Through a burgeoning array of novel applications, businesses are turning to AI to dramatically expand the value they can create for their customers. Often, such applications involve optimizing internal processes: the data, the workflows, the controls managed inside the four walls of a business. But equally important is the value that AI can help to realize beyond those walls, through collaborative relationships with buyers, suppliers, and other key stakeholders. A firm, after all, is only as successful as its ability to manage spend, suppliers, and risk across its ecosystem. This is why the touchpoints between trading partners鈥攖he digital networks through which day-to-day operational and transactional data flow up and down the supply chain鈥攈old immense potential to unlock value as businesses increasingly become .

Business networks form an interdependent system within which buyers, suppliers, procurement organizations, service providers, financial institutions, and AI agents coordinate decisions, foster collaboration, and deter disruption. As the world鈥檚 largest business-to-business marketplace, facilitates over US$8 trillion in commerce annually across more than 940 million transactions as of the 12 months ending the third quarter of 2026. Aided by an expanding set of AI agents, the network can contextualize vast troves of operational data to help carry out desired tasks within strict parameters set by businesses seeking to manage risk, ensure compliance, and extend competitive advantage. If enterprise resource planning solutions can be thought of as an organization鈥檚 central nervous system, then cloud-based business networks comprise the connective tissue between enterprises seeking to manage spend, facilitate collaboration, and optimize procurement and invoicing processes.

The vision of 麻豆原创 Business Network is to become the intelligence and execution layer for commerce between companies, transforming the market from fragmented, point-to-point collaboration toward a connected ecosystem in which buyers, suppliers, logistics providers, and asset operators can anticipate change and coordinate decisions in real time. By combining the trusted business processes of with multi-enterprise network data, , and , 麻豆原创鈥檚 AI solution embedded across company systems and extensible across non-company systems, 麻豆原创 Business Network can enable increasingly intelligent, predictive, and autonomous processes across sourcing, procurement, supplier management, and finance.

Some of the greatest opportunity to harness value from cross-enterprise AI solutions lies in managing spend and supply chains. Consider, for example, the complexities and costs involved in , where a manufacturer must balance revenue, service levels, inventory, and production constraints across multiple parties in real time. To do so, the business runs simulations to surface recommendations for alternative configurations, sourcing strategies, or distribution scenarios, all in hopes of averting disruption that could affect buyers, suppliers, or end-user customers.

Years ago, such efforts might have proved unreliable owing to sheer complexity or, worse, fragmented data. But when paired with trading partners鈥� synchronous operational data converging through business networks, AI can not only produce actionable recommendations but can carry them out with precision and within specified parameters. It can even prompt crucial questions that businesses may have neglected to consider before previously undetected vulnerabilities have the chance to imperil mission-critical processes. When trading partners achieve end-to-end process transparency via the cloud, the intelligence and insights available to them increase exponentially, as do the efficiencies that result.

Yet it bears noting that the capabilities made possible by agentic AI neither replace nor diminish the importance of human involvement. When the C-suite leaders responsible for spend management and supply chain strategy evaluate autonomous solutions, governance emerges consistently as a top priority. To ensure accountability and oversight at every link of the supply chain, a business-to-business platform must offer agentic solutions that operate strictly within an organization鈥檚 authorized guardrails and internal controls. For compliance and audit purposes, it must also document the various factors that contribute to shaping each automated transaction. Transparency, after all, breeds trust, which in turn spurs adoption at scale.

As automated solutions take on a greater share of tactical tasks and routine processes鈥攕uch as generating demand forecasts, processing purchase orders, optimizing shipment schedules, streamlining warehouse operations, and the like鈥攕trategic judgment remains the undisputed province of supply chain and spend management professionals. Because all of the foregoing types of process data weave their way through business networks, they become the ideal fabric on which to embroider agentic AI capabilities.

The age-old problem in supply chain management posed by fragmented data residing on siloed, or even incompatible, systems falls away when core operational data intersects in the cloud at the business network layer. Such networks deliver not only a comprehensive view of the supply chain but also the agentic AI capabilities necessary to avert disruption, mitigate risk, and foster strategic collaboration among trading partners. By relying on operational data both contemporaneous and historical, business networks deliver the context within which enterprises can apply AI solutions reliably to solve many of their toughest operational challenges鈥攁nd to strengthen their trading relationships for long-term mutual success.

Learn more about and .

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

In Q3, we expanded our portfolio of Joule Assistants and introduced dozens of specialized agents that help customers move beyond isolated tasks toward connected, end-to-end execution. The value of AI has always been about what it accomplishes for our customers. Our recent releases help them streamline processes, increase productivity, and build more resilient operations.

Joule is 麻豆原创鈥檚 portfolio-wide AI engagement layer, combining agentic capabilities with 麻豆原创 business applications to help organizations become an Autonomous Enterprise. Through Joule Work, the new UI for AI, people describe what they want to achieve, get relevant insights, build app-less spaces personalized to their needs, and take action across connected business systems. When it鈥檚 time to execute, Joule Work selects the right Joule Assistant for the job. These assistants act as domain experts, bringing knowledge of roles and processes to the task at hand. They orchestrate specialized Joule Agents to execute tasks, using business context and data, respecting established authorizations, and maintaining audit trails. People set the direction, assistants coordinate agents, and agents carry out work with proper oversight and governance.

For example, billing teams can create invoices, identify anomalies, and resolve posting errors with the Billing Assistant and its agents. Supply chain planners can detect critical shortages earlier, assess trade-offs between service levels and inventory investment, and coordinate responses with the Supply Chain Planning Assistant. Maintenance teams can turn asset signals into coordinated maintenance action, helping address problems before they become larger operational disruptions. People retain oversight and control, while assistants and agents help reduce manual effort.

Customers are already putting these capabilities to work. PwC is using 麻豆原创鈥檚 Billing Assistant to help identify potential issues earlier, supporting better client outcomes. Novartis has launched a pilot of the Sourcing Assistant to help sourcing professionals focus on strategy, supplier engagement, and value creation.

鈥淎gents bring consistency and speed to work that previously required a lot of manual effort and coordination,鈥� , head of Procurement at Novartis. He expects improvements of 25% faster cycle times and a 35% uplift in FTE productivity.

As organizations adopt more agents, they need a clear view of their AI landscape. 麻豆原创 AI Agent Hub provides a central inventory of 麻豆原创 and non-麻豆原创 agents, helping teams keep track of and govern their growing agent portfolio. With 麻豆原创 Signavio agent mining and the Process Consulting Agent, we enable customers to identify their biggest opportunities for agentic AI and execute on them right away. This visibility supports a more coordinated approach to managing AI adoption across the business.

With Joule Studio, accessible through Joule Work, customers can create agents tailored to their business and extend 麻豆原创 standard agents with their own instructions. Browser-based tools and pro-code development options support different levels of technical expertise, while testing, versioning, and deployment turn ideas into agents that take action. This lets customers extend 麻豆原创鈥檚 capabilities to meet their business requirements.

Now, let鈥檚 dive into recent innovation.

Please note that this article covers only AI offerings released since July 1, 2026.

Joule

Joule Work

Employees can spend less time navigating applications and more time turning information into outcomes with Joule Work, which is available on desktop, in-app, web, and mobile. Joule Work, the new UI for AI, connects local and cloud environments, bringing conversational AI closer to the files, information, and business tools employees use every day. Employees can work with local files and folders in a secure sandbox environment, access current information through integrated web search, and connect to 麻豆原创 and non-麻豆原创 applications using Model Context Protocol (MCP) tools and Agent-to-Agent (a2a) integrations. Custom and corporate skills help streamline repetitive tasks, while local data and connected tools support faster creation of presentations, summaries, and other assets. And where a skill is not enough, the 麻豆原创 Knowledge Graph kicks in to search the entire space of business objects available to users for deeper transactional and analytical queries. Together, these capabilities reduce manual information analysis and help employees focus on higher-value work.

Dynamic workspaces, which we refer to as spaces, bring together insights, applications, Joule Assistants, and agents to support business workflows. Employees express what they want to accomplish, and Joule Assistants coordinate specialized agents to carry out the work. This effectively initiates the journey into a world where generative UI delivers an ultimate personalized experience to any end user. Joule Studio complements this experience with capabilities to build, deploy, and govern custom agents and workflows.

Early adopter feedback shows how this experience is changing the way employees interact with business information. Reinhausen, a global technology leader in electrical grid technologies, joined the Joule Work desktop early adopter program to support its AI journey. 鈥淲hat once required up to an hour of manual effort across our 麻豆原创 S/4HANA environment is now accessible in seconds through natural language, fundamentally changing how our teams interact with business data,鈥� said Peter Wied, director of Complexity Management at Reinhausen.

Customers are also using custom assistants to bring expertise closer to employees. Warehouse automation company KNAPP used Joule Studio to build an assistant that helps workers identify and resolve problems without waiting for an expert, reducing issue resolution times by about 90% and time spent on documentation and training by about 80%.

Click the button below to load the content from YouTube.

Always allow YouTube

Get started .

The general availability for Joule Work is now underway in a phased approach.

Joule Studio

Business and IT teams can tailor Joule to their organization鈥檚 needs with Joule Studio, combining custom AI agents for complex business processes with reusable skills for everyday tasks. The agent builder enables teams to create agents that plan, reason, and dynamically address business challenges across 麻豆原创 and non-麻豆原创 systems. These agents can coordinate multi-step processes, invoke APIs, work with documents, and collaborate with users or other agents, helping organizations handle ambiguity, exceptions, and workflows that go beyond predefined automation.

The skill builder complements these capabilities with reliable, reusable operations accessed through Joule鈥檚 conversational interface. Teams can create skills to retrieve specific data, execute system transactions, and connect 麻豆原创 and third-party applications using predefined logic. Joule can select and trigger relevant skills based on context, helping employees complete frequent tasks more efficiently.

New intent-based development capabilities draw on business context from 麻豆原创 Signavio, 麻豆原创 Knowledge Graph, and 麻豆原创 Domain Models, helping teams translate business needs into tailored solutions. Pro-code capabilities let developers work in their preferred IDE, Git repository, and AI coding tools.

Together, the two builders help organizations combine flexible, goal-driven agents with predictable, task-specific automation. Grounding agents in business data and processes supports reliable outcomes, while centralized management provides visibility into skills, agent execution, and data privacy enforcement. Joule Studio helps customers build agents faster, improve accuracy while reducing costs, deploy with built-in governance, and ground AI in their business context. Estimated benefits include a 35% reduction in the time to build and deploy custom Joule Agents and a 10% reduction in the time to deploy custom Joule skills, alongside less time spent on frequent business tasks.

The agent builder is available for free until December 2026, after which it becomes a premium AI feature. The skill builder is a base AI feature.

Learn more . Get started and .

Click the button below to load the content from YouTube.

Always allow YouTube

The general availability for Joule Studio is now underway in a phased approach.

麻豆原创 Joule for Consultants, AI-assisted custom knowledge benchmarking
Generally available

麻豆原创 consultants can use custom knowledge grounding in 麻豆原创 Joule for Consultants to receive expert guidance that combines 麻豆原创-curated content with system connectivity for an organization鈥檚 institutional knowledge. Through a grounding service that indexes organizational content with 麻豆原创 AI Core grounding, surfacing relevant information from internal documents into the Joule workflow. This way, responses reflect the firm鈥檚 methodologies, policies, delivery standards, and domain expertise. This reduces time spent searching and switching between tools while supporting growth in knowledge sources over time; it can improve productivity by up to 19%, reduce design iterations and subsequent rework by 50%, increase the share of profit by 1.5% through more optimized 麻豆原创 processes, and accelerate time to realized value by 13.7%.

Customers are already seeing the value of 麻豆原创 Joule for Consultants. reports a 40% reduction in development effort and a 25% decrease in software rework, helping its consultants focus more on innovation and client delivery.  expects to reduce consultant training time by 20 to 30% and save 93 hours each week on information searches, enabling consultants to build expertise faster and spend more time addressing clients鈥� business challenges.

Get started .

This capability is generally available.

Autonomous SCM

Product Design Assistant

• Change Record Management Agent
• Product Data Maintenance Agent
• Product Structure Optimization Agent

Design engineers and product managers can bring products to market faster and avoid costly rework with the Product Design Assistant. It connects data across design, engineering, compliance, and downstream processes, analyzing designs, recipes, and product information to surface insights. It also flags issues early and checks materials and requirements against internal rules and regulations. Three agents released in Q3 strengthen the foundations of product development. Engineers can keep product master data accurate with the Product Data Maintenance Agent, while the Product Structure Optimization Agent consistently optimizes bills of material across product views to reduce costs. When designs need to be changed, the Change Record Management Agent identifies similar change records affecting the same product and proposes a new draft version to initiate the change process. This reduces delays caused by fragmented change data and improves governance and traceability.

The result is faster, more confident design decisions and higher product quality, with estimated benefits including a 19% reduction in product design costs, a 10% increase in prototype success, a five percent reduction in cost of goods sold from design improvements, and a 12% reduction in tooling and material waste costs.

Get started .

The general availability for Product Design Assistant is now underway in a phased approach.

Logistics Assistant

• Batch Optimization Agent
• Warehouse Workload Optimization Agent
• Fixed Bin Maintenance Agent
• Material Reservation Processing Agent

Warehouse and logistics teams can keep operations running smoothly from inbound shipments to outbound deliveries with the Logistics Assistant. It senses disruptions as they happen and coordinates detection, planning, and execution across warehousing and transportation, managing decisions on labor, inventory, dispatch, and freight. Four agents released in Q3 focus on warehouse execution. Supervisors can match staff to demand and spot potential resource shortages early with the Warehouse Workload Optimization Agent. The Fixed Bin Maintenance Agent adjusts bins and replenishment as demand changes. On the inventory side, the Batch Optimization Agent monitors batch expiration and triggers actions to reduce waste. The Material Reservation Processing Agent lets users manage material reservations in natural language, with built-in human review. Together, these capabilities shorten the time from plan to execution, improve resilience to disruption, and lower the cost to serve by reducing expedites and inventory waste.

Get started .

The general availability for Logistics Assistant is now underway in a phased approach.

Manufacturing Assistant

• Production Planning and Operations Agent
• Production Master Data Readiness Agent
• Production Planning Order Progress Agent
• Workplace Safety Agent

Production planners and plant operators can keep manufacturing on track and respond to disruptions sooner with the Manufacturing Assistant. It detects issues in real time and runs corrective workflows for quality, scheduling, and workforce management. It also recommends next-best actions with clear pros and cons, so operators can focus on the exceptions that matter most.

Four agents released in Q3 support production from preparation through execution. The Production Master Data Readiness Agent makes sure materials are fully ready for production without manual setup, and the Production Planning Order Progress Agent identifies coverage issues at every order level. To speed up order-to-delivery, the Production Planning and Operations Agent helps planners release orders in as little as half the time. On the shop floor, the Workplace Safety Agent lets workers report safety concerns by describing what they observe, then assesses risks and suggests actions based on the situation and past data.

By coordinating people, systems, and workflows toward shared operational goals, the assistant helps reduce downtime, waste, and safety response times while supporting compliance through built-in traceability. Estimated benefits include a 14% reduction in production cycle time, a 19% reduction in scrap and defect rates, a six percent reduction in changeover time, a 10% reduction in operating income lost to unplanned downtime, and a 10% reduction in energy costs.

Get started .

The general availability for Manufacturing Assistant is now underway in a phased approach.

Supply Chain Planning Assistant

• Exception Management Agent
• Inventory Investment Allocation Agent
• Supply Chain Planning Orchestration Agent

Supply chain planners can detect issues earlier and respond to change with confidence using the Supply Chain Planning Assistant. It brings AI agents into everyday planning work, including exception management, demand fulfillment, inventory assessment, and capacity analysis, with one-click scenario simulation, root-cause analysis, and actionable recommendations. Three agents released in Q3 help planners turn analysis into action. The Exception Management Agent detects and resolves critical supply planning issues, giving planners the insights they need to protect service levels and avoid costly expedites. The Inventory Investment Allocation Agent weighs service levels against working capital to recommend optimal stock targets. The Supply Chain Planning Orchestration Agent coordinates these and other specialized agents across planning workflows. By speeding up decisions and surfacing capacity issues and persistent shortages in advance, the assistant helps planners keep schedules and inventory targets on track, with estimated benefits including a 20% reduction in planning coordination overhead and a 10% reduction in planning cycle time.

Get started .

The general availability for Supply Chain Planning Assistant is now underway in a phased approach.

Asset Operations Assistant

• Operational Maintenance Planning Agent
• Maintenance Event Planning Agent
• Maintenance Request Initiation Agent
• Maintenance Job Debrief Agent
• Equipment Insight Agent
• Task List Management Agent

Maintenance teams can identify critical asset conditions earlier and resolve them before they turn into larger operational disruptions with the Asset Operations Assistant. It turns asset signals into coordinated maintenance action and automates prioritization, planning, and scheduling, leaving teams more time for high-value work and exceptions.

Six agents released in Q3 cover the maintenance cycle from first request to final debrief. Technicians can create and route maintenance requests from natural-language input with the Maintenance Request Initiation Agent, while the Equipment Insights Agent provides a complete view of equipment to support better decision-making. The Operational Maintenance Planning Agent combines preventive, predictive, and corrective tasks into executable weekly and biweekly plans. When conditions change, the Maintenance Event Planning Agent analyzes real-time data to reprioritize tasks and adjust schedules. The Maintenance Task List Management Agent automates task list creation for greater consistency, and the Maintenance Job Debrief Agent streamlines job debriefs with AI-driven recommendations. By connecting asset health, risk, work outcomes, and financial impact, the assistant helps organizations increase planned work, reduce unplanned downtime, and improve uptime.

Get started .

The general availability for Asset Operations Assistant is now underway in a phased approach.

麻豆原创 Integration Business Planning, AI-assisted scenario planning

Supply chain planners can respond to disruptions with confidence using scenario planning in 麻豆原创 Integrated Business Planning. Within one workspace, they can assess impacts on demand and sales orders, identify alternative supply sources, and simulate mitigation options against KPIs such as service level and utilization before adopting the best-performing scenario. This streamlined approach helps planners make faster, data-driven decisions, build trust in their plans, and strengthen supply chain resilience.

Get started .

This capability is generally available.

Autonomous HCM

HR Service Assistant

• HR Knowledge Agent
• HR Workflow Accelerator Agent
• Payroll Explanation
• Time Off Service Agent
• Time Sheet Service Agent
• HR Service Orchestration Agent

HR service teams can resolve routine employee requests conversationally, without creating a case each time, using the HR Service Assistant. The assistant provides always-on support and draws on six agents released in Q3. Employees get fast, cited, policy-grounded answers from the HR Knowledge Agent, while the HR Service Orchestration Agent resolves requests through self-services or routes them to the right specialist agent. Common everyday questions are handled directly in the conversation: the Payroll Explanation Agent clarifies pay statements, and the Time Sheet Service Agent and Time Off Service Agent guide employees through submitting timesheets and creating compliant leave requests. When processes stall, the HR Workflow Accelerator Agent identifies delays and resolves them, allowing HR teams to reserve expert attention for complex cases. Estimated benefits include a 24% increase in case deflection to self-service, a 26% reduction in time to resolution, and a 40% reduction in queries that need Tier 2 or higher intervention.

Get started .

The general availability for HR Service Assistant is now underway in a phased approach.

HR Operations Assistant

• Employee Data Integration Agent
• Position Optimization Agent
• Job Change Request Agent
• Compensation Guidance Agent
• Job Architecture Maintenance Agent
• Skills Governance Agent

HR teams and managers can simplify core HR administration while keeping employee, job, and organizational data consistent and compliant with the HR Operations Assistant. Six agents released in Q3 help connect these activities: managers can find, edit, and create positions with the Position Optimization Agent and translate their intent into job changes with the Job Change Request Agent, while the Compensation Guidance Agent recommends policy-aligned salary increases based on performance, compensation, and skills data. To maintain the underlying data, the Employee Data Integration Agent resolves data inconsistencies, while the Job Architecture Maintenance Agent and Skills Governance Agent help keep role鈥搒kill mappings current and the skills ecosystem clean and AI-ready. Working alongside the assistant鈥檚 other specialized agents, they reduce administrative effort and support more reliable HR processes, with estimated benefits including a 39% reduction in data errors, a 20% reduction in HR transactional work, and a 25% reduction in manager time on core HR workflows.

Get started .

The general availability for HR Operations Assistant is now underway in a phased approach.

Performance and Goals Assistant

• Calibration Equity Agent
• Goal Creation Agent
• Goal Progress Agent

Managers and HR teams can align employee goals with business strategy and bring greater consistency to performance evaluations using the Performance and Goals Assistant. Three agents released in Q3 contribute to its broader capabilities: the Goal Creation Agent generates SMART performance goals grounded in strategy and role context; the Goal Progress Agent tracks completion in real time and flags risks before deadlines are missed; and the Calibration Equity Agent identifies potential inconsistencies in employees’ performance ratings before or during calibration. By combining clearer goals, proactive progress monitoring, and insights into rating inconsistencies, the assistant helps managers conduct more efficient reviews and make better-informed calibration decisions, with estimated benefits of a 21.4% reduction in review completion time and a 30% reduction in manual decision-making effort for managers.

Get started .

The general availability for Performance and Goals Assistant is now underway in a phased approach.

HR System Assistant

• Configuration Transport Agent
• HCM Audit Agent
• Role-based Permissions Agent

HR administrators can resolve access issues, manage configuration changes, and keep systems audit-ready with the HR System Assistant. It automates low-risk tasks and guides higher-risk changes, helping reduce errors and accelerate go-lives. Its Q3 releases address three key administrative needs: the Configuration Transport Agent discovers, bundles, and securely migrates configuration changes across tenants; the HCM Audit Agent enables natural language queries of 麻豆原创 SuccessFactors audit logs; and the Role-Based Permissions Agent queries user access, helps fix permission issues, and automates secure access resolution. As part of the assistant鈥檚 broader capabilities, these agents support faster troubleshooting, fewer configuration defects, and stronger traceability, with estimated benefits of a 70% reduction in configuration transport effort, a 90% reduction in time spent generating audit reports, and a 90% reduction in permission incident resolution costs.

Get started .

The general availability for HR System Assistant is now underway in a phased approach.

Autonomous Finance

Billing Assistant

• Billing Posting Agent
• Billing Creation Agent
• Billing Anomaly Agent
• Billing Adjustment Agent
• Error Explanation and Resolution Agent
• Billing Orchestration Agent

Billing teams can improve invoice accuracy and resolve issues faster with the Billing Assistant, which coordinates activities from document creation through adjustments and posting support. There are six agents being released in Q3: teams can prioritize due lists and create policy-aligned billing documents with the Billing Creation Agent, while the Billing Anomaly Agent flags unusual taxes and charges for review. When errors arise, the Billing Posting Agent and the Error Explanation and Resolution Agent help teams understand the issues and identify corrective steps, while the Billing Adjustment Agent cancels and reissues invoices to apply adjustments. The Billing Orchestration Agent coordinates these activities to keep billing processes moving. Together, these capabilities reduce manual effort and support faster invoice correction and dispute resolution, with estimated benefits including a 90% reduction in time spent analyzing and resolving posting issues, a 70% reduction in billing document creation effort, a 70% reduction in anomaly detection effort, and a 54% reduction in invoice reprocessing effort.

Get started .

The general availability for Billing Assistant is now underway in a phased approach.

Financial Closing Assistant

• Journal Entry Agent
• Accounting Accruals Agent
• Receivables and Payables Clearing Agent
• Analytical Business Insights Agent
• Asset Accounting Anomaly Detection Agent
• Financial Consistency Analysis Agent
• Financial Closing Orchestration Agent

Finance and accounting teams can accelerate period-end execution with the Financial Closing Assistant while controlling the extent to which agents participate in journal postings, clearing, and analysis. Seven agents released in Q3 support connected closing activities: teams can streamline audit-ready journal processing and accruals management with the Journal Entry Agent and Accounting Accruals Agent, and identify clearing opportunities through AI-based matching and aging analysis with the Receivables and Payables Clearing Agent. The Asset Accounting Anomaly Detection Agent and Financial Consistency Analysis Agent help improve accuracy by preventing invalid asset postings and resolving data errors, while the Analytical Business Insights Agent turns financial KPI analysis into executive summaries. Coordinating these workflows, the Financial Closing Orchestration Agent helps keep activities moving across teams and agents. This approach supports a faster, more reliable close, with an estimated 35% increase in productivity for staff performing reconciliations and adjustments.

Get started .

The general availability for Financial Closing Assistant is now underway in a phased approach.

Cash and Treasury Assistant

• Cash Positioning Agent
• Bank Relationship Agent
• Cash and Treasury Orchestration Agent

Treasury teams can manage liquidity more confidently and lower financing and banking costs with the Cash and Treasury Assistant. It monitors internal funding positions and needs, proposes cash transfers between bank accounts, and identifies ways to streamline bank wallet share and fees. Three agents released in Q3 support this work. The Cash Positioning Agent optimizes cash and performs cash-positioning tasks, such as checking balances, forecasting cash flows, and transferring funds. The Bank Relationship Agent gives treasurers a comprehensive view of the enterprise鈥檚 banking relationships, and the Cash and Treasury Orchestration Agent coordinates these activities with the assistant’s other specialized agents. Better interest yields and lower financing costs can free up funds for growth initiatives. Estimated benefits include a 50% increase in cash management and treasury staff productivity and a 10% reduction in bank commissions and fees. Productivity is also estimated to rise by 30% in the following areas: liquidity management and cash forecasting, FX risk and hedging, bank relationship management, and treasury reporting and compliance.

Get started .

The general availability for Cash and Treasury Assistant is now underway in a phased approach.

Financial Consolidation Assistant

• Financial Consolidation Data Submission Agent
• Financial Consolidation Orchestration Agent

Consolidation teams and local accountants can complete the financial close faster and with less manual effort using the Financial Consolidation Assistant. The assistant supports work across data preparation and consolidation. It guides users through issue resolution, simplifies master data maintenance, and speeds up simulations of mergers, FX changes, and other business scenarios. Two agents released in Q3 make the close cycle smoother. Local accountants can automate data submissions and resolve errors before data reaches group consolidation using the Financial Consolidation Data Submission Agent. The Financial Consolidation Orchestration Agent coordinates its agents. Teams spend less time collecting and correcting data and more time analyzing results, with an estimated 25% increase in productivity for staff performing reconciliations and adjustments.

Get started .

The general availability for Financial Consolidation Assistant is now underway in a phased approach.

Sales Operations Assistant

• Billing Block Resolution Agent
• Credit Block Resolution Agent
• Delivery Issue Resolution Agent
• Supply Issue Resolution Agent

Sales teams can keep orders moving and address fulfillment obstacles directly in their workflow with the Sales Operations Assistant. It automates sales order creation from unstructured data and supports order updates, shortening processing cycles and reducing errors. Four agents released in Q3 target common sources of delay: teams can address billing and credit blocks with the Billing Block Resolution Agent and Credit Block Resolution Agent, tackle delivery issues with the Delivery Issue Resolution Agent, and identify, analyze, and receive recommended solutions for supply problems with the Supply Issue Resolution Agent. By combining faster issue resolution with accurate, up-to-date sales data, the assistant helps improve customer satisfaction and support informed pricing decisions, with estimated benefits including a 15% reduction in revenue lost to fulfillment issues, a 10% reduction in financial losses from stockouts, and a 50% reduction in time spent resolving billing blocks and credit issues.

Get started .

The general availability for Sales Operations Assistant is now underway in a phased approach.

Recurring Receivables Assistant

• Collection Insights Agent
• Convergent Invoicing Execution Agent
• Subscription Lifecycle Agent

Finance teams can accelerate collections and manage high-volume recurring receivables more efficiently with the Recurring Receivables Assistant. Supporting recurring billing and subscription-based business models, it brings customer account context, risk insights, and recommended next steps into order-to-cash activities. Three agents released in Q3 help teams act on these insights: collectors get collection support from the Collection Insights Agent, while the Convergent Invoicing Execution Agent automates invoice corrections through geography-aware, regulation-compliant rebilling. The Subscription Lifecycle Agent complements these activities by automating subscription contract management from search through execution. Together, these capabilities help protect revenue, reduce downstream corrections, and free blocked cash, with estimated benefits including a 20% reduction in controllable days sales outstanding, a 20% increase in accounts receivable staff productivity, and a 10% reduction in controllable write-offs.

Get started .

The Recurring Receivables Assistant is available in the 麻豆原创 Early Adopter Care program.

Accounts Receivable Assistant

• Collection Account Preparation Agent
• Dispute Resolution Agent
• Dunning Insights Agent
• Collections Email Outreach Agent
• Dispute Creation Agent
• Receivable Account Analysis Agent
• Accounts Receivable Orchestration Agent

Accounts receivable teams can prepare more effective collection calls and release disputed cash sooner with the Accounts Receivable Assistant. Seven agents released in Q3 connect account analysis, customer outreach, and dispute handling: collectors can build a complete customer account picture and prioritize their next steps with the Receivable Account Analysis Agent, Collection Account Preparation Agent, and Dunning Insights Agent, while the Collections Email Outreach Agent automates correspondence for worklist items that do not require a call. The Dispute Creation Agent manages dispute cases using natural language processing and provides insights, while the Dispute Resolution Agent validates cases and suggests actionable solutions. The Accounts Receivable Orchestration Agent coordinates these activities to reduce manual effort and collection delays. Estimated benefits include a 35% increase in accounts receivable staff productivity, a 25% reduction in controllable days sales outstanding, a 15% reduction in uncollectable write-offs, and a five percent reduction in customer churn from disputes.

Get started .

The general availability for Accounts Receivable Assistant is now underway in a phased approach.

Tax Compliance Assistant

• Legal Change Agent
• Regulatory Document Mapping Explanation Agent
• Statutory Report Analysis Agent
• Statutory Report Extension Update Agent
• Tax and Compliance Orchestration Agent

Finance and IT teams can keep pace with regulatory changes and reduce manual compliance work with the Tax and Compliance Assistant. It supports continuous monitoring and automation across tax calculations, e-invoicing, statutory reporting, and payments, helping teams identify issues before they become costly disruptions. Five agents released in Q3 connect regulatory discovery with reporting maintenance: the Legal Change Agent helps teams discover relevant regulatory changes, while the Regulatory Document Mapping Explanation Agent clarifies regulated e-invoice field mappings and compliance rules through Joule. Teams can review statutory reports for anomalies and recommended fixes with the Statutory Report Analysis Agent, and merge report extensions when 麻豆原创 delivers new versions using the Statutory Report Extension Update Agent. The Tax and Compliance Orchestration Agent coordinates these activities, supporting traceable processes and faster error correction. Estimated benefits include a 75% reduction in compliance rework costs, a 30% reduction in tax compliance process costs, a 40% reduction in regulatory penalties and fines, and a 50% reduction in compliance monitoring effort.

Get started .

The general availability for Tax and Compliance Assistant is available in the 麻豆原创 Early Adopter Care program.

International Trade Assistant

• International Trade Product Profile Agent
• International Trade Classification Agent

International trade teams can streamline goods classification and manage changing trade requirements with the International Trade Assistant, bringing AI-powered support into enterprise import, export, compliance, and origin management processes. Two agents released in Q3 connect product understanding with classification: the International Trade Product Profile Agent collects and unifies product data to establish its semantic meaning, while the International Trade Classification Agent automatically classifies goods for shipping, helping teams save time and support compliance. Alongside capabilities such as sanction screening and EU Intrastat reporting, these agents help replace disconnected, reactive processes with a more governed and scalable approach to international trade.

Get started .

The general availability for International Trade Assistant is available in the 麻豆原创 Early Adopter Care program.

Accounts Payable Assistant

• Accounts Payable Orchestration Agent
• Payment Inquiry Handling Agent
• Receivables and Payables Clearing Agent

Accounts payable teams can reduce manual payment handling and reconcile vendor accounts more efficiently with the Accounts Payable Assistant. It combines payment automation, proactive validation, and guidance on exceptions with insights into cash flow and discount opportunities. Three agents released in Q3 support these workflows: teams can manage routine invoice-specific payment inquiries with the Payment Inquiry Handling Agent and generate balanced clearing proposals for open items in accounts payable and receivable with the Receivables and Payables Clearing Agent. The Accounts Payable Orchestration Agent coordinates the agents. By streamlining payment-related tasks and helping teams address discrepancies, the assistant offers estimated benefits of a 35% increase in accounts payable staff productivity and a 20% reduction in duplicate payments and exceptions.

Get started .

The general availability for Accounts Payable Assistant is now underway in a phased approach.

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted KPI and report summary

Managers and executives can get a quicker view of business performance with KPI and report summaries in 麻豆原创 S/4HANA Cloud Public Edition. The feature turns Generic Drilldown reports into concise natural-language summaries that highlight key metrics, trends, anomalies, and threshold breaches directly within 麻豆原创 Fiori apps. This makes complex analytics easier to interpret and share, helping users make more informed decisions without manual report analysis.

Get started .

This capability is generally available.

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

EHS compliance managers can set up regulatory obligations and permits more efficiently with environment management and compliance management in 麻豆原创 S/4HANA Cloud Public Edition. The feature scans PDF documents to capture header data, identify relevant requirements, and propose related tasks such as maintenance notifications or reporting activities, while keeping the source document and proposed actions visible side by side. This reduces data entry errors and setup time, strengthens auditability by linking requirements to their source, and can reduce compliance obligation management costs by up to 65% while lowering the risk of penalties and fines.

Get started .

This capability is generally available.

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted aging work in progress analytics and management

Project financial controllers can track and manage aging work in process more effectively with Joule in 麻豆原创 S/4HANA Cloud Public Edition. The feature analyzes WIP for time-and-expense projects, identifies delayed billing, summarizes relevant insights in dynamic charts, and supports actions to help prevent revenue loss. This shortens the time needed to review WIP amounts, speeds billing decisions, and helps reduce potential cash flow risk.

Get started .

This capability is generally available.

麻豆原创 Cloud Identity Access Governance, AI-assisted access review

Access reviewers can make faster, more informed certification decisions with AI-assisted access review in 麻豆原创 Cloud Identity Access Governance. The feature provides context-aware recommendations based on historical review outcomes, peer-group analysis, and organizational access patterns, along with business-friendly explanations to help reviewers assess whether a user鈥檚 access remains appropriate. This reduces review effort and operational overhead while improving decision quality, strengthening access governance, and supporting compliance.

Get started .

This capability is generally available.

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted document extraction for simplified business partner master data maintenance

Sales managers, purchasing managers, and business partner master data specialists can accelerate business partner onboarding with document extraction in 麻豆原创 S/4HANA Cloud Public Edition. Integrated into the Manage Business Partner app, 麻豆原创 Document AI extracts names, addresses, bank account details, and tax numbers from uploaded purchase orders, quotations, and invoices, and automatically populates the relevant fields. This reduces manual transcription and switching between files and screens, helping improve data accuracy, consistency, and operational efficiency.

Get started .

This capability is generally available.

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted incoming bill of exchange posting

Finance teams can streamline incoming bill of exchange processing in 麻豆原创 S/4HANA Cloud Public Edition with automated data extraction and posting proposals. By uploading PDF or image files, they can capture bill details, identify missing or inconsistent data, and match open customer items to support posting and reconciliation. This reduces manual entry and errors, improves processing efficiency, and helps teams handle higher volumes across supported countries.

Get started .

This capability is generally available.

Autonomous Spend Management

Purchasing Assistant

• Purchase Order Lifecycle Management Agent

Purchasing teams can make faster, more consistent buying decisions and protect margins with the Purchasing Assistant. It identifies spend leakage, recommends the best-fit suppliers with clear, explainable reasoning, and automatically enriches and validates catalog data at upload. It also monitors frequently purchased materials for potential supply gaps and assigns new sources of supply. The Purchase Order Lifecycle Management Agent, released in Q3, extends this support beyond the point of purchase. It flags delivery risks for open orders and guides purchasers on the next steps. By automating analysis and reducing manual follow-up, the assistant improves catalog quality and keeps critical materials in stock, with estimated benefits including a one percent decrease in buying spend and a 30% increase in buying staff productivity.

Get started .

The general availability for Purchasing Assistant is now underway in a phased approach.

Supplier Management Assistant

• Supplier Management Identification and Optimization Agent

Supplier managers and procurement teams can build a more resilient supplier base and make better informed decisions with the Supplier Management Assistant. It supports the full supplier life cycle: it unifies supplier data across systems into a single, consistent view, assesses supplier performance to recommend targeted development plans, and continuously monitors financial, compliance, and ESG risk using real-time external data. The Supplier Management Identification and Optimization Agent, released in Q3, adds AI-powered supplier identification and optimization, helping teams find suitable suppliers and make sourcing decisions faster. With less manual effort spent gathering supplier information and assessing risk, organizations can respond to changes in their supply base sooner, with an estimated 20% increase in supplier management staff productivity.

Get started .

The general availability for Supplier Management Assistant is now underway in a phased approach.

Procurement Contract Assistant

• Procurement Contract Compliance Monitoring Agent
• Procurement Contract Analysis Agent
• Procurement Contract Renewal Optimization Agent

Procurement and contract management teams can protect contract value and reduce risk across the contract life cycle with the Procurement Contract Assistant. It produces legally compliant first drafts, continuously monitors terms, and supports decisions on renewal, renegotiation, and new sourcing. Three agents released in Q3 help bring existing and active agreements under control. Teams can speed up the ingestion of legacy contracts with the Procurement Contract Analysis Agent, which extracts metadata and obligations, while the Procurement Contract Compliance Monitoring Agent monitors those obligations and detects deviations in real time. As agreements near expiration, the Procurement Contract Renewal Optimization Agent evaluates them and recommends the next action. By surfacing risks to pricing, usage, SLAs, and obligations earlier, the assistant improves compliance and renewal outcomes, with estimated benefits including a 45% increase in contract management staff productivity and a 50% reduction in gaps in terms-and-conditions monitoring.

Get started .

The general availability for Procurement Contract Assistant is now underway in a phased approach.

Category Management Assistant

• Category Strategy Development Agent
• Market Insights Agent

Category managers can build, refine, and continuously optimize category strategies with the Category Management Assistant, providing procurement teams with a basis for more proactive decision-making. The assistant combines spend data, supplier context, and external market intelligence into a single view of each category, surfacing risks and opportunities such as market shifts, compliance gaps, and value leakage early. Two agents released in Q3 connect market research directly to strategy. The Market Insights Agent automates category research and delivers verified procurement intelligence, and the Category Strategy Development Agent turns market intelligence into data-driven strategy recommendations. Category managers spend less time gathering information and can adapt their strategies as conditions change, with estimated benefits including a 35% increase in category management staff productivity and a one percent reduction in maverick spend.

Get started .

The general availability for Category Management Assistant is now underway in a phased approach.

Invoicing Assistant

• Invoicing Orchestration Agent

Accounts payable teams can move toward touchless invoice processing with the Invoicing Assistant, which automates AP from invoice receipt to payment scheduling with minimal human input. It extracts invoice data, accelerates posting, and draws on integrated procurement and finance data to reduce errors, provide real-time insights, and detect potential fraud. The Invoicing Orchestration Agent, released in Q3, fully automates AP by extracting invoice data and orchestrating end-to-end processing with minimal human input. Less time spent on manual data entry and exception handling results in a more secure, compliant, and efficient process, and more room for higher-value work.

Get started .

The general availability for Invoicing Assistant is now underway in a phased approach.

Receiving Assistant

• Return Goods to Supplier Agent

Procurement and receiving teams can streamline goods receipts, service entry sheets, returns, and quality tracking with the Receiving Assistant, reducing manual steps while reinforcing purchase order and contract compliance. For supplier returns, the Return Goods to Supplier Agent helps identify slow-moving or obsolete stock and uses material details and return quantities to trace the original supplier and purchase order. It then prepares a draft return purchase order and notifies the responsible purchaser, who reviews the proposal and agrees on the return terms with the supplier. This combines automated preparation with human oversight to reduce administrative effort, help release working capital tied up in excess inventory, and lower the financial risk of unresolved dead stock.

Get started .

The general availability for Receiving Assistant is now underway in a phased approach.

Requisition Assistant

• Purchase Requisition Creation Agent
• Purchase Requisition Optimization Agent

Employees can find the items and services they need and prepare policy-compliant purchase requests with the Requisition Assistant. The Purchase Requisition Optimization Agent searches and compares options across multiple catalogs in real time, ranking alternatives against priorities such as price, quality, supplier preference, and delivery time. To simplify request preparation, the Purchase Requisition Creation Agent turns free-text requests or documents into ready-to-submit purchase carts, guides users to the appropriate buying channels, and autofills forms while checking policies and validating key details. These capabilities help employees balance purchasing needs with company preferences, reduce errors before submission, and shorten requisition-to-order cycles, with an estimated 15% increase in requisition staff productivity.

Get started .

The general availability for Requisition Assistant is now underway in a phased approach.

Operational Procurement Assistant

• Invoice Reminder Agent
• Material Spend Advisory Agent

Procurement teams can reduce manual follow-up and strengthen contract compliance across the procure-to-pay cycle with the Operational Procurement Assistant. It monitors and drives the processing of purchase requisitions, purchase orders, supplier contracts, scheduling agreements, service entry sheets, and supplier invoices. Teams can identify off-contract spending, quantify potential savings, and spot quick wins with the Material Spend Advisory Agent, while accountants receive invoice insights through the Invoice Reminder Agent. By reducing manual steps, keeping contracts and sourcing data up to date, and simplifying supplier quote management, the assistant helps accelerate procurement execution, reduce errors and delays, and improve contract utilization.

Get started .

The general availability for Operational Procurement Assistant is now underway in a phased approach.

麻豆原创 Ariba Contracts, AI-assisted contract creation from documents

Suppliers can create contracts in 麻豆原创 Ariba Contracts from existing contract PDFs. The feature extracts relevant contract details, recommends required fields, and provides a preview where users can review, edit, or override values before creating the contract. This reduces repetitive data entry, supports more consistent contract data, and helps accelerate contract onboarding and digitization.

Get started .

This capability is generally available.

麻豆原创 Ariba Contracts, AI-assisted contract creation from prompts

Contract managers can start new contracts in 麻豆原创 Ariba Contracts using natural-language prompts directly within the contract creation experience. The feature translates a small number of inputs into contract header fields in seconds, helping users focus on their intent rather than navigating through separate steps. Users review and confirm the proposed details before creating the contract, reducing effort while maintaining human control as contract volumes grow.

Get started .

This capability is generally available.

麻豆原创 Ariba Contracts, AI-assisted contract field recommendations

Contract managers can complete contracts faster in 麻豆原创 Ariba Contracts with context-aware field recommendations. The feature suggests relevant values from reliable data sources for fields such as supplier, company code, and payment terms, helping users navigate organizational rules and dependencies with less manual effort. Explainable recommendations support accuracy and compliance while allowing contract managers to retain control and flexibility over final values.

Get started .

This capability is generally available.

Concur Travel, AI-assisted trip changes

Business travelers and travel coordinators can manage itinerary changes through a natural-language conversation with Joule in Concur Travel. They can find a trip by describing it, review the estimated cost of a modification before confirming it, and update flights, hotels, or rental cars without switching to separate booking tools. This provides real-time support that reduces manual work and helps users make travel changes faster.

Get started .

This capability is generally available.

Concur Expense, AI-assisted approval manager

Approval managers can use AI-powered insights in Concur Expense to focus their review on the transactions that require attention. The feature identifies unusual patterns, inconsistencies, and missing context, while routine, lower-risk expenses recede from view to reduce review noise. Explainable AI reasoning clarifies why an item was flagged, and direct access to receipts, expense history, and supporting details helps managers quickly validate decisions. Integrated into existing approval workflows, the feature helps speed up reviews, improve consistency, and maintain accountability without requiring approvers to be expense-policy experts.

Get started .

This capability is available in 麻豆原创 Early Adopter Care.

Concur Expense, AI-assisted corporate card management

Card administrators and business travelers can simplify virtual card management with AI-driven automation in Concur Expense. Administrators can translate policies written in natural language into spending limits, merchant category controls, and approval workflows, while travelers can request cards and funds conversationally through familiar messaging channels. This reduces administrative effort, accelerates access to funds, and supports compliance through upfront spending guardrails. The feature is currently available only to eligible customers enrolled in the corresponding 麻豆原创 Early Adopter Care program.

Get started .

This capability is available in 麻豆原创 Early Adopter Care.

Concur Travel, AI-assisted travel filters

Business travelers can find suitable flights faster with AI-assisted travel filters in Concur Travel. By describing preferences such as a preferred airline or departure time window in plain language, they can narrow search results without scanning numerous options or adjusting filters individually. This helps travelers identify relevant itineraries more efficiently, simplify decision-making, and book with greater confidence.

Get started .

This capability is generally available.

Concur Travel, AI-assisted travel search

Corporate travelers can find relevant rail stations more easily with AI-assisted travel search in Concur Travel, even when they do not know the exact station name or local spelling. They can search in supported languages using station names, cities, countries, or points of interest, with support for typos, omitted accents, and different word orders. This helps travelers identify suitable stations with less effort and plan rail journeys with greater confidence.

Get started .

This capability is generally available.

Autonomous CX

Case Management Assistant

• Case Action Recommendation Agent
• Case Preparation Agent
• Case Processing Agent
• Case Management Orchestration Agent

Service representatives can move from case intake to resolution with clearer context and guided actions using the Case Management Assistant. Four agents released in Q3 support this journey: the Case Preparation Agent analyzes incoming requests and extracts key customer context, giving representatives an informed starting point, while the Case Action Recommendation Agent recommends next best actions and helps prioritize tasks based on the live case. The Case Processing Agent assists with processing steps across relevant scenarios and domains, while the Case Management Orchestration Agent coordinates the specialized agents throughout the workflow. By reducing back-and-forth and supporting case summaries and customer communications, the assistant helps teams deliver more efficient, consistent service, with estimated benefits including a 35% reduction in diagnosis effort, a 50% reduction in misrouting, and a 20% reduction in resolution time.

Get started .

The general availability for Case Management Assistant is now underway in a phased approach.

Deal Qualification Assistant

• Lead Conversion Agent
• Lead Enrichment Agent
• Lead Qualification Agent
• Lead Routing Agent
• Deal Qualification Orchestration Agent

Sales teams can prioritize promising prospects and accelerate opportunity creation with the Deal Qualification Assistant. It deduplicates lead data, assesses fit and intent, and automates routing and engagement. Four agents released in Q3 connect these activities: the Lead Enrichment Agent enhances incoming lead records with relevant external data, ensuring sales teams have the context needed to engage effectively, while the Lead Qualification Agent categorizes prospects as qualified, nurtured, or disqualified based on ideal customer criteria. After an account executive confirms qualification, the Lead Conversion Agent creates the required account, contact, and opportunity records, preserving lead details and engagement history. The Deal Qualification Orchestration Agent coordinates the specialized agents across the process. This reduces research and data entry while improving pipeline quality, with estimated benefits including a 35% reduction in manual deal-qualification effort and a 10% increase in the lead-to-meeting ratio.

Get started .

The general availability for Deal Qualification Assistant is now underway in a phased approach.

麻豆原创 Enterprise Service Management, AI-assisted document extraction

Service and support staff can extract relevant information from image and PDF attachments in 麻豆原创 Enterprise Service Management. The feature converts unstructured document content into structured data鈥攕uch as invoice or contract-account details鈥攁nd supports retrieval of related entities from 麻豆原创 back-end systems, including 麻豆原创 S/4HANA Cloud. This accelerates document handling, improves data accuracy, and connects incoming documents more smoothly to existing workflows and business processes.

Get started .

This capability is generally available.

麻豆原创 Omnichannel Promotion Pricing, AI-assisted promotional text translation

Promotion planners can use 麻豆原创 Omnichannel Promotion Pricing to translate promotional text into more than 150 languages. AI-powered translation reduces the manual work required to maintain multilingual content and helps keep messaging consistent across global promotion campaigns.

Get started .

This capability is generally available.

麻豆原创 Engagement Cloud, AI-assisted content composer

Marketers can accelerate campaign creation with the AI-powered content composer in 麻豆原创 Engagement Cloud, generating personalized copy and brand-consistent images directly within the campaign editor. Drawing on product catalog data, audience attributes, and reference campaigns, they can create headlines, body copy, calls to action, and hero images while retaining control to preview, edit, or regenerate each element. This integrated workflow helps teams launch campaigns faster, scale personalization, and reduce tool switching.

Get started .

This capability is generally available.

麻豆原创 Business AI Platform

Mistral on 麻豆原创 Business AI Platform

Organizations can use Mistral’s enterprise AI platform, including Mistral Vibe Work and AI Studio, hosted on 麻豆原创 Business AI Platform, to enhance productivity. Employees can interact with multilingual large language models to chat, think, search, write, upload files, and receive answers to questions, helping them automate meaningful daily work from a single environment. The offering also provides a no-code environment for teams to design, customize, deploy, and operate AI agents and workflows end-to-end. Mistral models are deployed locally on 麻豆原创 Cloud Infrastructure to support data processing within a trusted region, helping organizations address regulatory requirements, regional compliance mandates, and geopolitical considerations. A fully sovereign version on 麻豆原创 Sovereign Cloud, supporting legal, operational, technical, and data sovereignty, is planned for early 2027.

Get started .

This capability is generally available.

麻豆原创 Analytics Cloud, AI-assisted prompt insights

Story designers can embed large language model prompts as widgets in 麻豆原创 Analytics Cloud stories, enabling story consumers to generate AI responses directly within their analytics experience. The feature can provide structured analysis of tables or answer broader business questions, helping users create data-driven narratives and decision support without moving internal data to external AI tools. This reduces manual analysis effort and can cut the time required to analyze 麻豆原创 Analytics Cloud data by 60%.

Get started .

This capability is generally available.

麻豆原创 Analytics Cloud, AI-assisted story code generation

Business analysts can build customized dashboards more efficiently with AI-assisted story code generation in 麻豆原创 Analytics Cloud. The feature automatically generates JavaScript and explains its functionality and coding choices, helping analysts understand, modify, and extend scripts to create low-code analytics applications. This reduces manual coding effort, supports faster delivery of analytics solutions, and gives analysts greater flexibility to tailor dashboards to business needs.

Get started .

This capability is generally available.

麻豆原创 Datasphere, AI-assisted SQL generation

Data modelers can create and refine SQL views more efficiently with AI-assisted SQL generation in 麻豆原创 Datasphere. Using natural language prompts in the SQL View Builder, they can generate SQL code for new or existing views. This helps reduce manual coding effort and increase modeling productivity.

Get started .

This capability is generally available

Generative AI hub enhancements

麻豆原创-RPT-1.6
麻豆原创-RPT-1.6, now available on generative AI hub, is our latest model in the 麻豆原创-RPT family. It delivers the strongest gains in prediction quality to date, particularly for high-cardinality classification, and is validated across 197 real-world enterprise tasks.

• Explainability: Available in all 麻豆原创-RPT-1.6 variants, this includes column-level feature importances and the ability to surface specific historical rows most influential to each prediction, giving business users and decision-makers a clearer basis for trusting and acting on AI-driven outputs.
• Deep Context Mode: Only available in 麻豆原创-RPT-1.6-large, this allows the model to draw on significantly larger reference datasets to improve prediction quality. It is intended for use cases with large historical data, such as invoice records spanning multiple fiscal years or product catalogs in the tens of thousands. This mode trades higher latency and cost for higher accuracy, and can be enabled via a single parameter in the prediction configuration.

Tabular Orchestration
Tabular Orchestration, now available on generative AI hub, is a new managed workflow for 麻豆原创-RPT models. It handles context management and data access, thereby removing the need to build and maintain custom data pipelines. Teams register their data source and scenario configuration once at design time. Every inference is a single API call, with the workflow automatically handling data ingestion and context selection before routing the prediction request to the specified 麻豆原创-RPT model. This setup is designed to easily carry forward as the workflow expands to support additional tabular foundation models beyond 麻豆原创-RPT in future releases.

Prior Labs’ TabPFN-3.5-Plus
Business analysts and AI teams can turn structured business data into actionable predictions faster with TabPFN-3.5 Plus, now available in 麻豆原创 AI Core. Developed by Prior Labs, an 麻豆原创 company, the tabular foundation model helps organizations predict outcomes such as payment delays, supplier risks, customer churn, and upsell opportunities鈥攚ithout task-specific model training or tuning. Unlike large language models, which excel at language and knowledge tasks, TabPFN-3.5 Plus is purpose-built for the rows and columns that underpin critical business decisions.

The model works with data as it exists in business systems, handling missing values, mixed data types, and inconsistent fields without preprocessing. Through in-context learning, it uses labeled examples to make predictions from raw tabular data, including columns containing thousands of distinct values, such as product codes or customer identifiers. This reduces the manual preparation and trial-and-error configuration associated with traditional machine learning, helping teams move from business data to predictions in minutes.

For customers, this means a faster path to predictive insights with less model-development effort. Finance teams can anticipate payment delays, procurement teams can assess supplier risks, and customer-facing teams can identify churn risks and upsell opportunities. By making prediction more accessible, TabPFN-3.5 Plus helps organizations use their structured data to inform decisions and act earlier on emerging risks and opportunities.

Learn more here and . .

Enterprise Architecture Assistant

• Enterprise Architecture Management Agent

Enterprise architects can find answers and maintain more complete, up-to-date architecture inventories without leaving 麻豆原创 LeanIX using the Enterprise Architecture Assistant. Released in Q3, its Enterprise Architecture Management Agent enables architects to query and analyze inventory data across multiple dimensions, drawing on internal documentation from repositories such as 麻豆原创 LeanIX, Confluence, and SharePoint. Architects can identify missing fields and conduct gap analysis within their workflow, reducing the need to manually search documents or switch between applications. By bringing contextual research and analysis into 麻豆原创 LeanIX, the assistant helps shorten information searches, simplify navigation and data management tasks, and strengthen inventory quality and governance.

Get started .

The general availability for Enterprise Architecture Assistant is now underway in a phased approach.

Data Management Assistant

• Transition Data Quality Scope Agent
• Transition Data Quality Evaluation Agent
• Transition Data Quality Prioritization Agent
• Transition Data Quality Validation Agent
• Transition Data Quality Automated Resolution Agent
• Data Management Orchestration Agent

Data management teams can identify, prioritize, and correct data quality issues across the transformation life cycle with the Data Management Assistant. Its Q3 lineup connects six agents within a governed workflow: the Transition Data Quality Scope Agent selects relevant KPIs, while the Transition Data Quality Evaluation Agent analyzes execution results to identify trends and severity. Teams can focus on the most important corrections with the Transition Data Quality Prioritization Agent, then identify source systems and verify proposed fixes through the Transition Data Quality Validation Agent. The Transition Data Quality Automated Resolution Agent executes corrections only after human approval, with the Data Management Orchestration Agent coordinating the specialized agents throughout the process. By combining ongoing monitoring, actionable recommendations, and sandbox validation before production deployment, the assistant helps teams reduce correction risks, detect emerging issues, and maintain data governance at scale.

Get started .

The general availability for Data Management Assistant is now underway in a phased approach.

Process Transformation Assistant

• Process Consulting Agent

Business users and process analysts can uncover opportunities for improvement and turn insights into prioritized actions with the Process Transformation Assistant in 麻豆原创 Signavio. It combines conversational process mining with data preparation, tailored recommendations, and structured value cases to reduce configuration effort and support faster decisions. In Q3, the Process Consulting Agent lets users explore processes through natural-language questions, using multi-agent reasoning to retrieve relevant data, perform analyses, and translate findings into contextual recommendations and next-best actions. This helps users without specialist analytical skills contribute to process improvement while freeing analysts from time-consuming searches. Estimated benefits of the agent include a 90% reduction in time spent on complex data searches per artifact and a five percent reduction in average time spent analyzing, designing, modeling, and monitoring a process.

Get started .

The general availability for Process Transformation Assistant is now underway in a phased approach.

ALM Dashboard Generation Agent

IT and operations teams can use the ALM Dashboard Generation Agent to create graphical dashboard cards from system and service data in 麻豆原创 Cloud ALM through natural-language prompts. The agent helps users build personalized, role-specific monitoring dashboards without extensive data expertise, making it easier to tailor views to operational needs and deliver relevant insights to each user. This can reduce dashboard creation and maintenance effort by 75% and increase business productivity by 25% through faster access to customized information.

Get started .

This capability is generally available.

ALM Alert Resolution Agent

Alert processors can use the ALM Alert Resolution Agent in 麻豆原创 Cloud ALM to analyze alert details, including error messages, thresholds, related issues, and system context, and gain a comprehensive view of the current situation. The agent automates initial triage, searches help documentation, knowledge base articles, and 麻豆原创 Notes, and provides recommended troubleshooting and resolution steps directly on the Alert Details page. This helps reduce mean time to resolution, lower manual triage and troubleshooting effort, improve system uptime, and standardize incident resolution with consistent, AI-guided workflows.

Get started .

This capability is generally available.

麻豆原创 Regulatory Insights

Compliance officers can use 麻豆原创 Regulatory Insights to manage complex and evolving compliance requirements. The solution extracts and structures control requirements from lengthy regulatory documents, compares regulatory versions to identify new, changed, or withdrawn requirements, and analyzes the extent to which existing internal controls provide coverage. AI-driven recommendations help identify potential controls for closing gaps, while validation and contextual analysis support accurate mapping of related regulatory and control language. APIs enable integration with existing compliance and risk management systems, helping organizations reduce manual effort, improve transparency, maintain consistent data, and strengthen compliance processes at scale. By helping teams identify regulatory changes earlier and understand complex documents faster, the solution can help reduce penalties or rework costs from missed changes by 25% and reduce the average time spent comprehending regulatory documents by 70%.

Get started .

This capability is available as beta release.

麻豆原创 Cloud ALM, AI-assisted operations score optimization

IT and operations leads responsible for 麻豆原创 S/4HANA landscapes in RISE with 麻豆原创 can use the AI assistant in 麻豆原创 Cloud ALM Operations View to understand Operations Index scores and their day-to-day impact. The assistant translates technical metrics, KPIs, and configuration data into clear, context-aware explanations, identifies the primary factors affecting current scores, and highlights the systems, configuration gaps, or runtime issues that need attention first. This helps operations owners prioritize actions, allocate effort effectively, and make faster decisions aligned with clean core principles without manually interpreting every dashboard chart or KPI.

Get started .

This capability is generally available.

Industry AI

Spare Parts Request Processing Agent

Spare Parts teams can use the Spare Parts Request Processing Agent to process requests from multiple input channels and initiate the creation of sales quotations in the target system. The agent identifies the appropriate parts and involves experts when request details are missing or ambiguous, helping ensure accurate responses without requiring specialists to manually manage every request. This reduces the time and effort required to respond to customers, shortens the time to create quotes, increases spare-parts sales, and improves customer satisfaction.

Get started .

This capability is available in 麻豆原创 Early Adopter Care.

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.

I鈥檝e spent most of my career building supply chain technology to drive business outcomes at scale. Earlier in my career, nobody was talking about AI. But I was helping build what we鈥檇 now call an autonomous supply chain.

At scale, manual decision-making simply cannot keep pace with growing consumer expectations. That鈥檚 why the next phase of supply chain AI needs to move beyond analysis to help organizations turn insights into action across the processes and applications that move goods. 

Decision velocity: where supply chain speed is won or lost 

Even the most intelligent supply chains can struggle to turn a meaningful signal into a well-governed response. I think of that as decision velocity: how quickly an organization can recognize change and coordinate the right response based on relevant business context.听

In supply chain, decisions are inherently interconnected. Planning affects manufacturing, which depends on product and asset readiness, suppliers, logistics partners, and more. I hear this from our customers today: each decision could be rational; the sum of them was not.听

AI can automate individual tasks, but isolated intelligence only creates isolated value. 

Agents need to understand how a decision in one domain affects the next. That鈥檚 where supply chain applications become critical, providing the business context, connected processes, and controls that agents need to act. 

New Joule Agents extend AI across the supply chain 

This year at 麻豆原创 Connect, we’re expanding the capabilities of six Joule Assistants introduced earlier at 麻豆原创 Sapphire and adding specialized Joule Agents that can take on critical supply chain tasks. These capabilities will help organizations respond faster and automate more routine work while keeping people at the center of informed decision-making: 

• The Product Design Assistant will be able to interpret product designs, recipes, and specifications and orchestrate compliant product changes, helping accelerate time to market.听
• The Supply Chain Planning Assistant will help planners sense, simulate, and resolve exceptions in a single workspace, helping teams understand downstream impacts and address disruptions before they ripple across the enterprise.听
• The Manufacturing Assistant will help teams respond to plant-floor disruptions as they happen, while new capabilities in the Logistics Assistant span warehousing, outbound optimization, fulfillment, and transportation dispatching, helping turn logistics insight into action.听聽
• New agentic capabilities for the Asset Operations Assistant will help translate equipment and maintenance signals into action by supporting the initiation, screening, and simulation of maintenance requests. And the Business Network Assistant will improve collaboration with suppliers and logistics partners in areas such as sourcing, contracting, and exception handling. 

What connects these scenarios is the ability for agents to operate within the business context already governing the supply chain, so an insight in one area can inform the next and, when authorized, trigger coordinated action.听General availability for these new capabilities is planned for Q4 2026.听

Customer results show autonomy taking hold 

Customers are already putting this shift into practice.  

Takeda Pharmaceuticals will use the Supply Chain Planning Assistant to help pinpoint likely causes behind planning issues and propose corrective steps, supporting adaptive planning processes over time.  

Rebecca Kaufmann, senior vice president and head of Enterprise Platforms at Takeda Pharmaceuticals, said, 鈥淲e are combining the 麻豆原创 industry and technology knowledge with our organizational real-life experience. The Supply Chain Planning Assistant will provide us with AI-detected root causes and AI-suggested remediation and also automated performance tracking resulting in a self-healing capability.鈥澛犅�

Doehler, a global producer of natural ingredients for the food, beverage, life sciences, and nutrition industries, is applying AI to logistics issue resolution.  

Stephan Schissler, CIO at Doehler GmbH, says, “Our people’s greatest value lies in deciding what to do next鈥攁nd now they can focus entirely on that. The Logistics Issue Resolution Agent detects the root cause, recommends the resolution, and turns a multi-hour firefight into a one-click decision. Our logistics team has recovered roughly a third of the time once lost to troubleshooting, and our processes are becoming self-resolving rather than exception-driven.”聽

This is how autonomy delivers practical value: moving from manually managing exceptions toward more intelligent supply chain processes. 

Building autonomy on a foundation of trust 

As AI takes on a greater role in supply chain decisions, trust must be built into how it operates. Leaders need to understand what AI decided and why, define what it is authorized to complete, intervene when necessary, and know who is accountable. 

That is the direction behind everything we are introducing at 麻豆原创 Connect in 2026. By grounding Joule Assistants and their agents in the processes and data of the 麻豆原创 Supply Chain Management portfolio, we can help organizations move from insight to coordinated action while keeping people at the center of the decisions that matter most.听

For supply chain leaders, that is where autonomy becomes tangible: less time spent on routine work and resolving exceptions, faster responses when conditions change, and more time for the strategic decisions that strengthen resilience, efficiency and customer value. 

Ultimately, it comes down to decision velocity you can trust. 

Devesh Mishra is general manager and chief product officer for 麻豆原创 Supply Chain Management.

鈥淚t’s time to show you the Autonomous Enterprise in action underpinned by great customer stories,鈥� 麻豆原创 CEO Christian Klein told his keynote audience at the start of the event.  

Klein reminded the audience that 麻豆原创 introduced the Autonomous Enterprise at its 麻豆原创 Sapphire conference in May 2026 as 鈥渢he beginning of better.鈥� Since then, he said, 麻豆原创 has worked with hundreds of customers to implement Joule Work as the AI engagement layer for the Autonomous Enterprise. 

A new UI for AI 

鈥淭his month, we are rolling out Joule Work for all customers,鈥� Klein said, describing it as a new UI for AI. He noted that for decades, users had to learn how 麻豆原创 worked, but with Joule Work, 麻豆原创 learns how people work. 鈥淔rom now on, the more than 400 million 麻豆原创 users can talk in their own language to 麻豆原创, and Joule Work gets the job done.鈥� 

Click the button below to load the content from YouTube.

Always allow YouTube

Klein explained that Joule Work is based on three pillars: conversations, where users ask questions and delegate tasks to agents; spaces, which display content, insights, and shared work; and Joule Studio, where customers extend Joule or build agents tailored to their own processes.   

He called 麻豆原创鈥檚 deep business and data context its 鈥渟ecret sauce.鈥� That context includes 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, 50 million tables, more than 50,000 public and private APIs, 400 data products, and extensive process knowledge. 鈥淭hat’s why Joule doesn’t guess,鈥� he said. 

麻豆原创鈥檚 110,000 employees are already using Joule to perform hundreds of thousands of tasks every day, he shared: 鈥淲e are already seeing productivity gains in central functions like HR, finance, and procurement of over 20% and even bigger gains in more complex analytical and planning tasks.鈥� 

麻豆原创 Autonomous Suite 

Klein then turned his attention to the 麻豆原创 Autonomous Suite, the second layer in the Autonomous Enterprise. The suite initially covers five domains: finance, procurement, supply chain, human resources, and customer experience. 麻豆原创 Autonomous Suite is designed for work where a good answer is insufficient and 鈥渢he right answer鈥� is required every time, he said.  

鈥淟LMs are probabilistic and only give you the most likely answer,鈥� Klein said. He contrasted that probabilistic approach with 麻豆原创’s embedded agents. Because the agents operate within deterministic application workflows, they use the same data, follow the same rules, and leave the same audit trail as the applications themselves. Customers can choose the level of autonomy appropriate to each process, retaining human approval where risk is high and allowing greater automation for routine work. 

Since 麻豆原创 Sapphire, Klein said 麻豆原创 has created more than 20 Joule Assistants and over 200 Joule Agents, and is aiming for more than 400 agents by year-end. 鈥淏ut the real story isn鈥檛 the number of agents. It鈥檚 the business outcomes they deliver,鈥� he said. 

麻豆原创 Business AI Platform 

鈥淭hese agents can only understand your business so well because of the 麻豆原创 Business AI Platform,鈥� Klein said. 鈥淭he platform gives customers the best frontier model for every agentic use case, the deepest out-of-the-box business context and 麻豆原创-managed governance.鈥�  

Building on Klein鈥檚 remarks, Manoj Swaminathan, president and chief product officer of 麻豆原创 Autonomous Suite, described the 麻豆原创 Business AI Platform as the infrastructure that enables the Autonomous Enterprise. The platform is organized around three capabilities: building agents, contextualizing them with business data, and governing how they operate. 

Swaminathan explained how the context layer makes agents more accurate. Joule Studio spans no-code and professional development and offers access to more than 70 models, a strategy he said reduces lock-in and controls token costs.  

鈥淛oule Studio is natively integrated with our context layer,鈥� he said. 鈥淪o, the agents you build are more accurate, faster to deploy, and more efficient to run. Our knowledge graph is the map with the processes, data flows, and business tools. The agents find the right processes among thousands and the right information among over 7 million feeds. 麻豆原创 Business Data Cloud brings that understanding to all your data, one consistent view, the processes, policies, and logic to make it meaningful.鈥� 

Swaminathan said no AI can compensate for a broken data model. To help agents understand customers鈥� business rules, 麻豆原创 Domain Models are trained on 麻豆原创鈥檚 code. For predictions, 麻豆原创 provides two engines grounded in how a customer’s business operates: 麻豆原创-RPT, 麻豆原创’s model family trained on its business data, and the Prior Labs tabular AI model.

Jerseys from Jersey 

During his section of the keynote, Jan Gilg, global president of Customer Success & Americas, used an imaginary startup 鈥� 鈥淛erseys from Jersey鈥� 鈥� to invite a handful of customers to the stage to answer his questions and validate aspects of 麻豆原创鈥檚 Autonomous Enterprise strategy.  

The customers included Novartis, which is piloting Joule sourcing agents for bid analysis and negotiation support; Morgan Foods, which described a supply-chain transformation built on 麻豆原创 S/4HANA and 麻豆原创 Integrated Business Planning; Nestl茅, which emphasized the importance of a unified digital core; and 麻豆原创 customer and partner PwC, which spoke about the value of the Industry AI portfolio from 麻豆原创. 

Summing up their comments, Gilg noted that the elements of the 麻豆原创 Autonomous Suite 鈥渁re more than a collection of functional components. It鈥檚 one system working together like connective tissue that provides connectivity, context, and control.鈥�

Gilg also made several product announcements, including the launch of 麻豆原创 Pay, an embedded payments service that can automatically execute and reconcile supplier payments once an invoice is approved. He also announced 麻豆原创鈥檚 planned acquisition of TechWolf, a Belgian workforce-intelligence startup designed to help close skills gaps. 

Security and governance 

In the closing section of the keynote, 麻豆原创 Chief Security Officer Marielle Ehrmann focused on trust and governance. She noted that ransomware handovers that once took eight hours now take 22 seconds with AI, and while 83% of enterprises use AI daily, only 13% have real visibility into it.  

鈥淭he biggest threat to companies is not malicious AI; it鈥檚 unmanaged AI,鈥� Ehrmann said. To counter that threat, she said every agent should have a verified owner, a risk tier, and scoped access rights, supported by zero-trust checks on identity, purpose, and data sensitivity as well as human oversight. 

She emphasized that 麻豆原创 Business AI Platform incorporates regulatory and localization requirements, applies user authorizations, keeps customer data from being used to train foundation models, and supports three levels of oversight: human-in-the-loop approval, human-on-the-loop monitoring, and human-in-command override authority. 鈥淭he more autonomously an agent operates, the tighter the oversight applied,鈥� Ehrmann said, calling the principle 鈥渇reedom within boundaries.鈥� 

A clear shift among customers 

Wrapping up the keynote, Klein emphasized that trust is key to everything 麻豆原创 does and has been for over 50 years. 鈥淲e are delivering the most trusted and governed AI in the industry,鈥� he said, but added, 鈥淎I also requires significant change management to ensure it delivers the desired outcomes for your business.鈥� 

That is where 麻豆原创鈥檚 business transformation solutions come in, he said. 麻豆原创 Signavio measures process value before and after a change to help justify token spending; 麻豆原创 LeanIX discovers and tracks AI agents; and 麻豆原创 WalkMe supports user adoption and trust. Klein also highlighted an agent-led migration toolchain. Together, he said, these capabilities mean that the days of multi-million-dollar migration spend are gone.

鈥淭his is no longer the start of something better. This is better,鈥� Klein told the audience. He described a clear shift among 麻豆原创 customers: 鈥淔rom manual steps to connected workflows, from reactive decision-making to predictive insights, from humans in spreadsheets to humans in and on the loop–all powered by our AI platform to keep AI accurate, governed, and extensible.鈥�

And, most importantly, Klein said, 鈥淚ts ready for you today鈥� This is the Autonomous Enterprise.鈥� 

Joule Work, Joule Assistants and 麻豆原创 Business AI Platform help organizations turn business AI into trusted outcomes across every core function.

LAS VEGAS 鈥� (NYSE: 麻豆原创) today showcased the Autonomous Enterprise in action at 麻豆原创 Connect, demonstrating how Joule Work and Joule Assistants generate value for customers across every line of business.

“This is a breakthrough moment for business AI,” said Christian Klein, CEO of 麻豆原创 SE. “The Autonomous Enterprise has arrived. With Joule and 麻豆原创 Autonomous Suite, built on 麻豆原创 Business AI Platform, we’re helping organizations like Novartis, Morgan Foods, Nestl茅 and PwC connect intelligence across every function to deliver trusted business outcomes.”

At 麻豆原创 Connect, these customers shared how the Autonomous Enterprise is already driving measurable value across their businesses:

• 鈥淲e’ve co-developed and recently launched a pilot of 麻豆原创’s Joule Sourcing Assistant,鈥� said Christoph Buerki, Head of Procurement, Novartis. 鈥淥ur vision is for AI agents to handle the manual heavy lifting, enabling sourcing professionals to focus on strategy, supplier engagement and value creation.鈥�
• 鈥淎t Morgan Foods, we鈥檙e already putting the pieces in place for agentic adoption, especially through our technical foundation. The biggest shift will be moving from reactive to predictive, where agents can connect demand signals, inventory levels and supplier status faster than ever before,鈥� said Steve Hankins, Chief Financial Officer, Morgan Foods, 鈥淥ur superpower will come from people on top of agents. Our approximately 1,000 employees are what make our supply chains work鈥攖he technology helps make them even better.鈥�
• 鈥淥ur 麻豆原创 S/4HANA transformation across 140 countries is creating a connected digital core with consistent processes, trusted data and greater visibility across markets and functions. With that foundation, Joule and the Accounts Receivable Assistant can automatically prioritize collections work based on risk and business context, recommend the next best action and help our finance teams respond faster to change,鈥� said Luca Dell’Orletta, Global Head IT Innovation & Enterprise Architecture, Nestl茅.
• 鈥淚n professional services, billing can be one of the more error-prone processes, with accuracy playing an important role in the client experience. 麻豆原创鈥檚 Billing Assistant brings greater intelligence to this critical process, helping identify potential issues earlier so our people can deliver better client outcomes and build stronger relationships,鈥� said Jill Notz, Chief Accounting Officer, Controller, Business Services Leader, PwC. Building on the success of the Billing Assistant, PwC and 麻豆原创 are into new areas of joint AI innovation.

麻豆原创’s Autonomous Enterprise Scales Up

Joule Work is beginning its customer rollout as a new AI user interface that lets employees interact with 麻豆原创 solutions in their own language and complete work across 麻豆原创 and third-party data. Grounded in business context from 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, Joule provides information users can rely on. At 麻豆原创, Joule Work is already live with 110,000 employees, with the company seeing 20% productivity gains across finance, HR and procurement. A select group of customers also is using Joule Work in their business environments.

• 鈥淧artnering within the Early Adopter Program for Joule Work Desktop has delivered more momentum in just a few months than we saw in all the years before,鈥� said Peter Wied, Director of Complexity Management at Reinhausen. 鈥淲e see huge potential in making access to our 麻豆原创 S/4HANA data significantly easier and faster through natural language. This has the potential to permanently transform how our teams interact with business data.鈥�
• 鈥淭he dedicated team has been phenomenal. Their proactive communication, focus on accelerating architecture activation, rapid remediation of defects and overall support have enabled us to become Joule ready much sooner than would have been possible had we needed to navigate these challenges on our own,鈥� said Keith Smith, 麻豆原创 Platform Architect, CONA Services. 鈥淭he CONA team is excited about the progress made to date and looks forward to exploring and testing Joule’s capabilities in greater depth over the coming months as we continue our adoption journey.鈥�

When a query is not enough, Joule Assistants execute operational work directly within business workflows, using established data, authorizations and audit trails. Customers control the level of autonomy. 麻豆原创’s approach is also open: through the Agent2Agent protocol, Joule can connect with third-party AI and agents, bringing governed business context into broader AI workflows.

At 麻豆原创 Connect, 麻豆原创 showcased how these capabilities generate outcomes across 麻豆原创 Autonomous Suite:

• In finance, controllers can automate revenue recognition, disclosures and trade compliance, with early deployments of the International Trade Assistant reducing trade classification effort by up to 50%.  
• In supply chain, planners can turn multi-hour disruptions into one-click resolutions across planning, manufacturing and logistics.
• In HR, leaders can determine the best way to close workforce gaps, while employees can make smarter benefits choices tailored to their needs.
• In procurement, decision-makers can identify savings opportunities against peer benchmarks and manage the full contingent workforce life cycle.
• In customer experience, organizations can turn customer engagement into sales opportunities with AI-powered campaigns, quoting and customer workflows.
• Across industries, 麻豆原创 is collaborating with customers to apply AI to specialized industry processes, helping organizations in manufacturing, retail, commodity trading and asset-intensive industries improve decision-making, automate routine actions and build more resilient operations.

The Platform Powering Business AI You Can Trust

麻豆原创 Business AI Platform gives organizations one place to build, contextualize and govern AI across 麻豆原创 and third-party environments. With Joule Studio, business users and developers can build and extend skills and agents from no-code to pro-code workflows, choosing from more than 70 AI models. 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption.

麻豆原创-managed governance helps organizations scale AI with transparency, accountability and control. 麻豆原创 AI Agent Hub in 麻豆原创 LeanIX solutions provides a central inventory of enterprise agents, while 麻豆原创鈥檚 independently ISO/IEC 42001-certified governance architecture supports regulatory requirements, established authorizations and auditable AI operations.

To help organizations adopt AI at scale, 麻豆原创’s Business Transformation Management portfolio, including 麻豆原创 Signavio, 麻豆原创 LeanIX and 麻豆原创 WalkMe solutions, provides the toolchain to analyze processes, govern applications and agents, and drive adoption across the enterprise.

麻豆原创 Brings Embedded Payments to Cloud ERP

麻豆原创 also announced that it is entering the payments market with 麻豆原创 Pay, powered by Tereina, an 麻豆原创 company. Embedded directly in 麻豆原创 Cloud ERP, 麻豆原创 Pay executes and reconciles payments within the same workflow when an invoice is due, reducing manual file handling and external processing dependencies, while giving customers greater control.

Partners Expand the Reach of Autonomous Business

麻豆原创 is extending the Autonomous Enterprise beyond 麻豆原创’s own application portfolio through new partnerships that bring specialized intelligence directly into 麻豆原创 workflows.

A new partnership between 麻豆原创 and Moody鈥檚 Corporation is designed to embed Moody鈥檚 supplier risk monitoring data into 麻豆原创 Ariba Supplier Lifecycle and Performance. This gives procurement teams continuously updated insights into supplier financial health, operational risk and regulatory status at the point of decision. Organizations will be able to move from periodic risk reviews toward continuous monitoring, enabling Joule Agents to flag supplier risk signals and surface alternatives before disruption affects the business.

An expanded partnership with ORO Labs brings procurement orchestration to 麻豆原创 customers as a solution extension. 麻豆原创 Ariba Procurement Orchestration by ORO Labs is a purpose-built orchestration layer that connects procurement workflows end to end across heterogeneous enterprise environments, giving business users a seamless experience for intake, actions and visibility.

Visit the . Get 麻豆原创 news via  and .

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�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Aim茅e Leabon, +1 (212) 653-9600, aimee.leabon@sap.com, EDT
麻豆原创 麻豆原创 Room; press@sap.com

This press release was created with the assistance of artificial intelligence and has been reviewed by the editorial team.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 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.
Please consider our . If you received this press release in your e-mail and you wish to unsubscribe to our mailing list please contact press@sap.com and write Unsubscribe in the subject line.鈥�

The hand-crafted stringing on the face of the racket, the customized design, the packaging and distribution, and the systems that enable each touchpoint are all part of a global supply chain that ensures the racket gets from the warehouse into the gear bag of the world No. 5 exactly when he needs it.

That journey鈥攆rom raw materials and global suppliers through manufacturing, warehousing, customs, and last-mile delivery鈥攊s a story. And 麻豆原创 helps power it.

The carefully curated racket, along with Wilson鈥檚 shoes, shirt, cap, and shorts de Minaur chooses to wear as he competes at the highest level, are just a few of the thousands of products Wilson manufactures and delivers to athletes and customers around the world.

Behind each product is an interconnected global operation spanning manufacturing, warehousing, retail, e-commerce, and B2B channels and a digital foundation that helps Wilson keep it all moving seamlessly.

Powering a global sporting goods business

Wilson is a global leader in sports equipment and apparel, with a legacy of more than a century of innovation across tennis, basketball, baseball, golf, and other sports. From developing high-performance equipment for the world鈥檚 best athletes to creating products for players at every level, Wilson combines deep sporting expertise, innovation, and craftsmanship to help athletes perform at their best.

For almost two decades, Wilson has trusted 麻豆原创 to run its global operations, connecting hundreds of employees across finance, sales, logistics, warehousing, and other critical retail functions.

Wilson’s 麻豆原创 landscape spans core enterprise resource planning (ERP), supply chain management, data and analytics, procurement, travel, global trade, integration and enterprise architecture. Its current environment includes 麻豆原创 ERP Central Component (麻豆原创 ECC), 麻豆原创 Analytics Cloud, 麻豆原创 Datasphere, , and 麻豆原创 Business Technology Platform, as well as 麻豆原创 Ariba, 麻豆原创 Concur, and 麻豆原创 LeanIX solutions, among others.

