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%.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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%.

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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.

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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.

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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.

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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.

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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%.

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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.

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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.

According to research from the , 72% of executives believe organizations claiming to transform work with AI are primarily automating existing processes rather than fundamentally redesigning how work gets done. