The future of supply chain management will not be defined by more digital tools alone. It will be defined by the ability to operate the supply chain as a connected, adaptive, and increasingly autonomous system.

For leaders who move first, supply chain will evolve from a cost-management function into a competitive differentiator, enabling faster time to market, stronger service levels, and greater resilience. The organizations that lead will not be those running the most AI pilots. They will be the ones using AI to redesign how the enterprise senses, decides, and acts across the end-to-end supply chain.

For more information about Autonomous Supply Chain Management, download the white paper, .

Hagen Heubach is chief marketing officer for Supply Chain Management at 麻豆原创.

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Grupo UMA, a leading motorcycle assembler and distributor, is accelerating manufacturing growth across Colombia and Central America with 麻豆原创 Cloud ERP Private.

Operating in multiple countries and serving thousands of riders every month, the company needed standardized, automated, and data鈥慸riven processes to support expansion while maintaining quality and customer experience. By implementing 麻豆原创 Cloud ERP Private, Grupo UMA streamlined core business processes across finance, production, and logistics, replacing manual work with real鈥憈ime insights and end鈥憈o鈥慹nd process integration. Global operating models, automated workflows, and transparent cost visibility now enable faster decision鈥憁aking and scalable growth across the region. The impact: production increased from approximately 11,000 to 17,000 motorcycles per month, with a clear path to 20,000. Across markets including Guatemala, El Salvador, Costa Rica, Honduras, Nicaragua, and Colombia, Grupo UMA is improving supply chain efficiency, optimizing production capacity, and delivering consistent quality with solutions such as 麻豆原创 Extended Warehouse Management (麻豆原创 EWM). Beyond operations, teams are shifting from manual, operational work to a more strategic, innovation鈥慸riven, and analytics鈥慺ocused approach鈥攈elping the organization evolve into a truly data鈥慸riven enterprise.

Discover how 麻豆原创 helps manufacturers in Latin America scale faster, operate smarter, and deliver better customer experiences with cloud ERP and read the full customer story on the 麻豆原创 News Center.

Workforce scarcity impacting global logistics operations, logistics corridors becoming tools in geopolitical conflicts, and continuously rising transportation costs all point to the same reality:聽Future-proofing logistics is no longer a strategic choice, but the critical tipping point that separates those who will rise from those who will fall in an increasingly unforgiving global economy.

Modernizing logistics is no longer about 鈥渋f鈥� but how fast and how far

Traditional logistics systems were designed primarily for efficiency. Today鈥檚 supply chains, however, are more complex and exposed to even more risk, requiring resilience, agility, and smarter decision鈥憁aking across warehousing and transportation operations.

麻豆原创ure is constant and from multiple directions, including geopolitical tensions, economic volatility, stringent government regulations, and rising customer expectations. The core challenge is no longer reacting to individual disruptions but overcoming constant firefighting. Leaders are seeking a clear path toward a more agile and future鈥憆eady logistics strategy. Two questions sit at the center of this challenge:聽How fast do logistics operations have to change? And how complex are the operations that must be supported?

Answering these questions starts with examining the technological foundations that power your current logistics operations. Long-standing solutions鈥攕uch as 麻豆原创 ERP Central Component modules for logistics execution – warehouse management (LE-WM) and logistics execution – transportation (LE-TRA) as well as 麻豆原创 Extended Warehouse Management and 麻豆原创 Transportation Management鈥攈ave served reliably for decades, yet 麻豆原创 continues to evolve to serve today’s demands for real-time adaptability and scale.

麻豆原创鈥檚 logistics portfolio has supported customers across three decades and continues to evolve with adaptive, cloud-native, AI-driven platforms capable of learning, predicting, and orchestrating logistics processes autonomously, because that is what companies need to compete now and in the future.

The right journey depends on innovation speed, risk tolerance, operational complexity

Future鈥憄roofing logistics ultimately comes down to choosing the right modernization path. Every organization has a unique starting point, depending on how existing solutions have been implemented across the business. To choose the right next step, leaders need to understand the available options, determine what fits with the organization鈥檚 appetite for innovation, and assess the transformational impact on the team.

Gartner鈥檚 logistics complexity model, breaking down process complexity across five levels, can help when setting a transformation strategy.

Companies operating at levels one to three of Gartner鈥檚 model are typically characterized by manual or semi-automated processes, regional distribution, and lower complexity. These companies are best-suited for SaaS-native warehouse and/or transportation solutions that offer the implementation speed of standardized workflows, cloud qualities such as flexible, mobile interface, and advantages from improved scalability and lower TCO.

Organizations at levels four and five require warehouse automation for high volume distribution, multi-modal transportation, and orchestration across multiple ERP systems. These companies seek the benefit of dedicated cloud environments that offer a higher level of adaptation for more control over their operations and their solution landscape.

麻豆原创 offers different pathways to help businesses run and modernize across the span of operational complexity. Below are three journeys to guide strategic planning for modernization. Each journey can be aligned to high-level business ambitions, accounting for process complexity, innovation speed, and risk tolerance.

Journey 1: Sustain temporary stability while preparing for modernization

Moving legacy 麻豆原创 ERP Central Component modules LE-WM and LE-TRA to 麻豆原创 S/4HANA for stockroom management keeps operations supported until 2040, offering more time to manage your transformation. This journey is about sustaining what works until you need to evolve. It is designed for organizations that need more time to move their decades-old warehousing solution into the future. This approach, rooted in stockroom management, extends the life of a proven system without prematurely forcing change. It is a temporary but intentional holding pattern for conservative logistics strategies based on a firm foundation. Throughout this journey, 麻豆原创 Logistics Management can be the go-to solution when you are ready to move from stockroom management.

Journey 2a: Modernize logistics in controlled steps

For organizations that know modernization is essential but need to be mindful of organizational change management, this journey offers a stable path. It begins with moving on-premise 麻豆原创 ERP Central Component modules LE-WM and LE-TRA to 麻豆原创 S/4HANA Cloud, private edition, with basic warehouse management and transportation management capabilities, creating a modern foundation for future readiness. From there, companies can evolve their processes toward more advanced options as their needs grow (see journey 2b). This journey is best suited to businesses that want flexibility and control in their operations as well as in their change management. This journey also supports deeply integrated logistics that align with the RISE with 麻豆原创 journey.

Along this journey, if you find that your business complexity is manageable, 麻豆原创 Logistics Management can even be incorporated as the most modern, AI-native 麻豆原创 solution for logistics to complement your ongoing operations.

Journey 2b: Move large-scale logistics to the cloud

This journey supports organizations that need to manage highly specific processes, high-automation, and mission-critical logistics execution with one or multiple ERP systems. You can migrate from 麻豆原创 Extended Warehouse Management and 麻豆原创 Transportation Management to the cloud with 麻豆原创 S/4HANA Cloud for advanced extended warehouse and transportation management without losing depth or control. This path can also serve as a second step for advancing operations from basic to advanced 麻豆原创 S/4HANA Cloud in order to support growing business needs.

Journey 3: The modernization gamechanger for logistics

For innovation leaders ready to sprint ahead of the competition, this journey represents the direct path to the most modern logistics operating model. Companies move from on-premise 麻豆原创 ERP Central Component modules LE-WM and LE-TRA to AI-native聽, bringing together cloud delivery, embedded intelligence, and network connectivity in a single solution for warehousing and transportation.

This is the right path for businesses that want to standardize faster, simplify their landscape, and take advantage of continuous innovation. You gain a more connected and adaptive logistics model with built-in AI and a carrier network. Along this journey, you are setting the pace for modern supply chains.

Future of logistics: Cloud-first, AI at the core, modular by design

Logistics is accelerating into a new era, one defined by both efficiency and intelligent adaptability and autonomous orchestration. Embodied in its evolving logistics portfolio, 麻豆原创’s strategy offers a clear, flexible, and future-ready path for companies at every level of complexity.

Whether maintaining existing operations, maturing gradually as complexity increases, or leapfrogging to leading-edge capabilities, you can now compose and run your entire logistics operations on 麻豆原创. Basic to moderate complexity processes are supported with 麻豆原创 Logistics Management, and advanced and highly automated business with S/4HANA Cloud EWM and TM. By combining the two, you can design and achieve logistics networks to improve speed, agility, and resilience.

To explore which聽logistics聽journey fits your business best, don鈥檛聽miss our “Future of Supply Chain” conversation with 麻豆原创 executive聽Till聽Dengel:聽.

While expectations for reliable, on-time delivery remain high, organizations are navigating faster鈥慶hanging demand, more complex global networks, and increasing pressure on cost and working capital. And they鈥檙e looking for ways to turn insight into action more quickly and consistently across the supply chain.

麻豆原创 has been helping organizations build more connected and intelligent supply chains for over 50 years. At 麻豆原创 Connect in October, we introduced 麻豆原创 Supply Chain Orchestration, establishing a foundation for detecting issues, coordinating responses, and connecting execution across complex supply networks.

The innovations announced this week at 麻豆原创 Sapphire extend that vision further. By introducing a new set of AI-driven assistants and agents, we鈥檙e moving orchestration toward an autonomous operating model, where planning, manufacturing, logistics, and asset operations increasingly anticipate, coordinate, and resolve without manual intervention at every step.

AI grounded in real operations

AI delivers lasting value in supply chain management only when it is embedded where work actually happens. Autonomous agents do not operate independently of enterprise applications; they rely on deeply integrated processes and trusted data. Precision, compliance, and resilience depend on this foundation. Without it, AI does not scale or earn trust.

At 麻豆原创, the Autonomous Enterprise represents a vision for how organizations will run their businesses in the future: with insight, decision-making, and execution increasingly connected, while people remain firmly in control. Autonomous Supply Chain Management is a practical step toward that vision.

Autonomous Supply Chain Management reflects an evolution in how planning, execution, and operations work together. People define goals and priorities, assistants orchestrate activity across domains, and agents execute the work鈥攁ll within governed, end鈥憈o鈥慹nd processes.

At 麻豆原创 Sapphire, we鈥檙e introducing , enabled by new Joule Assistants and Industry AI scenarios that apply this model to daily operations across planning, manufacturing, logistics, engineering, and asset management. General availability will be phased throughout 2026, starting now.

Joule Assistants across the supply chain

Rather than disconnected AI tools, the following assistants will be embedded directly into core 麻豆原创 supply chain applications, where deep process knowledge, semantically rich business data, and enterprise鈥慻rade governance already exist.

Each will support a distinct area of responsibility while sharing context, data, and outcomes across the supply chain:

• Asset and Service Assistant: Changes how work gets detected and dispatched, turning signals and anomalies into action rather than queue items
• Business Network Assistant: Extends this coordination outward across suppliers, logistics providers, and service partners so execution doesn鈥檛 stall at the edges of the enterprise
• Logistics Assistant: Keeps warehouse and transportation execution moving as conditions change, coordinating agents rather than waiting for human handoffs at every step
• Manufacturing Assistant: Connects shop floor signals with broader operational context so teams can act on disruptions faster
• Planning Assistant: Helps planners stay ahead of exceptions and constraints without having to manually piece together signals from across the network
• Product Design Assistant: Helps engineering and manufacturing teams stay aligned as products evolve, surfacing the downstream implications of changes before they create rework or delays

From assistants to autonomous agents

In addition to these assistants, 麻豆原创 is delivering more than 60 purpose鈥慴uilt agents across supply chain processes. These agents are designed to sense events, analyze impact, and take guided action within defined business guardrails, helping coordinate execution while keeping people firmly in control.

In manufacturing, agents such as the Production Excellence Agent and Production Master Data Readiness Agent continuously monitor production, quality, and machine signals to detect issues early and keep routings and work instructions aligned with enterprise plans. In asset and service operations, the Asset Performance Alert Processing Agent and Technician Briefing Agent are designed to assess asset conditions, prioritize work, and increase first time fix rates, helping reduce downtime and improve responsiveness.

Beyond supply chain-specific scenarios, these assistants and agents will also extend into 麻豆原创’s cloud ERP environment, including , supporting 麻豆原创鈥檚 broader Autonomous Enterprise strategy. General availability will be phased through 2026, starting now.

Building on this foundation, 麻豆原创 Industry AI adds industry-specific intelligence that complements the core assistants. Rather than standalone features, Industry AI brings together purpose-built agents, process expertise, and business data to drive measurable outcomes. This value-led approach helps organizations apply AI in ways that reflect regulated requirements, complex production models, and asset-intensive operations 鈥� accelerating information across entire industry value chains.

People remain responsible for strategy, oversight, and the decisions that require judgement. What changes is how consistently high-volume, time-sensitive coordination happens across the supply chain.

Where this shows up in practice

The Autonomous Enterprise is our vision, and the innovations we鈥檝e announced at 麻豆原创 Sapphire are concrete steps that customers can build on within current 麻豆原创 environments. They are focused on addressing value leakage caused by fragmented handoffs, delayed decisions, and manual work.

In planning, new capabilities will connect commercial decisions directly with supply planning, linking promotion and pricing plans to inventory and replenishment to reduce stockouts, minimize write-offs, and improve planning consistently. New capabilities include vendor-managed inventory, transportation load building, deployment optimization, and co- and by-product planning.

In manufacturing and engineering, updates to will strengthen compliance and traceability in regulated environments. AI capabilities in the engineering-to-manufacturing handover will help teams understand the downstream impact of design changes before they reach the shop floor, surfacing implications for bills of materials, routings, lead times, and costs directly in context.

In , new Joule Agents will support execution-level decisions across warehouse and transportation operations, validating inbound receipts, aligning labor with real workload, and helping organizations respond faster to shifting constraints. Predictive labor planning in will allow operations teams to anticipate workforce needs rather than react to gaps.

In asset and service management, a new 麻豆原创 Field Service and Asset Management solution will bring planning, scheduling, dispatching, and field execution together in a single experience, connected to so work execution, parts usage, and costs stay aligned across service, operations, and finance.

These capabilities will become available in phases through 2026, aligning with customers鈥� existing 麻豆原创 landscapes. Together, they represent incremental but meaningful progress toward more connected, automated, and resilient supply chain operations.

The path forward

Supply chains don鈥檛 become autonomous overnight. This evolution happens workflow by workflow, expanding automation where it delivers real value, while keeping people firmly in control. As AI becomes embedded in execution, supply chain teams spend less time monitoring and firefighting, and more time shaping decisions, managing trade-offs, and building resilience.

This shift is bigger than any single organization. In a new white paper,聽, we explore how leading organizations are moving beyond isolated AI pilots toward AI embedded across end-to-end supply chain processes, and what it takes to get there. This article draws on multiple sources, including analytical support from McKinsey & Company.

That鈥檚 the direction we are moving, from reacting toward supply chains that anticipate, absorb, and adapt. What we鈥檙e introducing at 麻豆原创 Sapphire reflects that commitment.For more details on all announcements made this week, please refer to the .

Dominik Metzger is president and chief product officer of 麻豆原创 Supply Chain Management.

In his kickoff keynote at 麻豆原创 Sapphire Orlando, Florida, Klein and other 麻豆原创 Board members detailed how 麻豆原创 plans to bring agentic AI to the world’s most critical business workflows so that humans and AI can meet the accelerating demands of global business profitably, strategically, and safely.

鈥淭oday I鈥檓 super proud to launch our new 麻豆原创 Business AI Platform, which forms the basis for our vision of the future of business: the Autonomous Enterprise, where agents run the business and you can focus on what truly matters,鈥� Klein said.

Enterprise AI is at an inflection point, Klein told his 30,000-strong in-person and virtual keynote audience, and 麻豆原创 is in a unique position to deliver what customers need to turn their businesses into autonomous enterprises.

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The business AI imperative

Across industries, organizations are investing heavily in artificial intelligence, yet many still struggle to translate that investment into meaningful business value. At 麻豆原创 Sapphire, the message was clear: This isn鈥檛 a technology problem; it鈥檚 a context and execution problem.

While 80% accuracy may be sufficient for consumer AI applications, Klein said, 鈥淓ighty percent is just not good enough when you run the world鈥檚 most business-critical businesses. They [LLMs] should not guess; they should deliver accurate, compliant, and secure outcomes.鈥� 

Klein acknowledged that while adoption of AI has become near-universal, tangible business value remains elusive. Citing a recent Stanford AI survey, he noted that almost every company is now using AI, but seeing only limited return.

The reason, he argued, lies in a structural gap. Above the waterline of enterprise AI, LLMs continue to improve at tasks trained on publicly available data, while below it lies what enterprises truly need: AI that understands mission-critical business data, end-to-end processes, and operates within security, compliance, and governance frameworks.

ERP as the foundation for business AI

麻豆原创鈥檚 answer to this challenge begins with what Klein described as 鈥渢he brain of every company: its ERP system.鈥� For over 50 years, 麻豆原创 has had solutions with incredibly deep process and data domain know-how alongside the governance requirements, compliance controls, and company-specific configurations that define how businesses actually run.

Now, as part of the company鈥檚 new vision, 麻豆原创 plans to infuse this institutional knowledge into AI agents, enabling them to navigate thousands of business processes, select from more than 7 million data fields, and verify identity and access authorizations before returning any output.

鈥淲e鈥檙e bringing together LLMs with 50 years of business know-how stored in our ERP. But to do this, we had to do nothing less than completely reinvent our company,鈥� he told the audience. 鈥淭oday we are very excited to show you the new 麻豆原创 and our vision for the Autonomous Enterprise.鈥�

麻豆原创 Business AI Platform

To bring this vision to life, 麻豆原创 executives on stage announced a series of important innovations, beginning with the launch of the new 麻豆原创 Business AI Platform, a unified architecture bringing together 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud, and AI Foundation under a single roof.

鈥淭he heart of this new platform is the rich context layer,鈥� said Klein. 鈥淗ere, we infuse the deep ERP business domain know-how into the AI agents. Through our knowledge graphs, our AI agents have now a compass, a map, to find the right process and data in your ERP universe. And to provide the agents even more context, we are also introducing our new 麻豆原创 Domain Models. They have been trained on 麻豆原创’s code to even better understand the business logic of your company.鈥�

But, he said, 麻豆原创 is going further: 鈥淏ecause you run your business not only with 麻豆原创 solutions, our AI agents have to also understand non-麻豆原创 data. That’s why we included our 麻豆原创 Business Data Cloud in the context layer to build a single semantical data layer across 麻豆原创 and non-麻豆原创. No more silos, no spaghetti data sprawl鈥攂ecause no AI agent can compensate for a broken data model.鈥�

Echoing Klein, 麻豆原创 CTO Philipp Herzig, who presented the platform in detail, said it has been designed to close the agent adoption gap in the enterprise by delivering outcome, speed, enterprise-readiness, and context. 鈥淚t’s the place where you build, contextualize, reason, and govern AI,鈥� he said.

Herzig explained that the platform is structured around three layers: the context layer which Klein referenced, the build layer, and the governance layer. 鈥淎gents are only as powerful as the context they operate on,鈥� he said. 鈥淟acking context is the number one reason why enterprise AI projects fail to deliver value.鈥�

Within the build layer of the new platform, the new Joule Studio is designed to understand a company鈥檚 business challenges and enables the building of new AI agents quickly and easily.

The third tier is the governance layer, anchored by the new 麻豆原创 AI Agent Hub built on 麻豆原创 LeanIX. This provides a single command center to discover, manage, and govern all AI agents鈥斅槎乖� and non-麻豆原创. It will be generally available in Q3 and included in 麻豆原创 Business AI Platform at no additional charge.

Underscoring the changing AI marketplace, Herzig was joined on stage by KPMG Global Head of Advisory Rob Fisher, who told the audience: 鈥淲hat I鈥檓 hearing from clients is a clear shift; they鈥檙e moving from AI pilots to embedding integrated AI and agents into how work gets done. Where we see leaders really separating from the pack is in the execution and the organizational adaptability.鈥�

麻豆原创 Autonomous Suite

Building on the platform, 麻豆原创 Executive Board Member Muhammad Alam, 麻豆原创 Product & Engineering, announced the transformation of 麻豆原创鈥檚 SaaS application portfolio into the 麻豆原创 Autonomous Suite, described as the most significant evolution of 麻豆原创鈥檚 applications business in the company鈥檚 history.

The suite spans five domains: Autonomous Finance, Autonomous Spend, Autonomous Supply Chain Management, Autonomous HCM, and Autonomous CX, with more than 200 agents and over 50 assistants available in the coming months. Each assistant is mapped to core business roles and carries defined KPIs tracked through 麻豆原创 AI Agent Hub.

鈥溌槎乖� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,鈥� said Alam. 鈥淭hese agents are designed with outcomes as a core objective. Each assistant has a defined set of ROI KPIs that you can expect it to deliver.鈥� 

鈥淯nderpinning the autonomous suite are out-of-the-box agents鈥攈undreds of agents cutting across all core business processes,鈥� he shared. 鈥淭hese agents come together into what we call assistants, or Joule Assistants. We’ve mapped these assistants to roles across the core processes of an organization, because we know that the first step 
in realizing value from AI is to empower your people to do more, do it better, or do things that just weren’t possible to be done before.鈥�

Turning to Joule itself, Muhammad said 麻豆原创 is fundamentally reimagining how users will interact with 麻豆原创 applications in the future.

鈥淲e call this Joule spaces and along with the familiar Joule conversations experience and Joule Studio 2.0, it is now part of what we call Joule Work,鈥� he explained.

鈥淛oule Work represents a massive step forward in super-charging the capabilities of Joule as we know it today,鈥� Alam said. 鈥淲ith Joule Work, we’re bringing a claw-based agentic harness to Joule along with computer and file access, better support for open standards such as MCP and A2A, access to a more complete knowledge base, and, of course, amazing visualizations on the fly.鈥�

Industry AI: H&M and Sector-Specific Transformation

During the keynote, 麻豆原创 Chief Operating Officer Sebastian Steinhaeuser introduced the Industry AI initiative, delivering AI-powered solutions built on decades of sector-specific expertise across 26 industries. In life sciences, he highlighted how 麻豆原创 customer Takeda is achieving up to 10% productivity gains, up to 25% reduction in revenue loss from stock-outs, and up to five percent reduction in safety stock through Autonomous Regulated Manufacturing.

He was also joined on stage by H&M Group CDIO Ellen Svanstr枚m, who discussed how the fashion retailer is embedding AI across its value chain. Built on RISE with 麻豆原创, 麻豆原创 Business Data Cloud, 麻豆原创 Commerce Cloud, and 麻豆原创 SuccessFactors solutions, H&M has developed a Store Intelligence Agent that processes real-time signals to generate actionable recommendations for store managers. Svanstrom also demonstrated the AI-powered InStore Concierge, a customer-facing agent that bridges digital and physical retail through personalized outfit recommendations and real-time availability.

RISE with 麻豆原创 and 麻豆原创 GROW: Path to the Autonomous Enterprise

Returning to the keynote stage, Klein emphasized that technology adoption alone does not create business value. Simply plugging AI agents into your system landscape will drive zero value, he said. 鈥淢oving to the Autonomous Enterprise requires serious change management. Adoption of AI goes hand-in-hand with business process change and end user enablement.鈥�

To support customers on this journey, 麻豆原创 announced a comprehensive reset of its RISE with 麻豆原创 and 麻豆原创 GROW offerings. RISE with 麻豆原创 customers will receive contractual commitment to activate three Joule Assistants within the first year, with the Max Success Plan extending adoption across the full enterprise.  

麻豆原创 GROW customers will receive more than 20 AI assistants from day one, with an AI-enabled toolchain designed to support go-live in weeks. New partnerships with Palantir and Accenture will support the most complex migration scenarios.

Closing: The Autonomous Enterprise

Klein closed the keynote by asking Joule to summarize the key takeaways and noting that 麻豆原创 is evolving from being a software company to becoming a business AI company.

鈥淲e showed how to turn the promise of business AI into reality with 麻豆原创 Business AI Platform, which provides the data processes and governance AI need to deliver accurate and secure outcomes at scale; we introduced the 麻豆原创 Autonomous Suite, where applications reason, decide, and act for you; and we showed how to manage change management with RISE with 麻豆原创. Together with customers and partners, we showed how 麻豆原创 is helping companies realize the vision of the Autonomous Enterprise.鈥�

鈥淲e鈥檝e been reinventing how businesses run for over 50 years, and now by infusing 麻豆原创鈥檚 ERP brain into the new 麻豆原创 Business AI Platform, we鈥檙e solving one of the biggest challenges businesses are facing today: how to turn AI into business value,鈥� he said. 鈥淚t鈥檚 the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.鈥�

The company introduces a unified 麻豆原创 Business AI Platform, deepening partnerships with Anthropic, Amazon Web Services, Google Cloud, Microsoft, NVIDIA and Palantir

ORLANDO聽鈥� At 麻豆原创 Sapphire in 2026, (NYSE: 麻豆原创) introduced the to help enhance the world’s most critical business workflows, so that humans and AI work together to meet the accelerating demands of global business profitably, strategically and safely.

鈥淔or the mission-critical processes of our customers, ‘almost right’ just isn鈥檛 good enough,鈥� said Christian Klein, CEO of 麻豆原创 SE. 鈥淏y uniting 麻豆原创 Business AI Platform with 麻豆原创 Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.鈥�

The Autonomous Enterprise includes a unified AI platform for building, contextualizing and governing agents, an autonomous suite that executes core business operations and a new user experience that redefines how people work with enterprise software.

Introducing 麻豆原创 Business AI Platform

麻豆原创 Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 麻豆原创 Business AI Platform now unifies 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud and 麻豆原创 Business AI into a single, governed environment.

At its core is the 麻豆原创 Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer’s 麻豆原创 landscape. Joule Studio is 麻豆原创’s AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code and AI frameworks of their choice on 麻豆原创-managed infrastructure that is secure, scalable and optimized for enterprise AI.

Deploying 麻豆原创 Autonomous Suite Across Every Business Function and Industry

Building on this foundation, 麻豆原创 also introduced 麻豆原创 Autonomous Suite, which enables 麻豆原创’s existing business applications with AI agents capable of running processes from start-to-finish.

The suite will deploy more than 50 domain-specific Joule Assistants across finance, supply chain, procurement, human capital management and customer experience. These assistants will automate end-to-end processes by orchestrating a subset of over 200 specialized agents to execute precise tasks. For example, the new Autonomous Close Assistant can compress the financial close process from weeks to days by automating journal entries, reconciliation and error resolution across the entire process.

麻豆原创 also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements. At 麻豆原创 Sapphire, 麻豆原创 showcased its work with European energy giant RWE to leverage Industry AI, helping reduce unplanned downtime across its offshore wind turbines. With 麻豆原创’s Autonomous Asset Management scenario, AI agents are designed to analyze data from thousands of past incidents, identify the likely root cause and generate pre-filled work orders with the right tools and proven fixes from other sites.

Designing the Autonomous User Experience

The company also revealed Joule Work, redefining how users engage with 麻豆原创 software. Instead of navigating individual applications and entering data across several screens, users will now interact primarily with Joule. By describing a desired business outcome, Joule will orchestrate the right combination of workflows, data and agents to get it done.

Joule Work goes beyond conversation, proactively surfacing relevant insights and automating routine tasks behind the scenes so work moves forward even when humans aren’t actively steering it. It will be available on desktop, mobile and voice across 麻豆原创 and non-麻豆原创 systems.

Accelerating the Customer Journey Toward Autonomy with 鈧�100 Million Infusion

麻豆原创 evolved its customer and partner programs to help accelerate the organization’s journey to the Autonomous Enterprise. To catalyze adoption, the company has launched a 鈧�100 million fund for 麻豆原创 partners to help customers deploy 麻豆原创-built AI assistants and agents. The fund is also available to partners that extend or build new partner agents on the new 麻豆原创 Business AI Platform using Joule Studio.

麻豆原创 has enhanced its RISE with 麻豆原创 and 麻豆原创 GROW offerings to accelerate AI adoption. Both include access to the Joule Assistants portfolio; RISE with 麻豆原创 customers will have three assistants activated within their first year, while 麻豆原创 GROW customers receive full portfolio access at onboarding. 麻豆原创 S/4HANA on-premises and 麻豆原创 ERP Central Component (麻豆原创 ECC) customers are not excluded: those that commit to transitioning the majority of their current landscape to 麻豆原创 Cloud ERP gain access to select AI scenarios, bridging the gap between their current landscape and their cloud destination

麻豆原创 also introduced new agent-led transformation tooling that can reduce ERP migration efforts by more than 35 percent, driving faster and more predictable projects by automating system analysis, code remediation, configuration and testing at scale.

Lastly, 麻豆原创 announced a full slate of strategic partnerships across each category:

• Platform and suite partnerships include Anthropic, with Claude among the foundation models 麻豆原创鈥檚 AI platform will leverage to power Joule agents across HR, procurement and supply chain; Amazon Web Services, bringing zero-copy data integration between 麻豆原创 Business Data Cloud and Amazon Athena; Google Cloud and Microsoft, enabling bidirectional agent-to-agent interoperability between Joule and external agent frameworks; Mistral AI and Cohere, delivering sovereign model options on 麻豆原创’s cloud infrastructure; , providing visual AI workflow orchestration inside Joule Studio; NVIDIA, whose OpenShell provides the trusted secure runtime for Joule Studio; and , bringing AI agents into 麻豆原创 Service Cloud to handle customer interactions with full access to business data and service processes.
• Implementation partnerships include Palantir and Accenture, partnering on complex data migration scenarios, and for AI-powered cloud ERP migrations.

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About 麻豆原创

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

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In today鈥檚 environment of ongoing disruption, rising customer expectations, and persistent labor and cost pressures, warehouse operations are more strategic than ever. We believe long-term recognition in this market requires more than point solutions; it demands scale, depth, and an orchestrated approach that connects warehousing with other supply chain functions.

A recognition we believe is built on scale, reach, and execution

We believe scale matters when it comes to warehouse management. Warehouse operations are increasingly complex and diverse, and organizations often operate networks that span regions, industries, and levels of automation. Warehouse management is not a one鈥憇ize鈥慺its鈥慳ll challenge, and global organizations need solutions that can support regional requirements while remaining consistent and integrated across complex networks.

(麻豆原创 EWM) is designed to support organizations running 麻豆原创 ERP or 麻豆原创 S/4HANA as well as non-麻豆原创 environments. With customers across 24 industries, 麻豆原创 EWM supports a broad range of warehouse complexity鈥攆rom regional distribution centers to highly automated, high鈥憈hroughput operations. It enables organizations to standardize execution, improve visibility, and integrate warehouse processes with transportation, manufacturing, and broader supply chain operations.

麻豆原创 EWM continues to expand its innovation footprint with APIs for seamless robotics integration, as well as AI-assisted capabilities such as predictive labor demand planning and slotting. 麻豆原创鈥檚 Joule AI solution鈥攅mbedded across applications鈥攃an further enhance 麻豆原创 EWM by enabling natural-language interactions and supporting AI capabilities that operate both within workflows and in the background, helping organizations improve workforce efficiency and execution agility.

A portfolio approach to meet different warehouse needs

麻豆原创鈥檚 warehouse strategy is built around choice and flexibility. In February 2026, 麻豆原创 announced the general availability of , an AI鈥慹nabled, cloud鈥憂ative, microservices-architecture-based solution designed to complement 麻豆原创鈥檚 established logistics portfolio by supporting local, satellite, and mid鈥憇cale logistics operations.

麻豆原创 Logistics Management helps unite warehouse execution and transportation planning in a single solution, supporting pick鈥憄ack鈥憇hip processes while enabling integrated freight coordination and carrier collaboration through . Designed to work seamlessly with , the solution helps organizations connect localized operations with broader enterprise landscapes, improving coordination and real鈥憈ime visibility across logistics networks. Embedded AI capabilities, including support for Joule, can assist users with faster decision鈥憁aking and more intuitive interactions across logistics workflows.

Together, 麻豆原创 EWM and 麻豆原创 Logistics Management enable organizations to align technology investments with operational complexity, supporting mixed warehouse networks that include both highly automated facilities and smaller, distributed sites.

Platform strategy and supply chain convergence

Warehouse execution does not operate in isolation. 麻豆原创鈥檚 platform strategy connects warehousing with transportation, manufacturing, quality, maintenance, global trade, sustainability, and partner collaboration across the supply chain.

麻豆原创 EWM can be used with solutions to support process analysis and continuous improvement. It can leverage standardized APIs across 麻豆原创 ERP and 麻豆原创 S/4HANA to connect with adjacent execution systems such as transportation management, global trade, environmental health and safety, and . This platform-based approach helps organizations move beyond siloed execution toward coordinated, end鈥憈o鈥慹nd supply chain

Looking ahead

麻豆原创 remains focused on helping customers modernize warehouse operations while navigating broader ERP and cloud transformations. While organizations must carefully evaluate deployment models, cloud strategies, and long鈥憈erm road maps, 麻豆原创 continues to invest in warehouse management solutions that scale globally, integrate deeply, and support evolving business requirements.

We believe that being recognized by Gartner as a Leader for the 12^th consecutive time reflects continued execution across 麻豆原创鈥檚 warehouse management portfolio and the trust customers place in 麻豆原创 to manage critical logistics operations worldwide.

to learn more about why 麻豆原创 is a Leader. Learn more about the capabilities of .

Till Dengel is global head of Product Marketing for Logistics and Asset & Service Management at 麻豆原创.

*Gartner, Magic Quadrant for Warehouse Management Systems, by Simon Tunstall, Rishabh Narang, Federica Stufano, 29 April 2026.

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

Held from April 20鈥�24, Hannover Messe is the world鈥檚 leading industrial trade fair.

On day one, Christian Klein, CEO of 麻豆原创 SE, stopped by the 麻豆原创 booth before joining German Chancellor Friedrich Merz and other industrial leaders on the center stage to discuss the importance of moving from AI ambition to real-world execution.

And visitors to the 麻豆原创 booth experienced that shift firsthand, following the production of the ginger shot.

Packaged in a neat blue box, the ginger shot was refreshing but that wasn鈥檛 the only takeaway. The real takeaway was how 麻豆原创鈥檚 new set of AI-powered manufacturing and supply chain innovations can deliver connected .

Supply chain orchestration

From AI and data and then using 麻豆原创鈥檚 agentic AI, visitors saw what supply chain orchestration looks like in practice. 麻豆原创 uses , trusted data, and applications to help manufacturers聽sense, analyze, and act in real time.

At the booth, visitors saw human operators interact with an ANYbotics robot through Joule using natural language to run live, remote field service inspections; Uhlmann鈥檚 high-tech glass-fronted packing machine, PacXplorer, in action opposite the CNC machine from DMG MORI that was creating spare parts for the PacXplorer; and, at end of the production cycle, AIMBO鈥檚 robot handling the picking and packing of the ginger shot. Both AIMBO and ANYbotics are part of 麻豆原创鈥檚 growing network of physical AI partnerships.

In addition to many tours held in German and English, day one also saw tours in Japanese, Chinese, and Portuguese鈥擝razil was the partner country at Hannover Messe 2026.

Equipped with headphones to block out the noise of the crowds at the booth, visitors heard how 麻豆原创鈥檚 AI can deliver trusted orchestration and smarter execution for and .

Live AI use cases demonstrate functions and benefits

Operations and insights use case

Here, visitors experienced 麻豆原创鈥檚 vision of supply chain orchestration. In this vision, supply chain orchestration acts as the nerve center of the enterprise. It uses external alerts such as natural disasters, port congestions, or supplier routes to optimize enterprise logistics and planning using agents.

Benefits can include faster response times with AI-assisted monitoring and automated alerts; improved decision-making with data-driven, operational decisions powered by integrated business AI capabilities; and seamless integration with end-to-end connectivity from supply chain planning through to manufacturing execution and quality control.

Top AI functions

• can assist with order release and real-time monitoring.
• A physical AI robot inspects hazards, analyzes inspection data, and identifies root causes.
• Supply optimization analysis helps summarize insights, analyze, and explain the time-series optimization planning run.

Smart production use case

DMG MORI demonstrated production at its CNC machine鈥攁s part of an end-to-end process鈥攆rom engineering to planning to production.

As the white robotic arm of the CNC machine silently moved the pusher spare part聽after the milling process, visitors learned about the benefits of integration, from design to tool management, CNC programs to as part of a seamless, integrated process. The production operator dashboard offers the operator on the machine AI capabilities and insights to operational and maintenance information.

The process then continues through to logistics execution with 麻豆原创 Logistics Management, which helps combine warehousing and transportation capabilities for smaller warehouses.听 This聽features an AI-powered logistics assistant that can cut through the noise, automatically gathering, summarizing, and prioritizing critical shipment information. It can also provide real-time shipping prices, bringing to life trusted orchestration and smarter execution.

Top AI functions

• uses natural language to help streamline warehouse and transportation operations.
• can provide manufacturing information and support decision-making throughout the workflow.

Intelligent packaging use case

Uhlmann’s PacXplorer and 麻豆原创 highlighted a fully integrated, high-speed packaging line from 麻豆原创 S/4HANA, to 麻豆原创 Digital Manufacturing, down to Uhlmann鈥檚 automation layer to produce the packaged ginger shot. The ginger shots were moved away from the line by a mobile autonomous robot from Symovo. This use case showed visitors how 麻豆原创 supports regulated industries such as pharma and life sciences. 聽

Highlighted benefits include increased operational speed with higher throughput thanks to decreased order processing time, built-in regulatory compliance, reduced manual intervention, inventory transparency, and data integrity across the entire production chain.

Top AI functions

• Condition monitoring-led services can enhance asset uptime and service efficiency by combining AI-driven insights and seamless collaboration across the service ecosystem.
• AI-empowered flow analysis enables quick process modeling and engineering optimization.
• Intelligent exception handling is embedded in agent-driven processes.
• Joule’s integrated AI agents can support decision-making throughout the workflow.
• Joule can help power order and line insights.

Humanoid use case

At the final stop before getting their ginger shots, visitors watched an intelligent humanoid robot perform physical tasks at the end of the packaging line, bridging the gap between digital planning and physical execution, highlighting 麻豆原创鈥檚 Project Embodied AI.

Benefits of humanoids include increased operational speed with higher throughput due to a decreased order processing time; increased business uptime and cost efficiency especially in areas dangerous or difficult for humans; inventory transparency with real-time data integrity across the warehouse; and physical-digital alignment eliminating misalignment between planning and execution.

Top AI functions

• Joule and Joule Studio can enable robots to understand the physical world, make autonomous decisions, and learn from their environment for smarter operations.

More than a quick refuel

At the end of their visit, visitors got so much more than a quick refuel to slake their thirst. Following the creation of the ginger shot from recipe development and planning to production with mixing, filling, and packing, visitors came away with a clear understanding of how 麻豆原创 is connecting insight to execution with trusted orchestration and smarter execution. And, it is this trusted orchestration and smarter execution that is building the resilience every manufacturer needs in today鈥檚 world.

To succeed, manufacturers need more than incremental improvements or siloed optimizations. They need to orchestrate their operations end to end with connected processes and trusted data, so they can respond faster to change, operate more efficiently, remain compliant, and continue to grow鈥攅ven as disruption is constant.

At Hannover Messe 2026, the world鈥檚 leading stage for industrial transformation, 麻豆原创 will introduce a new set of AI鈥憄owered manufacturing and supply chain innovations. These innovations help companies ensure business continuity by orchestrating people, processes, and technology across their extended enterprise, turning volatility into an opportunity for resilience, efficiency, and customer impact.

From AI insight to AI in execution

For years, manufacturers have invested in analytics and dashboards to improve visibility. But visibility alone does not prevent disruption. What鈥檚 required now is AI embedded directly into core business processes, where intelligence can analyze alerts, reason over business impact, and provide real-time solutions to resolve issues. With agentic AI, companies are now able to go a step further: automating the right actions for the best outcomes, with humans remaining in the loop wherever critical decisions are required.

麻豆原创 is operationalizing AI at industrial scale by embedding AI agents directly into supply chain and manufacturing workflows and contextualizing them with trusted enterprise and network data. Built on harmonized industrial, transactional, and network data, these agents can move beyond analysis to real鈥憈ime prediction and execution, working to deliver resilience, regulatory readiness, and measurable customer impact from day one. Creating tangible ROI is what matters most鈥攚hether by reducing unplanned downtimes, scrap, and rework, or by increasing quality and ultimately production output.

Orchestrating the supply chain end to end with AI

At the center of 麻豆原创鈥檚 focus at Hannover Messe is .

麻豆原创 helps manufacturers connect processes and data not only across internal teams, but also across company boundaries鈥攚ith suppliers, logistics partners, and service providers. By using AI agents to connect design, planning, procurement, manufacturing, logistics, service, and asset management鈥攁nd by integrating seamlessly with ERP and line-of-business systems鈥斅槎乖� helps break down silos that slow decision-making and increase operational risk.

This new agentic orchestration is powered and governed by a portfolio of intelligent applications that act, not just analyze, enabling faster, more coordinated responses without sacrificing quality, control, or growth.

New AI agents redefining planning, service, and operations

At Hannover Messe 2026, 麻豆原创 will showcase AI agents that help manufacturers and operators reduce time to value, stabilize operations, and improve service levels amid ongoing disruption. As a precursor to broader announcements planned for 麻豆原创 Sapphire, these agents demonstrate how agentic AI delivers practical benefits across all supply chain domains. Here are a few examples:

Manufacturing

• Production Master Data Agent helps automate and optimize the creation and maintenance of production master data. By leveraging the bill of materials, the agent can generate production routings鈥攊ncluding operations and work centers鈥攁nd help ensure components are correctly assigned across the production process. This helps reduce manual effort, accelerate production setup, and keep production data accurate as requirements change. General availability is planned for Q2 2026.
• Production Planning and Operations Agent enables planners to release production orders using natural language while automatically validating material availability, capacity, and scheduling constraints. Joule provides recommendations鈥攕uch as alternative components or rescheduling options鈥攖hat planners can review and approve, reducing manual work and keeping production aligned with real鈥憌orld conditions. General availability is planned for Q2 2026.

Assets & services

• Field Service Dispatcher Agent can improve service responsiveness and asset uptime by dispatching the right technician based on skills, location, asset condition, and priority鈥攄riving faster resolution and better workforce utilization. General availability is planned for Q2 2026.
• Alert Processing Agent can enrich operational alerts using past incidents, resolutions, and contextual signals and recommend clear, data鈥慸riven actions to help teams resolve issues faster and improve operational reliability. General availability is planned for Q3 2026.
• Asset Health Agent analyzes time鈥憇eries health indicators to assess and summarize the current and projected health of individual and multiple technical objects. By forecasting when assets are likely to become critical and alerting users in real time, the agent supports condition鈥慴ased maintenance and helps minimize downtime while ensuring asset availability. General availability is planned for Q3 2026.

AI agents advancing logistics execution

• Material Reservation Agent helps ensure materials are available when and where needed by automating reservation creation and maintenance based on business rules鈥攔educing delays, improving inventory accuracy, and optimizing working capital. General availability is planned for Q2 2026.
• Outbound Task Orchestration Agent can protect customer service levels by detecting and resolving picking and packing issues in real time, orchestrating corrective actions to support on鈥憈ime, accurate delivery. General availability is planned for Q2 2026.

Aligning workforce, logistics, and assets in real time

Operational resilience also depends on synchronizing people with all other resources as conditions change.

With , skills, certifications, availability, and labor rules are aligned with real-time operational demand so workforce plans can adjust automatically as production changes.

In logistics, , together with the new solution, helps organizations reduce transportation costs, accelerate warehouse execution, and improve delivery performance. Using conversational interaction with Joule, order managers can prioritize fulfillment while automatically accounting for availability and scheduling constraints.

Asset and quality operations also benefit from embedded intelligence. AI-assisted anomaly detection and alert processing in helps teams identify risks earlier, prioritize actions, and reduce unplanned downtime. In parallel, 麻豆原创 Document AI can automate the , improving throughput, data quality, and compliance at scale.

Regulatory readiness and what鈥檚 next

As regulatory requirements tighten, 麻豆原创 is expanding support for Digital Product Passports as part of , aligned with the EU鈥檚 Ecodesign for Sustainable Products Regulation (ESPR). These capabilities help manufacturers create ESPR鈥憆eady product records capturing environmental impact, material composition, repairability, and recyclability data. General availability is planned for Q2 2026.

Expanded 麻豆原创 Business Network capabilities also deliver built鈥慽n e鈥慽nvoicing compliance and data-residency support, enabling secure partner collaboration, synchronized logistics, and improved delivery performance across global networks.

See it live at Hannover Messe 2026

Taken together, these innovations reflect a shift from reactive management to intelligent execution鈥攚here AI is embedded directly into the processes that keep manufacturing and supply chains running today while laying the foundation for the next wave of innovation that will be unveiled at 麻豆原创 Sapphire.

Visit 麻豆原创 at booth F08 in Hall 15 at Hannover Messe 2026, April 20鈥�24, to see how AI-infused orchestration, embedded AI agents, and end鈥憈o鈥慹nd supply chain applications are redefining manufacturing.

Dominik Metzger is president and chief product officer for 麻豆原创 Supply Chain Management.

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.

Get started .

SECTION

麻豆原创 Business AI for supply chain

Project Setup Agent
Beta release

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

Get started .

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

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

Get started .

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

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

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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.

Get started .

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

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

Get started .

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

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

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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.

Get started .

麻豆原创 Business AI for finance

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

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

Get started .

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

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

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

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

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

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

Get started .

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

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

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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.

Get started .

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

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

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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.

Get started .

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

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

Get started .

Expense Automation Agent
麻豆原创 Early Adopter Care

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

See the demo .

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

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

Get started .

Policy Navigator
麻豆原创 Early Adopter Care

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

Get started .

麻豆原创 Business AI for procurement

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

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

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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.

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麻豆原创 Document AI, enhancements

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

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

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

Generative AI Hub in AI Foundation, enhancements

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

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

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

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

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

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

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

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

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

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

See .

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

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

Get started .

麻豆原创 Business AI for industries

Tender Analysis Agent
General availability

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

Get started .

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

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

Get started .

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

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

Get started .

Joule with 麻豆原创 Intelligent Clinical Supply Management
General availability

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

Get started .

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

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

Get started .

麻豆原创 Business AI for business transformation management

Joule with 麻豆原创 Signavio solutions
General availability

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

Get started .

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

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

Get started .

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

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

Get started .

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.

We believe this recognition reflects 麻豆原创鈥檚 continued focus on helping organizations run resilient, efficient, and increasingly intelligent transportation operations in a rapidly changing global logistics environment.

Magic Quadrant reports are a culmination of rigorous, fact-based research in specific markets, providing a wide-angle view of the relative positions of providers in markets where growth is high and provider differentiation is distinct.

We believe 麻豆原创鈥檚 placement as a Leader underscores our commitment to ongoing innovation across transportation, logistics execution, and supply chain orchestration.

Addressing today鈥檚 transportation challenges

Transportation operations are under constant pressure, from cost volatility and capacity constraints to sustainability requirements and rising customer expectations. Organizations need solutions that help them plan, execute, and adapt across increasingly complex networks while maintaining visibility and control.

and are designed to support these needs through a holistic, end鈥憈o鈥慹nd approach. By connecting freight procurement, planning, execution, and settlement on a single platform, 麻豆原创 helps organizations respond more effectively to disruptions, align transportation decisions with broader supply chain objectives, and support compliance with regional and industry鈥憇pecific requirements.

A platform built for complex, global operations

麻豆原创 Transportation Management supports organizations operating across multiple modes, regions, and industries. Built to scale with business growth, the solution is designed to support complex, global transportation networks while enabling standardization and process consistency across operations.

Customers across industries鈥攊ncluding consumer products, chemicals, agriculture, mining, retail, wholesale distribution, and industrial manufacturing鈥攗se 麻豆原创 Transportation Management to manage complex transportation networks at scale. Industry鈥憇pecific capabilities from 麻豆原创, such as support for automotive and mill and mining operations, along with integration with , help organizations address specialized requirements while accelerating time to value. Dedicated industry business units further tailor go鈥憈o鈥憁arket strategies and solutions to industry鈥憇pecific challenges.

Advancing transportation management with AI

Data-driven decision-making is increasingly essential for transportation operations. 麻豆原创 continues to invest in AI-driven capabilities that help automate processes, improve responsiveness, and increase productivity.

Recent innovations include AI-assisted use cases such as goods receipt processing, as well as the integration of conversational planning into transportation planning workflows. These capabilities are designed to help planners and operators work more efficiently by reducing manual effort and supporting faster, more informed decisions across execution and settlement processes. 麻豆原创 Joule for Consultants is another recent AI innovation that accelerates solution adoption by offering instant, expert-level guidance and best practice recommendations for solution configuration.

Supporting a connected logistics landscape

Transportation does not operate in isolation. 麻豆原创鈥檚 logistics portfolio brings together transportation, warehousing, and business network collaboration on a cohesive foundation.

This includes the recent general availability of , a new solution designed to support regional and local distribution operations by combining transportation execution, warehouse processes, and carrier collaboration in a single offering. 麻豆原创 Logistics Management complements 麻豆原创 Transportation Management by helping organizations extend standardized logistics processes to satellite locations and growing operations, supporting broader adoption while reducing complexity. 麻豆原创 Logistics Management can be deployed alongside 麻豆原创 Transportation Management to support multi-tier transportation operations, providing the right tool for each level of complexity.

麻豆原创 Transportation Management, together with other logistics solutions from 麻豆原创, helps organizations modernize their logistics operations in a way that aligns with their broader ERP and supply chain strategies as they progress on their transformational journeys via or .

Why organizations choose 麻豆原创 Transportation Management

Organizations choose 麻豆原创 Transportation Management to support complex transportation requirements across global and regional operations. The solution offers broad functional coverage, deep integration across the 麻豆原创 supply chain portfolio, and the flexibility to support both advanced transportation networks and evolving business needs.

With continued investment across 麻豆原创 Transportation Management, 麻豆原创 Logistics Management, warehousing, and 麻豆原创 Business Network for Logistics, 麻豆原创 remains focused on helping organizations operate resilient transportation processes while supporting both global complexity and localized execution models.

Explore how 麻豆原创 Transportation Management can .

Till Dengel is global head of Product Marketing for Logistics and Asset & Service Management at 麻豆原创.

*Gartner, Magic Quadrant for Transportation Management Systems, Brock Johns, Oscar Sanchez Duran, Manav Jain, 30 March 2026.

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

The company manages an extensive portfolio of more than 125,000 products. Despite its strong market position, digitalizing procurement across diverse customer environments remains a key challenge, particularly in e-procurement, where large customers often have very different requirements, even when market standards exist.

To address this, W眉rth recognized the need to better connect procurement processes and now collaborates closely with leading e-procurement systems and platforms. The company has driven the harmonization of customer processes and ensured seamless onboarding to . At the same time, W眉rth actively supports its customers in harmonizing and digitalizing their own internal workflows.

As the world鈥檚 largest procurement platform, 麻豆原创 Business Network enables more efficient procurement and automated order processing and provides end-to-end transparency across the purchase-order鈥憈o鈥慽nvoice flow between W眉rth and participating customers. This scope involves purchasing orders, delivery confirmation, and invoices, with exceptions managed through clearly defined workflows.

Save time and boost efficiency: seven minutes saved per order

Manual processing of orders, sent as PDFs or via non鈥慽ntegrated channels, creates disproportionate effort, especially in relation to the order value, since indirect materials often involve smaller order values with many order items.

 With automation, W眉rth saves approximately seven minutes per order on average — approximately 490,000 minutes annually or about 8,167 hours. The platform enables digital order transmission, catalog exchange, and automated invoice matching, materially improving process efficiency.

Seamless customer purchasing journey

With around 3,000 sales representatives in Germany, more than 600 pick-up branches, and numerous on-site storage solutions, including automated dispensing machines, W眉rth offers customers a truly omnichannel purchasing experience. Through 麻豆原创 Business Network, all these touchpoints can be seamlessly integrated, giving customers that adopt this approach full transparency, as every order becomes visible directly within their own system.

One construction industry leader worked with W眉rth to integrate dispensing machines and branch pick鈥憉ps into 麻豆原创 Business Network, digitalizing its procurement processes. This integration has largely eliminated manual activities in day鈥憈o鈥慸ay order handling of standard processes. Exceptions are automatically identified and routed through defined workflows, while payment instructions are triggered once the purchase order, goods confirmation, and invoice are successfully matched.

Stronger supplier-customer partnership

Beyond operational savings and improved collaboration, W眉rth enhances the customer experience through near-real-time integration across procurement, invoicing, and logistics. Digitalized procurement processes help meet customer requirements more reliably and further strengthen the supplier-customer partnership.

To see how W眉rth streamlined procurement with 麻豆原创 Business Network and significantly reduced manual effort, .

Complementing 麻豆原创鈥檚 established logistics portfolio supporting large-scale supply chain operations, 麻豆原创 Logistics Management brings innovative capabilities specifically tuned to the needs of smaller operations seeking efficiency, real-time visibility, and faster decision-making.

鈥淟ogistics is undergoing a fundamental transformation. Those who invest in strategic warehousing and logistics networks are investing in a future defined by responsiveness and relevance. It鈥檚 about being ready, connected, and purposeful,鈥� says Till Dengel, 麻豆原创鈥檚 global head of Product Marketing for Logistics.

Designed for local impact, powered for global reach 

While 麻豆原创鈥檚 best-in-class  continue to serve complex global logistics with extensive capabilities, 麻豆原创 Logistics Management now bridges the gap for local and satellite operations needing powerful, streamlined tools and controls without the complexity of large enterprise systems. Not only can 麻豆原创 Logistics Management elevate the performance of localized operations, but it also enables a connected network of satellite operations that can stay coordinated with global enterprise systems.   

The  solution offers: 

• Connected fulfilment excellence: By uniting warehousing and transportation capabilities, 麻豆原创 Logistics Management helps streamline order fulfillment by managing pick-pack-ship workflows while efficiently planning and coordinating the freight movement. The solution includes built-in collaboration with carriers through 麻豆原创 Business Network, connecting shippers directly with logistics providers for real-time updates that can minimize costly delays and keep shipments on track.  
• Tailored for smaller operations: 麻豆原创 Logistics Management is ideal for local branches, subsidiaries, and seasonal operations. It helps eliminate unnecessary complexity, giving smaller operations the powerful tools and connectivity they need without the overhead of large enterprise systems. 
• Seamless integration: Designed to work seamlessly with , 麻豆原创 Logistics Management can eliminate hidden interface costs and helps ensure compatibility with 麻豆原创鈥檚 existing transportation and warehouse management tools. Businesses can benefit from a smooth, cohesive ecosystem. 
• AI-driven and human-centric: Embedded AI empowers faster, smarter decision-making and workflows. can enable users to interact via natural language, helping to make involved logistics questions easy to handle right from the start. The solution鈥檚 mobile-first design helps ensure users can ramp-up quickly and access essential functions anytime, anywhere, for efficient workflows on the go. 
• Scalable SaaS solution: As a SaaS-native solution, 麻豆原创 Logistics Management can be up and running in days. It can scale effortlessly as the business grows, offering built-in analytics and dashboards that help provide actionable insights tailored to operations鈥攕mall or large. 

鈥淰isibility grants insight, connectivity empowers control, and agility provides the decisive edge,鈥� Dengel says. 鈥淭he future of logistics belongs to those who digitize every process, orchestrate every tier, and deliver on every promise.鈥� 

麻豆原创 Logistics Management helps empower businesses to connect and manage logistics operations efficiently, regardless of size. Whether running small local operations or orchestrating global distribution, 麻豆原创鈥檚 latest AI-powered innovation can equip businesses with the tools and capabilities to thrive in highly competitive markets by enabling them to be connected, agile, and growth-oriented. Learn more about . 

Oyku Ilgar is part of 麻豆原创 Supply Chain Thought Leadership & Awareness.

But what happens when the bill comes due, so to speak, from local jurisdictions? How may a business transact commerce globally while adhering to an emerging set of electronic-invoicing requirements that differ among countries?

Global visibility across multiple tiers of the supply chain

As global supply chains weather shifting tariff policies, geopolitical tensions, and climate events, business leaders have turned to cloud-based business networks to instill operational resilience, extend transparency, and foster collaboration. The convergence of data, applications, and artificial intelligence capabilities enable businesses to manage supply chains, procurement, logistics, asset maintenance, working capital, dynamic discounting, and other crucial interdependencies with comprehensive reach. Yet just as digital platforms foster connected commerce, they also facilitate regulatory oversight of the very same activity. That which simplifies business processes can at the same time invite complexity in the regulations governing them, particularly when the fine print varies by jurisdiction. Call it a paradox of procurement, or an irony of the intelligent enterprise.

The proliferation of legislation mandating electronic invoicing reflects a desire on the part of governments to bolster tax compliance, streamline financial reporting, combat fraud, and document the ethical sourcing of product components. To aid with compliance in the jurisdictions where they transact, can support buyers and suppliers alike with the necessary workflows for invoice generation, submission, receipt, and storage鈥攁ll while safeguarding otherwise confidential data. Our prioritizes business-to-business collaboration by providing localization support for 41 countries, tailoring requested data to required format, and connecting businesses directly with trading partners and tax authorities. 麻豆原创 Business Network can integrate seamlessly with government electronic-invoicing portals through partners as well as through .

Electronic-invoicing capabilities take shape around emerging legislation

Already in 2026, new electronic-invoicing mandates have taken effect in , , and , with the and set to follow suit later in the year. Though it takes shape differently around the world, the trend toward electronic invoicing is unmistakable. Requirements range from periodic reporting to continuous transparency, from preapproval of transactions by tax authorities to notification after the fact, from country-specific formats to , and so on. In India, Malaysia, and Romania, for example, suppliers must clear invoices with tax authorities, whereas in Belgium, Germany, and Japan invoices must conform to a particular format. In France and the United Arab Emirates, meanwhile, a specific platform or network must be engaged. requires businesses to issue and receive invoices via its Sistema di Interscambio (SDI) platform, using a country-specific XML format called FatturaPA. By contrast, permits UBL, CII, and ZUGFeRD formats but takes an ambivalent approach as to method of transmission.

For each of these countries, 麻豆原创 Business Network can provide a solution. Connectivity to Italy鈥檚 SDI portal is natively embedded, obviating any need for additional licensing. For Germany, invoices sent through 麻豆原创 Business Network arrive in the UBL format. Organizations with a license for the cloud edition of the can even receive invoices originating outside 麻豆原创 Business Network, such as via e-mail or the pan-European Peppol procurement system.

Not only can 麻豆原创 Business Network accommodate the different formats set into law, but other invoicing attributes as well. Consider the obligation to archive. In Germany, invoices must be kept on hand for eight years. In France, it鈥檚 a decade. Elsewhere, mandates vary or may not apply. 麻豆原创 Business Network offers the flexibility to match business rules, or the parameters set by organizations within which transactions may proceed with trading partners, to all manner of regulatory requirements. This can prove especially valuable with orchestrating documents and processes that span sourcing, procurement, and finance鈥攃orporate functions that, prior to the advent of cloud-based networks, had often operated in relative isolation. 麻豆原创 Business Network can also provide businesses with the end-to-end visibility and鈥攅qually important鈥攖he analytics to assess performance, gauge against benchmarks, and identify opportunities for growth and collaboration.

For the emerging set of electronic-invoicing mandates across the globe and other compliance-related processes, . That鈥檚 because no matter where commerce takes place or in which local currency, C-suite leaders understand one thing is priceless: peace of mind. Only a cloud-based network supple enough to carry out operational processes on a global scale yet sufficiently nimble to adhere strictly to electronic-invoicing requirements and other regulations that typically arise on a national level can instill the confidence that businesses need to thrive in these turbulent times.

Learn how 麻豆原创 Business Network can by streamlining business processes, increasing visibility, and connecting to new buyers.

J枚rn Keller is executive vice president and chief product officer for 麻豆原创 Business Network.

The past few years have taught us that disruption is the new normal. Whether it鈥檚 global conflicts, raw material shortages, or sudden demand spikes, supply chains need to pivot faster than ever. That鈥檚 why this year, the conversation isn鈥檛 about incremental improvements鈥攊t鈥檚 about reimagining processes with intelligent technologies that anticipate, adapt, and act autonomously.

From complexity to clarity: how agentic AI changes the game

Agentic AI is reshaping supply chains, and we鈥檙e already seeing real value in practice:

• Supplier onboarding in hours, not weeks: Companies can drive substantial efficiencies by collaborating more deeply with their suppliers, such as material or logistics providers. AI agents autonomously validate supplier credentials, check compliance, and integrate them into your network, cutting onboarding time by up to 50%.
• Predictive maintenance and service that prevents downtime: Instead of reacting to failures, AI agents monitor equipment health and trigger proactive service, reducing unplanned outages by 30%.
• Autonomous disruption handling: When short-term disruptions or opportunities arise to demand or supply levels, AI agents evaluate events and alerts, model scenarios, and drive action while keeping humans in the loop. If critical inventory needs to be shifted for example, agents place orders automatically, optimizing stock levels and reducing lead times by 25%.

These aren鈥檛 distant possibilities鈥攖hey鈥檙e real scenarios already piloted by 麻豆原创 Supply Chain customers. AI isn鈥檛 replacing people; its amplifying human decision-making, freeing teams to focus on strategy rather than firefighting.

Why this matters: analyst rankings tell the story

麻豆原创 solutions underpin strategies that earned recognition in major 2025 analyst reports, including:

• IDC MarketScape for Multi-Enterprise Supply Chain Commerce Networks*: 麻豆原创 was named a Leader for enabling real-time collaboration and orchestration across global ecosystems with 麻豆原创 Business Network.
• **: 麻豆原创 was positioned as a Leader for innovations like predictive maintenance and agentic AI through Joule.
• ***: 麻豆原创 was recognized as a Leader for integrating planning, manufacturing, and logistics with advanced analytics and AI.

These accolades aren鈥檛 just badges of honor. They validate the trust our customers and partners place in 麻豆原创 and the impact we deliver together. They also reinforce a critical truth: supply chain excellence is now a boardroom priority.

Sustainability: from obligation to advantage

Sustainability isn鈥檛 just a compliance checkbox; it鈥檚 a competitive edge. More than 25% of global emissions are already taxed or regulated by trading systems. Circularity and carbon accountability have become core KPIs for supply chain leaders because responsible practices deliver measurable benefits. Meeting environmental, social, and governance (ESG) standards lowers regulatory and reputational risk, while optimizing logistics for lower emissions often translates into fewer miles traveled and reduced fuel costs. At the same time, customers and investors increasingly favor brands with transparent sustainability metrics, making it a powerful differentiator in the market.

麻豆原创 solutions help companies measure emissions, enable ESG compliance, and embed sustainability data deep into operational decision-making for procurement, logistics, dispatching, and planning. This turns sustainability into a lever for growth rather than a reporting exercise. In fact, companies recognized in Gartner鈥檚 rankings often cite sustainability as a driver of resilience and profitability. When businesses can prove carbon accountability and circularity, they鈥檙e not just meeting regulations, they鈥檙e building trust and unlocking new market opportunities.

Looking ahead: our 2026 roadmaps

In 2026, our priorities center on enabling supply chains that are more intelligent, more connected, and more resilient. We are deepening our investment in agentic AI to support end-to-end value streams such as integrated business planning, sales and operations execution, digital manufacturing, and logistics execution. The goal is to bring AI directly into processes where decisions are made so planning becomes more predictive and execution becomes more automated. Over time, organizations will entirely redesign workflows and decision-making processes for the true step-change in agentic AI.

We are also advancing our capabilities in supply chain orchestration. As global supply chains operate increasingly across networks, companies need a coordinated layer that unifies planning, procurement, manufacturing, and logistics with partner ecosystems. This year, we will continue strengthening how our solutions identify risks in the n-tier network of complex supply chains by synchronizing data, prescribing decisions and actions across the enterprise and the broader network, and helping customers manage disruptions end鈥憈o鈥慹nd with greater speed and clarity.

Finally, we remain focused on data excellence. Reliable, harmonized data is essential for AI-driven decisions and for orchestrating the supply chain. In 2026, we are continuing to enhance master data consistency, improve network-wide data quality, and support AI鈥憆eady data models that help ensure our customers can trust and operationalize their insights at scale.

Together, these areas form the backbone of the innovations we are delivering this year, with a clear aim of helping customers move from reactive operations to intelligent, proactive orchestration. But technology alone isn鈥檛 enough. The real magic happens when we collaborate with our customers and our partners, turning complexity into opportunity.

The takeaway: 2026 is about action at scale

The supply chain landscape is evolving faster than ever. Agentic AI, sustainability, and intelligent automation aren鈥檛 optional, but essential. Companies that embrace these technologies to truly evolve how they operate and take even complex decisions will lead in resilience, efficiency, and responsibility. Those that hesitate risk falling behind in a world where adaptability is the ultimate competitive advantage.

Don鈥檛 wait for disruption to force your hand. Build the capabilities now that will carry you through uncertainty and position you for growth. Learn more about 麻豆原创鈥檚 AI-powered solutions .

Dominik Metzger is president and chief product officer of 麻豆原创 Supply Chain Management.

*, November 2025, IDC #US53010225
**, December 2025, IDC ID # US52977525
***, October 2025, IDC ID# G00826212

At , I moderated a roundtable with supply chain and transformation leaders from Toyota, L鈥橭r茅al, Owens Corning, Ecolab, American Airlines, and Bayer. Across industries, one theme was clear: transformation succeeds when it is grounded in clarity, centered on people, and focused on customer impact.

If you can鈥檛 name the problem, don鈥檛 buy the technology

The most effective transformations begin with a clear articulation of the problem to be solved, the value at stake, and the outcomes expected. Too often, organizations chase new technology simply because it is available or gaining attention, not because it is tied to a specific business need. However, technologies like AI only deliver value when applied to well-defined business challenges.

Tying initiatives to measurable outcomes helps secure leadership alignment and supports change management. Clarity creates focus and helps teams understand why transformation matters. At its foundation, successful transformation rests on three pillars: people, process, and technology, all powered by high-quality data.

AI is only as smart as the network behind it

As supply chains become more complex, multi-tier visibility has moved from a nice-to-have to a requirement. Many of the biggest risks today, including regulatory exposure, disruptions, and cost volatility, originate deep in the supply chain, often beyond direct supplier relationships.

AI has emerged as a powerful enabler, but only when supported by trusted, shared data. More than half of the data needed to drive intelligent supply chains sits outside an organization鈥檚 four walls. Without visibility across trading partners, AI鈥檚 impact is limited.

Standardization also surfaced as a recurring theme during our roundtable conversation. While one-size-fits-all approaches rarely work, excessive customization slows progress and undermines scale. Leading organizations are finding a balance by standardizing where it drives speed and consistency, while allowing flexibility where it creates meaningful value.

Transformation doesn鈥檛 fail on technology, it fails on trust

Technology may enable transformation, but people determine whether it succeeds. Change management remains a critical factor, and even well-designed initiatives can stall if employees do not understand the purpose or feel threatened by the change.

Clear communication, local champions, and ongoing engagement help build trust and momentum. Leaders emphasized the importance of reinforcing that technology is designed to elevate roles by removing manual work and enabling employees to focus on higher-value activities, instead of replacing them. Being honest about what is working, what isn鈥檛, and when to pivot builds credibility and keeps teams engaged over the long term.

Customer-centric supply chains don鈥檛 happen by accident

A significant shift underway is the move from inward-facing efficiency to explicit customer-centricity. Many supply chain organizations historically assumed their work benefited customers without clearly articulating how.

Today, customer impact is a unifying principle. Whether serving consumers, passengers, farmers, or B2B customers, supply chains are increasingly recognized as drivers of experience, reliability, and brand trust.

Customer collaboration is also playing a larger role in transformation. Sharing data and aligning processes across networks creates shared value and unlocks differentiated services. Progress must be communicated in terms customers care about鈥攏ot internal metrics, but outcomes that improve service, speed, and transparency.

What the best transformation leaders do differently

Coming out of our conversation, the strongest transformation leaders shared a few defining traits:

• They pivot quickly when something isn鈥檛 working. Rather than protecting sunk costs or rigid plans, they recognize when assumptions change and adjust course. Speed and adaptability often matter more than perfection.
• They invest in people as intentionally as they invest in platforms. Adoption requires time, training, and leadership attention. Workforce readiness is treated as a core deliverable, not a side effort.
• They celebrate progress. Visible milestones help sustain momentum and reinforce positive behavior throughout a long transformation journey.
• They hold themselves accountable for real value creation. Success metrics are defined early and tracked consistently, whether financial, operational, or customer driven.

Turning ambition into measurable impact

What stood out most from my conversation at NASCES25 was the shared recognition that transformation is no longer optional. Supply chain leaders are embracing bold ambitions, people-centered change, and customer-focused innovation to turn intent into measurable impact.

plays a critical role in this journey by helping organizations connect processes, partners, and data across the value chain to improve visibility, resilience, and decision-making at scale. And beyond the network, helps orchestrate people, processes, and technology end-to-end鈥攅nabling leaders to move from intent to impact with integrated planning, execution, and insights that can drive real operational transformation.

To hear more directly from the leaders shaping this future, I encourage you to watch the and continue the conversation on how supply chains can lead meaningful transformation.

Keith Baranowski is global head of Sales for 麻豆原创 Business Network.

As the business expanded, so did the complexity of its operations and the expectations of its customers. The existing manufacturing development team, focused on small-scale factory applications, found it increasingly difficult to keep up with the pace. The data was often locked in silos or other systems. To address this, Howdens set out to automate and collect data from multiple points across its supply chain. 

Considering off-the-shelf solutions that could be tailored to its needs, Howdens Joinery needed a solution that would continue to evolve with the company. Through a detailed assessment of several manufacturing execution systems (MES), Howdens Joinery decided to replace all outdated manufacturing execution systems with the  solution, making it the heartbeat of its production processes with the help of a featured partner, . 

Reinventing kitchens with an innovative and customer-centric process 

The kitchen has evolved from a simple cooking space into the heart of the home. Knowing this, Howdens Joinery has adapted its offerings to meet the changing needs of its customers. 鈥淭he kitchen market has changed a lot over the years,鈥� says David Peacock, IS Manufacturing System technical lead at Howdens Joinery. 鈥淲e don鈥檛 sell a kitchen; we provide a living space, the central part of their homes.鈥� 

Howdens expanded its range beyond the standard kitchen colors and styles. This approach enables customers to experiment with various colors and styles before making a final decision. 鈥淚t鈥檚 almost like a trial run,鈥� Peacock explains. 鈥淲e can see if a new color is worth adding to our main range. If it鈥檚 popular, we can roll it out on a larger scale.鈥� 

This strategy not only helps customers find the perfect kitchen but also provides Howdens with valuable feedback on what works best. To support this expanded offering, the company invested in a new factory and upgraded paint lines. These improvements enhanced production capacity and equipped the team with new skills and expertise. 

Traditionally, the company made a stock model, but now customers can visit depots and order kitchens in any color and style they want. 鈥淲e have a fast turnaround, with manufacturing and shipping taking just five days,鈥� Peacock says. 鈥淭o make this possible, we updated our entire order strategy and implemented the new system in less than 12 months.鈥� 

By embracing innovation and listening to customer needs, Howdens Joinery has successfully transformed its business to stay ahead in a competitive market, making it easier than ever for customers to get the kitchen they truly want. 

鈥淗aving our own homegrown MES provided us a clear view of what needed to be produced on each production line,鈥� he says. 鈥淚n real time, operators could start or stop orders and receive confirmations. And we continued to add more features and functionalities to our MES.鈥�

Reducing order production lead time from 21 days to 14 days 

Howdens Joinery faced two major challenges as it transformed its approach to kitchen manufacturing. The company sells the individual pieces of a kitchen, such as cabinet doors or shelves, that are ordered separately.听

Highlighting that the company is聽sales order-driven, Peacock further adds,聽鈥淲hen you convert the sales orders into production orders, you get a sort of production order per piece. Tracking this is easier said than done.鈥� Each聽piece follows a specific route through the factory, depending on its shape and the machinery it needs to pass through. Since the company isn鈥檛 selling finished panels that are simply waiting on a shelf, tracking each part and keeping everything together was a great challenge.听

Another major hurdle was managing the concept of process lots. Because of the specific routing required for different components, orders often needed to be split and sent down two separate production routes. These production orders would then be grouped into SFCs (shop floor controls), but this sometimes made the process more complicated rather than simpler. 

鈥淲e are potentially in a one-for-one relationship with the production order, so the SFC number became a bit redundant,鈥澛燩eacock explains. The complexity increased when multiple orders were launched simultaneously.听He adds: 鈥淲e might be launching different production orders at a time, but we did not want in [麻豆原创 Digital Manufacturing] the guys on the shop floor to press start 40 times.鈥澛燭his led the company to create a mechanism for efficiently grouping orders, allowing, for example, all orders of a certain color to be processed together on the same production line.听

鈥淲hen you purchase [麻豆原创 Digital Manufacturing], you鈥檙e not just buying manufacturing, but you’re buying the ability to build a manufacturing landscape. So you can do your own customizations,鈥� he adds. 

With 麻豆原创 Digital Manufacturing, Howdens Joinery enhanced operational efficiency and achieved a supporting mechanism to support both make-to-stock and make-to-order production models. 

Continuous improvement as a key driver for the future of manufacturing 

Howdens Joinery is leveraging diverse technologies in production systems. Particularly as a company expanding its manufacturing capabilities, this requires the integration of IT and operational technology, as well as seamless communication with machinery and the automation of production workflows鈥攕uch as custom 麻豆原创 Business Technology Platform (麻豆原创 BTP) processes and production connectors.听聽

With this integration, Howdens Joinery achieved direct communication with various types of machinery, thereby enhancing production efficiency and reducing the need for manual intervention. 

鈥淲ith 麻豆原创 Digital Manufacturing, we gained operational excellence in our supply chain processes, leading to more efficient planning and an enormous increase in production. We reduced order production lead time from 21 days to 14 days in 2023 to 2024, contributing to faster customer fulfillment,” Peacock says.

Moreover, Howdens achieved a 99.98% service level from primary sites to depots in 2024, demonstrating near-perfect product availability. “We will continue this journey of continuous improvement to deliver the best products for our customers,鈥� he says. 

The innovative manufacturer plans to replace its legacy MES systems with a fully digital manufacturing solution, ensuring streamlined and efficient operations. With robust data quality and a flexible approach to integrating new technologies, Howdens Joinery is planning to integrate AI into its manufacturing processes as the next step. Its proactive approach to utilizing new technology for operational excellence is a great industry example for the broader manufacturing community.  

To learn more about Howdens Joinery’s transformation story, check out the full customer story .听

Oyku Ilgar is part of 麻豆原创 Supply Chain Management Thought Leadership & Awareness.

Headquartered in Homberg (Ohm), Germany, with worldwide locations, in 2024 KAMAX generated 鈧�1 billion in revenue and employs 4,000 people dedicated to serving OEMs globally.

To maintain its competitive edge, the ambitious company embarked on a transformative journey to streamline its supply chain through digitalization and intelligent logistics management. This transformation centers around the deployment of (麻豆原创 EWM),  (麻豆原创 TM), and a comprehensive 麻豆原创 S/4HANA platform, supporting superior logistics efficiency, transparency, and sustainability.

Optimizing logistics at scale

Handling approximately 400 transports daily across multiple global plants, KAMAX manages two distinct logistics flows: goods pre-packed and stored in warehouses, and a “pack-to-order” system where items are packaged just before shipment. Currently, three plants operate on 麻豆原创 S/4HANA with 麻豆原创 Extended Warehouse Management and one pilot plant with 麻豆原创 Transportation Management integrated, while others are transitioning from 麻豆原创 ERP Central Component (麻豆原创 ECC).

The implementation of the advanced shipping and receiving process dramatically improved logistics transparency and efficiency.

“The use of the unified package builder, which leverages real data instead of estimates, allows us to provide precise shipping information to freight forwarders earlier in the process,” Jens Hoidem, director of IT Business Solutions at KAMAX, explained. This improvement enhances truck planning and communication with carriers, positively impacting the company’s logistics operations daily.

KAMAX collaborates exclusively with freight forwarders, working with approximately 20 carriers globally. At the advanced shipping and receiving pilot plant, about 60 deliveries per day are coordinated, involving around 2,000 handling units across five to six trucks. This network supports operational responsiveness without compromising control.

On premise today, cloud-ready tomorrow

Currently, three of KAMAX鈥檚 plants run on 麻豆原创 S/4HANA, with the remaining plants on 麻豆原创 ECC, all on an on-premises basis designed to be cloud-ready for future transitions.

Hoidem pinpointed the critical process improvements brought by advanced shipping and receiving in combination with 麻豆原创 Extended Warehouse Management and 麻豆原创 Transportation Management: 鈥淭he shipping registration now uses the unified package builder, relying on accurate, real data rather than estimated figures. This has substantially improved truck planning and early communication with our freight forwarders, impacting around 60 deliveries and about 2,000 handling units daily at our pilot plant.鈥�

Over 95 percent of KAMAX’s transport is by truck. “We maintain a global footprint close to our OEM customers to optimize delivery times and costs,鈥� Hoidem added. 鈥淲e currently engage about 70 to 80 different freight forwarders worldwide, facilitating diverse and dynamic transport needs.鈥�

Sustainability and process automation

KAMAX has a bold strategy for sustainability and aims for carbon neutrality by 2037. Implementation of 麻豆原创 Extended Warehouse Management and 麻豆原创 Transportation Management plays a crucial role in supporting KAMAX’s goal by enabling better route planning, efficient truck utilization, and minimizing empty runs.

鈥淩educing CO2 emissions through smarter transport management is a key project outcome,鈥� Hoidem added.

The German company is also actively advancing in automation. In China, KAMAX has piloted RFID technology integrated with automated guided vehicles (AGVs) to automate intra-logistics, reducing manual labor and enhancing productivity.

the company’s digital subsidiary, has developed an Operator Cockpit linked with 麻豆原创 Extended Warehouse Management for real-time monitoring and automated production order management. Using laser technology, KAMAX automated piece counting, saving about 40 labour hours in May at their Slovakian plant across 1,200 containers.

KAMAX plans to roll out 麻豆原创 Extended Warehouse Management, 麻豆原创 Transportation Management, and advanced shipping and receiving across all seven plants, progressively improving automation and digitalization of intralogistics processes. 鈥淲e aim to integrate AI for advanced receiving and transportation management, continuing to optimize costs and capacity,鈥� Hoidem shared.

Curious about how KAMAX鈥檚 journey to streamline and future-proof its supply chain? .

That鈥檚 why I鈥檓 super proud to share that 麻豆原创 has been named a Leader in .* This marks the second time 麻豆原创 has received this recognition, following our position as a Leader in the 2023 IDC MarketScape.**

We believe this distinction reflects the strength of 鈥攐ur entry in the MESCCN space鈥攁nd the trust placed in the solution by companies around the world. It鈥檚 a milestone that underscores our commitment to helping businesses navigate complexity and build more connected, intelligent supply chains.

A legacy of collaboration

麻豆原创 Business Network is the world鈥檚 largest B2B trading partner platform, supporting more than US$6.5 trillion in annual transactions. It can modernize how procurement and supply chain processes connect across companies, helping build stronger, more resilient supply chains and deliver on the customer promise.

The network traces its roots back to the Ariba Supplier Network, founded in 1996. Over the years, it has evolved to support a broad range of supply chain processes. In 2021, we unified our capabilities under the 麻豆原创 Business Network brand, bringing together logistics, asset management, finance, sustainability, and talent-based networks into a single, comprehensive platform.

Today, millions of companies across 190 countries rely on 麻豆原创 Business Network to digitalize transactions, share information, and discover trading partners. By leveraging AI and configurable business rules, the network helps close break points between buyers and suppliers鈥攅nabling greater visibility, operational efficiency, and compliance across the supply chain.

What the IDC MarketScape recognized

According to the IDC MarketScape, 麻豆原创 Business Network鈥檚 positioning as a Leader is supported by several competitive strengths:

• Comprehensive product features and road map: 麻豆原创 Business Network offers an extensive range of features and functionality, covering all major B2B collaboration categories, including indirect and direct materials, MRO, logistics, finance, services, and sustainability. The network’s robust future road map enables continuous innovation, empowering businesses to stay ahead in a dynamic landscape.
• Seamless integration and extensibility: The network demonstrates capabilities in integration, connecting 麻豆原创 ERP, procurement, and supply chain modules while extending to other ERPs, customer applications, and cutting-edge technologies such as machine learning, AI, and blockchain.
• Global reach and real-time collaboration: 麻豆原创 Business Network enables trading partners to collaborate in real time across the globe across a wide breadth of business processes.
• Automation through configurable business rules: 麻豆原创 Business Network empowers businesses to automate essential processes by working to define and customize rules tailored to their specific needs. These configurable rules can streamline workflows, enforce compliance, and boost operational efficiency, reducing manual intervention.
• Robust foundation and ecosystem: 麻豆原创 Business Technology Platform (麻豆原创 BTP), combined with the broader 麻豆原创 ecosystem, can provide a scalable and extensible secure foundation for seamless integration across procurement, supply chain, and finance processes.

We believe these strengths, as recognized by the IDC MarketScape, reinforce the value 麻豆原创 delivers to organizations seeking to extend their business processes across the entire value chain.

Continuing to innovate on 麻豆原创 Business Network

We believe this recognition by the IDC MarketScape reflects not only the strength of 麻豆原创 today but also our commitment to ongoing innovation. We鈥檙e continuously enhancing the network to help companies collaborate more effectively, respond faster to change, and unlock new sources of value across their supply chains.

At 麻豆原创 Connect, we shared how 麻豆原创 Business Network is evolving to meet the demands of increasingly dynamic and interconnected business environments. Built on 麻豆原创 Business Technology Platform, the network now offers a scalable data foundation, seamless integration with 麻豆原创 Cloud ERP capabilities and third-party systems, and enhanced workflow customization through 麻豆原创 Build solutions. This has enabled many innovative initiatives to incorporate Joule across the network, reimagining analytics, automation, and approvals with intelligent capabilities that will be continuously released starting in 2026. 

We鈥檙e also further expanding integration with 麻豆原创 Cloud ERP, 麻豆原创 Ariba solutions, 麻豆原创 Fieldglass solutions, and 麻豆原创 Transportation Management to support end-to-end value streams. These enhancements can help streamline supplier onboarding, accelerate issue resolution, and improve sustainability tracking, empowering businesses to operate with greater agility and confidence.

Empowering businesses to realize the full value of collaboration

As multi-enterprise collaboration continues to evolve, we see tremendous opportunity to help organizations unlock new levels of agility, visibility, and efficiency. At 麻豆原创, we鈥檙e focused on making this journey as seamless and rewarding as possible.

Across industries, customers are already seeing the impact. , a leading aerospace manufacturer, is using 麻豆原创 Business Network Supply Chain Collaboration to improve visibility and responsiveness across its supplier ecosystem. Similarly, , one of the world鈥檚 largest aircraft manufacturers, is leveraging 麻豆原创 Business Network to streamline procurement and supply chain processes, enhancing operational agility and supplier engagement.

We鈥檙e investing in education, enablement, and intuitive user experiences to support companies as they expand their collaborative networks. Whether you鈥檙e a manufacturer, services provider, or supplier, our goal is to empower you to connect, collaborate, and grow with confidence鈥攍everaging the full potential of 麻豆原创 Business Network to help drive strategic outcomes across your value chain.

A strategic choice for the future

If you鈥檙e looking for a partner that offers both a robust multi-enterprise network and deep supply chain and procurement capabilities, 麻豆原创 is the clear choice. Our unmatched integration with core 麻豆原创 and non-麻豆原创 applications, combined with our strategic vision and global reach, makes us uniquely positioned to support your transformation.

As I shared in my recent article, we鈥檙e entering a new era of supply chain management鈥攐ne defined by connected ecosystems, intelligent automation, and sustainable growth. 麻豆原创 Business Network is at the heart of this transformation, helping businesses turn complexity into opportunity.

To our customers, partners, and the entire 麻豆原创 community, thank you for your trust and collaboration. We believe this recognition from the IDC MarketScape is a shared achievement, and we鈥檙e excited to continue building the future of supply chain commerce together.

To learn more, visit  and read the IDC MarketScape excerpt .

Dominik Metzger is president and chief product officer for 麻豆原创 Supply Chain Management.

*Source: , November 2025, IDC #US53010225.
**Source: IDC MarketScape: Worldwide Multi-Enterprise Supply Chain Commerce Network 2023 Vendor Assessment, December 2023, IDC #US49948423.

With the proliferation of software review platforms, customers now have the power to influence purchasing decisions by sharing their authentic experiences. Recent trends show that businesses that are prioritizing customer satisfaction are not only thriving, but also setting new industry standards.

(麻豆原创 IBP) has emerged as the clear leader in supply chain planning among customers. This recognition is consistently reflected across major software review platforms: , , and . The overwhelming support underscores the leadership of 麻豆原创 IBP and validates 麻豆原创鈥檚 commitment to delivering exceptional value to our customers.

Recent success at the 麻豆原创 Connect event in Las Vegas, where we introduced supply chain planning reimagined, has catapulted 麻豆原创 IBP to the forefront of the industry. It now leads in customer satisfaction across all major review platforms.*

Key insights and expert perspective

Gartner Peer Insights: Industry-Leading Performance

• 麻豆原创 IBP current rating: 4.8/5.0 (based on 51 reviews in the past 12 months)
• Market position: No. 1 rated in category

Our 4.8 rating on , a highly influential enterprise software review platform, reflects exceptional customer satisfaction and implementation success. This combination provides unmatched credibility in competitive situations and clear validation of the leadership position of 麻豆原创 IBP.

TrustRadius: Trusted and Top Rated

• 麻豆原创 IBP current rating: 8.4/10 (107 reviews)
• Recognition: 2026 Buyer鈥檚 Choice Award (announcement pending)
• Market position: Highest-rated in category

Winning the TrustRadius Buyer’s Choice Award for 2026 validates our customer-centric approach and reinforces our market leadership. The substantial base of 107 reviews provides statistical credibility and demonstrates a clear differentiation in customer experience.

G2: Recognized Leader

• 麻豆原创 IBP current rating:聽4.3/5.0 (251 reviews)
• Category status: Leader designation
• Market position:聽Highest-rated among major competitors

Being recognized as a Leader in G2’s Demand Planning Grid reflects the position of as a top-three solution in the Demand Planning category, backed by 251 customer reviews. This volume of authentic customer feedback is particularly valuable for prospects conducting due diligence.

These achievements are a testament to our dedication to excellence and customer satisfaction. We are deeply grateful for the trust and support of our customers. As we move forward, we remain committed to innovating and delivering industry-leading solutions that meet and exceed customer expectations. Stay tuned for more exciting developments and advances in supply chain planning as we continue to redefine the market together.

*Review data as of November 5, 2025

Few industries feel this dual pressure more than American candy makers, particularly during this year鈥檚 Halloween season — their single most important sales moment of the year.

Unfortunately, this year the spookiest season proved to be a particularly tricky one. According to , candy prices rose by 17% from 2024 to 2025. Price increases pose a threat to legacy brands, as 26% of American consumers say they can no longer afford brand loyalty, according to the .

For confectionery manufacturers that have long relied on emotional connection and nostalgia to sustain sales, this Halloween season created pressures on the front- and back-end, leading to what鈥檚 effectively called the 鈥淐PG squeeze.鈥�

Yet, there鈥檚 still room for optimism. The bottom line is that consumer demand hasn鈥檛 disappeared; it鈥檚 simply evolving. While this Halloween season presented a scare, candy makers can prepare for upcoming moments like the holiday season and Valentine鈥檚 Day by integrating financial, commercial, and supply chain planning as well as by connecting sourcing, production, logistics, marketing, and retail.

Supplier side reality

Behind the fun-size bars and Halloween packaging, U.S. candy makers grappled with operational headwinds this year. Volatile trade policy made ingredient and packaging costs unpredictable, while global disruptions reverberated through supply chains.

In anticipation, manufacturers stockpiled inventory and restructured supplier networks, tying up working capital and putting additional stress on already thin margins. The loss of supplier stability has also become a defining feature of today鈥檚 CPG landscape: 70% of companies report switching suppliers primarily due to cost considerations, and fewer than one in four (22%) have maintained supplier relationships longer than five years, according to .

For candy makers dependent on commodities like sugar, cocoa, and dairy, these disruptions hit particularly hard. Add that to the growing costs of packaging, transportation, and marketing, and even iconic brands found themselves squeezed from all sides.

Cautious consumers and the erosion of loyalty

On the consumer front, the loyalty that once defined relationships with classic candy brands began to show signs of strain. That鈥檚 bad news for staple brands that have long relied on customers who instinctively reach for the same branded candy every Halloween.

At the same time, social media has amplified product discovery. Trends can shift overnight, and a viral post about a new flavor or an unexpected candy collaboration can sway younger buyers instantly. For established brands, loyalty must now be earned continuously.

Halloween was one example of this shift, but we鈥檙e going to see families purchase fewer products or mix traditional favorites with lower-priced alternatives in the future as Americans continue to tighten their budgets. Meanwhile, retailers will face uncertain demand and fluctuating supplier costs, leading to a greater risk of stockouts. These trends highlight why CPG companies need smarter, more connected planning to stay ahead of shifting consumer behavior.

Stopping the squeeze with end-to-end connected planning

The effect of the CPG squeeze during this Halloween season offers candy makers valuable lessons before future moments of peak demand. Companies that continue to operate with fragmented data risk missing critical insights, whether it鈥檚 an emerging cost spike, a change in trade policy or a social trend that could make or break sales.

That鈥檚 why CPG companies must embrace end-to-end business planning, a holistic approach that aims to enable agility, transparency and collaboration across every stage of the value chain, through the following methods:

1. Integrated supply and demand planning

Using AI-driven analytics and real-time data, companies can more accurately balance supply and demand, ensuring they produce the right amount of product at the right time. For candy makers, that means having adjusted holiday production runs in response to early season buying trends or ingredient cost shifts.

This model helps connect supplier, logistics, and retail data streams, allowing teams to react instantly to cost spikes or sales slowdowns — helping CPGs improve forecast accuracy for tomorrow鈥檚 disruptions today.

2. Collaborative commercial and promotions planning

Integrating sales, marketing and trade promotion data with supply and finance planning helps maximize promotional ROI. that 68% of CPG companies are simplifying or otherwise improving their organizational structure to improve coordination between teams, leading to fewer out-of-stocks and stronger seasonal performance.

To make these efforts more effective, companies must turn to revenue growth management as a strategic link between planning and execution. By connecting ROI, volume, and profit and loss data, ensures promotions are timed and tailored to shopper needs. This approach supports customer retention, attracts new buyers, and helps maintain healthy margins.

The coordination of holiday campaigns, shelf placements, and promotional pricing with a unified view of inventory and demand is crucial. Rather than running separate marketing and logistics calendars, teams must collaborate around a single version of truth,聽ensuring the product featured in a viral ad is available on shelves.

3. Financial planning and scenario modeling

End-to-end planning also allows companies to simulate 鈥渨hat-if鈥� scenarios by modeling policy changes, supply shortages, or demand surges to test resilience. For example, a candy maker facing a 10% increase in imported cocoa costs can immediately assess how to reallocate budgets through promotional adjustments, sourcing alternatives, or margin management.

With real-time connectivity across teams, financial forecasts can automatically update as assumptions shift, empowering decision-makers to pivot fast.

Turning pressure into opportunity

The 鈥淐PG squeeze鈥� wasn鈥檛 just a momentary market condition; it鈥檚 a structural shift that will reshape how candy makers and other CPG brands operate for years to come.

Halloween this year delivered more tricks than treats for American candy makers. Rising costs, shifting loyalties and supply challenges exposed the fragility of traditional planning models. To weather the holidays ahead, all CPGs must embrace integrated planning models that connect every part of the value chain.

With greater visibility and agility to anticipate change and respond to consumer demand, CPG brands can make every holiday a little sweeter.

Jon Dano is an industry executive advisor for Consumer Products at 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

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See how 麻豆原创 Logistics Management helps companies run smarter, faster, and more connected logistics operations.

Discover 麻豆原创 Logistics Management鈥斅槎乖粹�檚 new, cloud-native solution designed to orchestrate and optimize logistics operations across the entire supply chain. In this video, you鈥檒l see how one customer uses 麻豆原创 Logistics Management to transform a small warehouse into a smart, connected logistics hub. With built-in AI, automation, and real-time insights, the customer has achieved seamless coordination between people, systems, and assets鈥攊ncreasing productivity, accuracy, and responsiveness. 麻豆原创 Logistics Management brings together order orchestration, transportation, and warehouse management into one intelligent platform. From inbound to outbound, the solution provides end-to-end visibility and real-time decision-making, helping organizations scale efficiently and respond dynamically to change. Launched on October 7, 麻豆原创 Logistics Management empowers businesses to:

• Orchestrate operations across multiple logistics functions with AI-driven insights.
• Automate manual workflows to help improve speed, accuracy, and resource utilization.
• Gain real-time visibility into performance, inventory, and delivery execution.
• Accelerate digital transformation with a cloud-native, scalable foundation on 麻豆原创 Business Technology Platform (麻豆原创 BTP).

Whether managing a local warehouse or a global network, 麻豆原创 Logistics Management can enable organizations to move from reactive logistics to proactive orchestration, turning complexity into competitive advantage.

Learn more about 麻豆原创 Logistics Management and how it can help you run logistics operations smarter and faster:

Through their innovative implementation of Soley’s Product Mining Platform with 麻豆原创’s supply chain management technologies, they prove that sustainability and profitability can go hand in hand.

The challenge: managing complex product portfolios at scale

CERATIZIT Group, a leading provider of hard material solutions for machining and wear protection, faced a challenge common to many modern manufacturing companies: managing a complex product portfolio with over 65,000 products. The company’s Cutting Tool Solutions division needed a solution to balance economic and ecological objectives while maintaining competitive advantage.

Klaus Lupfer, product lifecycle manager at CERATIZIT Deutschland GmbH, explains the company’s motivation: “In addition to the economic perspective on the product portfolio, the ecological aspect was equally important when partnering with Soley. As a company committed to sustainability for years, we are especially excited about the opportunities that the expansion of product carbon footprint data offers.”

The challenge was not just the product portfolio’s size but also the lack of transparency regarding product performance and sustainability metrics. Employees spent considerable time compiling reports rather than making strategic decisions, while limited insights into critical materials and suppliers prevented efficient phaseout of high-emission products.

AI-powered product portfolio analysis

Munich-based Soley GmbH, a past participant in the 麻豆原创.iO program, 麻豆原创鈥檚 former startup accelerator designed to foster and integrate innovative solutions into the 麻豆原创 ecosystem, developed an innovative response to this challenge. The Soley Product Mining Platform, available as part of 麻豆原创’s extension and add-on solutions, transforms complex product data into actionable insights through three core, AI-driven innovations that enable faster, smarter, and more impactful business decisions.

• AI Advisor uses AI to recommend precise actions鈥攆or example, suggesting which products should be phased out to minimize carbon footprint without sacrificing margins.
• AI Assistant provides an intuitive, natural-language interface that allows users to effortlessly interact with Soley, without requiring deep technical expertise.
• AI Detective analyzes data to uncover hidden dependencies and reveal strategic opportunities, such as identifying which configuration options should be eliminated to optimize both profitability and sustainability.

The Soley Product Mining Platform draws data from 麻豆原创 S/4HANA and 麻豆原创 Business Warehouse, utilizing 麻豆原创 Business Technology Platform (麻豆原创 BTP) as the service layer. 麻豆原创 Datasphere helps consolidate 麻豆原创 data and analytics, while 麻豆原创 Analytics Cloud provides the analytics that form the core of the AI model. This technical architecture enables intelligent data extraction and transformation through 麻豆原创 Databricks, while massive graph analytics enable complex dependency analysis.

“With these 麻豆原创 solutions, we’re delivering a true game changer for the sustainability of the high tech and manufacturing industries,” says Ephraim Triemer, shareholder and advisor of Enterprise Accounts at Soley. “For the first time, our customers can go beyond ESG reporting and take real action鈥攄riving sustainability while staying laser focused on profitability.”

Seamless 麻豆原创 integration creates value

By combining CERATIZIT’s Product Carbon Footprint (PCF) data with financial metrics, the Soley Product Mining Platform creates a digital twin that uncovers opportunities, identifies risks, and analyzes product hierarchies, bills of materials, and carbon footprints. With AI-driven intelligence guidance, Soley developers ensure the platform’s capabilities enable decisions and outcomes that improve both profitability and environmental stewardship.

Earlier this year, Dominik Metzger was appointed as president and Chief Product Officer of 麻豆原创 Supply Chain Management, bringing a renewed focus on resilience, sustainability, and intelligent automation.

鈥淢y chief priority is to ensure that we help customers not only respond to disruptions but also proactively prepare and act,鈥� Metzger said. 鈥淲e can do so by leveraging AI, generative AI, real-time data, and predictive analytics with the power of 麻豆原创鈥檚 technology. Our vision is to build an autonomous supply chain鈥攃onnected, contextualized, and collaborative.鈥�

麻豆原创 SCM leadership driving transformation

The analysis delivered impressive, measurable results that demonstrate the power of combining AI-driven analytics with 麻豆原创 technologies. CERATIZIT discovered an 87% implementation rate of suggested measures, driving product sustainability and supply chain optimization. Simultaneously, the company identified a reduction of over 30% in end-of-life “ballast” products with negative carbon footprints while creating 100% transparency in sustainability data across all elements, product sets, and aggregation levels.

Alexander Springer, CEO of Soley GmbH, explains the strategic significance: “If you know which products are the most critical to the overall success of your business, you can focus on safeguarding the value chain for those products, taking proactive steps to avoid any potential supply risks.”

A model for sustainable digital transformation

The successful partnership between CERATIZIT, Soley, and 麻豆原创 demonstrates how modern companies can achieve both economic and ecological goals through intelligent use of data and AI. The combination of proven 麻豆原创 technologies and innovative analytics solutions creates measurable value for companies of all sizes. For other 麻豆原创 customers and partners, this example shows that sustainability and profitability need not be opposing forces鈥攚ith the right technologies and partners, both objectives can be achieved simultaneously.

Learn more about the latest updates to 麻豆原创 supply chain management. The Soley Product Mining Platform is available on .

Visibility has always been essential for navigating uncertainty in business-to-business commerce. Yet it is also insufficient. After all, what good is merely seeing across the various tiers of the supply chain if a business lacks the ability to identify available alternatives, shift course immediately, and counter disruption before it impinges on the balance sheet?

At , our customers and partners had an extraordinary opportunity to explore our latest 麻豆原创 Business Network innovations鈥攁nd the generative and agentic AI solutions that are rapidly reshaping enterprises鈥� ability to extend N-tier visibility and take the decisive actions necessary to preserve the smooth flow of operations from the dual threats of volatility and risk.

To strengthen every link in the supply chain, businesses need to connect their mission-critical operational processes with those of their trading partners. Doing so enables them to achieve transparency, foster collaboration, drive efficiency, and maximize customer satisfaction. Through the vast troves of operational data that millions of trading partners accumulate in the routine course of day-to-day operations, 麻豆原创 Business Network鈥攖he world鈥檚 largest business-to-business platform鈥攊s uniquely positioned to help business leaders orchestrate their supply chains for success, no matter the circumstances.

Today, 麻豆原创 helps our customers to accomplish these objectives with a suite of AI-infused supply chain management applications鈥攁ll of them integrated with ERP and adjacent line-of-business applications to connect seamlessly with trading partners. By applying advanced analytics, operational insights, predictive signals, and recommended actions derived from both internal and external data sources, 麻豆原创 Business Network has set in motion an increasingly autonomous supply chain.

The innovations underlying it, meanwhile, are accelerating.

To further distinguish 麻豆原创 as the leader in enabling supply chain orchestration, I am extremely excited that in the first half of 2026 we will deliver a new product to help provide enterprises with capabilities for issue detection, insight, and action across their supply chains. Aptly called 麻豆原创 Supply Chain Orchestration, this new solution will help deliver N-tier insights and transform external and internal signals across supply chains into prioritized actions. These capabilities will rest on the 麻豆原创 Business Network foundation, drawing upon master data as well as native AI solutions to help orchestrate workflows and dramatically expand visibility across every tier of the supply chain.

麻豆原创 Supply Chain Orchestration can equip our customers with the tools and inference-driven insights they need to help mitigate multi-tier risk, enhance compliance, and bolster decision-support. The goal is to head off disruption before it arises鈥攁nd to offer our customers one of the most elusive yet priceless advantages that anybody can have in these turbulent times: peace of mind.

That鈥檚 why our customers entrust so many of their core operational processes to 麻豆原创 Business Network in the first place: for peace of mind, for resilience, for enduring value. Our strategy to deepen that value takes root in our ongoing transition to 麻豆原创 Business Technology Platform (麻豆原创 BTP), working to provide faster speeds, easier integration, faster collaboration, and continuous innovation on a grand scale, across industries. Our vision takes shape through intelligent applications, network convergence, and unmatched extensibility. Our priority to accelerate the value we make available to suppliers on the network finds example through our innovations that help simplify e-invoicing, expand automation, and facilitate discoverability by new potential trading partners. All these strategic elements take center stage in our product strategy, each of them strengthened by the unmatched generative and agentic AI capabilities that customers and partners have come to rely on from 麻豆原创 in our quest to make the world run better and improve people鈥檚 lives.

Couldn鈥檛 join us in Las Vegas? Check out the Supply Chain Connect at 麻豆原创 Connect Virtual keynote session, 鈥�,鈥� presented by Dominik Metzger, president and chief product officer, 麻豆原创 Supply Chain Management.

J枚rn Keller is executive vice president and chief product officer for 麻豆原创 Business Network.

The manufacturer was heavily reliant on manual documentation, which caused delays in accessing and updating critical data and documents, resulting in data quality and compliance issues.

To address these challenges and optimize asset management, LESER sought to establish seamless data integration through a unified single source of truth. After thorough research and careful comparison of options, the valve manufacturer successfully chose to implement digital twin technology with to help optimize collaboration with customers.

Error-free asset data and streamlined collaboration with smart asset management

Relying on a manual documentation process was not only time-consuming but also prone to errors and delays. This was causing significant challenges in accessing and updating critical data and documents, leading to poor data quality and inefficiencies across the ecosystem. Recognizing the need for a modern solution on the operator side, LESER identified the importance of supporting customers with a centralized asset management system. LESER decided to digitize its asset management system by implementing a centralized, cloud-based platform. This platform enables LESER to seamlessly share the digital twin with customers, enhancing transparency and data sharing while continuing to manage internal processes separately.

By implementing the technology integrated with , LESER created a one-to-one virtual replica of each piece of physical equipment and product, consolidating all relevant data and documentation into a single, accessible platform.

鈥淭he digital twin acts as a precise digital mirror of the physical safety valve, enabling our customers to receive complete, error-free, and up-to-date data about the safety valves,鈥� Pierre Draheim, manager of Product Data Management at LESER, explains.

LESER provides digital twins both for new () and existing () safety valves, centralizing all relevant data and documents. Each valve is labeled with the globally-standardized ID link, or QR code, IEC聽61406聽that allows LESER’s customers to directly access and sync product-specific information with their asset management systems, enabling seamless data transfer, documentation compliance, and cost reductions of up to 95% for initial recording.

鈥淏y embracing digital innovation, we have empowered our customers to boost their operational efficiency,” Draheim says. He emphasizes that this not only helps LESER achieve substantial time-savings but also enables the company to focus on core activities and drive greater business growth: “It’s a win-win. Not only us, but also our customers achieve significant improvements in overall productivity.”

Reduce operational costs with real-time digital twin integration

Automating valve data sharing within has made it much easier for LESER operators and service providers to coordinate maintenance, eliminating the need for manual data reconciliation. This automation cuts down on administrative work, helps avoid unnecessary downtime, and optimizes spare parts inventory, all of which contributes to a substantial decrease in operational costs.

By standardizing and digitizing data with a globally-standardized ID link, multiple service providers get instant access to accurate, up-to-date information.

鈥淲ith the introduction of the digital twin and 麻豆原创 Business Network Asset Collaboration, we can now automate valve management, making the entire process faster and more reliable,鈥� Draheim says.

Ensure safety and quality through global and regulatory compliance

Making sure safety valves meet international standards at every step requires a high level of automation in managing product data. This is especially important for LESER. 鈥淐ompliance is not just about meeting regulations, but about the ‘rules of the game’ in the industry, which enable an automated exchange of information across different IT systems and stakeholders,鈥� Draheim says.

With such a significant market presence, LESER holds its suppliers and materials to very high standards, ensuring every part complies not only with global regulations but also local rules. This level of care is particularly essential for operators working in industries with strict safety and regulatory conditions.

Beyond setting these standards, LESER keeps detailed records to maintain full transparency and traceability across the supply chain. This integrated approach helps the ambitious company reduce the need for additional level approvals and supports safe, reliable plant operations all over the world. In return, its customers experience improved reliability and confidence in the products and services they receive, creating a positive impact throughout the entire value chain.

Oyku Ilgar is part of 麻豆原创 Supply Chain Thought Leadership & Awareness.