And Wilson’s 麻豆原创 digital transformation is continuing. The company is preparing for a major 麻豆原创 S/4HANA transformation beginning in 2027, which will unlock new capabilities across areas such as extended warehouse management (EWM), transportation, quality, and omnichannel operations. As part of its 麻豆原创 S/4HANA journey, Wilson uses Joule to assist with code conversion marking the beginning of introducing into its business operations

One connected foundation for a connected customer experience

Beyond professional athletes such as de Minaur that choose to utilize Wilson to perform on and off the court, Wilson’s global customers interact with the company in many ways鈥攖hrough retail stores, e-commerce, and B2B channels. Behind those experiences is a complex network of products, inventory, orders, warehouses, and business processes that need to work together.

Built for the pace of sport

The world of professional sports moves quickly. A tennis match can turn in a matter of seconds. Consumer goods organizations like Wilson run an equally dynamic and demanding global operation: designing, manufacturing, moving, and selling products to customers and athletes around the world.

A major event, such as a Grand Slam or a Wilson ambassador winning a tournament, can bring heightened demand for the products athletes use and fans want to buy. This requires Wilson to coordinate inventory, production, warehouses, retailers, and e-commerce across markets and respond quickly as demand changes. 麻豆原创 solutions such as 麻豆原创 Extended Warehouse Management, 麻豆原创 Global Trade Services, 麻豆原创 Concur and 麻豆原创 Ariba provide Wilson with the digital foundation to run smarter, operate faster, and respond to the ever-changing demands running a global retail business

This September in New York fans will see Alex de Minaur compete with his trusted Wilson racket and adorn his new customized Wilson kit. What they won鈥檛 see is the integrated ecosystem and the multifaceted journey behind every single racket, every pair of shoes, every piece of apparel鈥攁nd the 麻豆原创 technology powering it.

Tennis is a game of preparation. When I walk onto the court, every detail matters鈥攆rom how the racket feels in my hand to the kit I’m wearing. Knowing that Wilson and the technology behind their business makes sure everything is ready exactly when I need it, that’s the kind of confidence that lets me focus on competing at my best.

Alex de Minaur

Whether it鈥檚 a game of tennis or the demands of a global business, success depends on having everything working in harmony. With 麻豆原创, Wilson can perform at its best.

And on the court, Alex de Minaur knows he can trust that everything is in place when the moment matters most.

Supply chain leaders today operate in an environment where disruptions are constantly changing, customer expectations shift quickly, and the window for effective response keeps shrinking. Organizations need more than digitalization. They need platforms that connect people, processes, data, and business networks鈥攁nd that turn that connectivity into faster, better decisions.

Our vision: Autonomous Supply Chain Management

The next frontier in supply chain is not just connectivity, it is decision intelligence. At 麻豆原创, represents our vision for how organizations will run their businesses in the future, with data, business context, policy, and AI reasoning working together so that the right decisions happen faster, more consistently, and at scale, while human judgment remains central.

is a practical step toward that vision, where people define goals and priorities, AI assistants orchestrate activity across domains, and agents execute the work within governed, end-to-end processes. Enterprises rely on fully autonomous agents to run supply chain processes and decisions within guardrails defined by the organization. Reaction times to disruptions compress from days to minutes. Data collection across organizational silos happens in near real time. Rather than manually collecting and interpreting data, planners receive auto-generated scenarios that are pre-validated and ready for a decision. That speed advantage is transformative.

But the value goes beyond speed. Organizations learn from past decisions and harmonize decision-making across the enterprise, leading to consistently better outcomes over time. AI delivers the greatest value when it is embedded where work actually happens, grounded in deeply integrated processes and trusted data.

Our approach

A truly integrated supply chain platform does more than connect data鈥攊t connects decisions. That is the principle that guides how we have built the , and it is what we believe sets 麻豆原创 apart.

Our breadth across execution, transactions, business networks, finance, and AI is unique. No other vendor brings together operational systems, trusted business data, and intelligence and orchestration in a single, deeply integrated suite. That breadth matters because supply chain decisions do not happen in isolation鈥攁 sourcing decision affects manufacturing capacity, which affects logistics, which affects financial commitments. When those systems are connected, decisions improve across the board.

We organize our platform around three layers. The first is operational systems, including applications such as , , , , , , and . These are where supply chain work happens. The second is trusted business data, anchored by , which aggregates data from 麻豆原创 and third-party sources to help give organizations a unified, real-time view across the enterprise. The third is intelligence and orchestration, delivered through , our AI engagement layer, which brings together agentic AI, embedded analytics, and network-enabled execution to help organizations move from reactive problem-solving to proactive decision-making.

This architecture helps organizations standardize processes across domains, reduce dependence on fragmented point solutions, and improve coordination from sourcing through final delivery鈥攍inking operational, financial, and network outcomes in real time.

Putting innovation into practice

We see demand for capabilities that bring together operational data, business context, and AI-powered insights, and we are actively investing to meet that need. New Joule Assistants are being embedded across planning, manufacturing, logistics, asset management, and supplier collaboration, helping teams act on changes faster and reduce time spent on manual coordination.

Alongside these assistants, we are delivering purpose-built AI agents across supply chain processes, designed to take guided action within defined business guardrails while keeping people firmly in control. These capabilities are becoming available in phases through 2026, aligning with customers鈥� existing 麻豆原创 landscapes.

Delivering real results for customers

Ultimately, in our opinion, recognition like this is only meaningful when it reflects real impact for the organizations we serve. Takeda Pharmaceuticals International AG, a global leader in R&D-based biopharmaceuticals, offers a concrete example of what this looks like in practice. Using 麻豆原创鈥檚 supply chain planning assistant, Takeda has moved from manual root-cause analysis to AI-detected diagnostics and AI-suggested remediation, with automated performance tracking that enables a self-healing supply chain capability.

鈥淎I represents the key enabler for Takeda鈥檚 transformation for the future,鈥� said Rebecca Kaufmann, senior vice president and head of Enterprise Platforms at Takeda Pharmaceuticals. 鈥淲e are combining the 麻豆原创 industry and technology knowledge with our organizational real-life experience. The supply chain planning assistant will provide us with AI-detected root causes and AI-suggested remediation and also automated performance tracking resulting in a self-healing capability.鈥�

Looking ahead

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. Supply chain teams are increasingly looking to spend less time monitoring and firefighting and more time shaping decisions, managing trade-offs, and building resilience.

We are grateful to the many customers, partners, analysts, and 麻豆原创 teams whose collaboration and insights help shape our products and strategy. While we are honored by this recognition, we view it as an important milestone for us rather than a destination. We remain committed to ongoing innovation that helps organizations transform their supply chains into strategic sources of competitive advantage鈥攁nd we thank our customers for their trust in that journey.

Devesh Mishra is GM and chief product officer for 麻豆原创 Supply Chain Management.

*Gartner, Magic Quadrant for Supply Chain Management Suites, Jan Snoeckx, Balaji Abbabatulla, Christian Titze, August 11, 2026.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
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.

For Lemvigh-M眉ller, an efficient supply chain isn’t a nice-to-have鈥攊t’s the business model. “Our company is low margin, and we are living from a very efficient supply chain,” says Frederik Aakerlund, CIO of Lemvigh-M眉ller. “We need to cut costs wherever we can, and we need to make sure our customers get our products as quickly as possible.”

Not every business partner connects via EDI (Electronic Data Interchange), the standard for exchanging business documents directly between IT systems. For Lemvigh-M眉ller, that means a steady stream of orders, delivery notes, and invoices arriving as PDFs and emails鈥攄ocuments that, until recently, had to be read and entered manually.

“Today we are receiving so many PDF files and emails that we don’t have the time to read them,” Aakerlund explains. “Basically, we don’t update our system, or we don’t find the deviations from what we expect, quickly enough.”

Click the button below to load the content from YouTube.

Always allow YouTube

Letting AI read the mail

To close that gap, the team built a use case for receiving documents from business partners that can’t be exchanged via EDI and having them read automatically by 麻豆原创 AI engines.

“This is exactly where AI is helping us,” Aakerlund says. “It’s reading 10 20-page documents in a few seconds, updating our system, and there’s no person involved.”

Behind the scenes, the solution combines a mix of 麻豆原创 Business AI Platform, AI components, and 麻豆原创 Fiori apps, integrated with Lemvigh-M眉ller’s core 麻豆原创 system鈥斅槎乖� Cloud ERP Private, which the company adopted two years ago.

The shift in daily work is tangible. “Our users, instead of reading a lot of emails, are just working in a dashboard, finding the things they need to work on,” Aakerlund says. “We’re living the in a small part of our business.”
What started as a single use case has since become a template. “We’ve kind of made it a template for receiving business documents like orders, delivery notes, invoices, and so on,” Aakerlund notes. “Whenever we can’t get them digitally, we read them via this new system. It works for all kinds of PDFs and emails we receive from our business partners.”

Aakerlund’s advice to other companies considering AI projects: don’t start big.

“A good piece of advice could be to find the pockets of inefficiency in your company and apply AI there, instead of going for some really, really big project,” he says. The first version of the use case took just 200 hours over 10 weeks to build. “It turned out to be a reusable architecture, with reusable templates for a lot of other business processes.”

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.

Click the button below to load the content from YouTube.

Always allow YouTube

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.

.

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.

.

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%.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

Click the button below to load the content from YouTube.

Always allow YouTube

.

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.

.

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.

.

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.

.

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.

Click the button below to load the content from YouTube.

Always allow YouTube

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

.

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.

Click the button below to load the content from YouTube.

Always allow YouTube

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.

Click the button below to load the content from YouTube.

Always allow YouTube

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.

.

Visit the . Get 麻豆原创 news via  and .

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�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Aim茅e Leabon, +1 646-799-3277, aimee.leabon@sap.com, EST
Marcus Winkler, +49 622 776-74-97, marcus.winkler@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.
Please consider our . If you received this press release in your e-mail and you wish to unsubscribe to our mailing list please contact press@sap.com and write Unsubscribe in the subject line.

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 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 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.  This 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

• Joule with 麻豆原创 Logistics Management 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.  

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 processing of incoming quality certificates, 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

Click the button below to load the content from YouTube.

Always allow YouTube

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

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

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

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

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

Some highlights from Q1 2026:

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

Joule

Joule, enhancements

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

To set up, see: , , and .

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

For more information, see .

麻豆原创 Joule for Consultants, enhancements

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

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

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

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

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

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

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

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

Get started .

SECTION

麻豆原创 Business AI for supply chain

Project Setup Agent
Beta release

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

and get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

麻豆原创 Business AI for finance

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

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

Get started .

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

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

Get started .

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.

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

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

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

Get started .

麻豆原创 Business AI for spend management

Expense Report Validation Agent
General availability

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

Get started .

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

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

Get started .

Expense Automation Agent
麻豆原创 Early Adopter Care

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

See the demo .

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

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

Get started .

Policy Navigator
麻豆原创 Early Adopter Care

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

Get started .

麻豆原创 Business AI for procurement

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

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

Get started .

麻豆原创 Business AI for customer experience

Catalog Optimization Agent
General availability

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

Get started .

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.

Get started .

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.

Get started .

Joule with 麻豆原创 Datasphere
General availability

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

Get started .

麻豆原创 Document AI, enhancements

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

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

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

Generative AI Hub in AI Foundation, enhancements

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

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

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

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

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

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

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

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

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

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

See .

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

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

Get started .

麻豆原创 Business AI for industries

Tender Analysis Agent
General availability

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

Get started .

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

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

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.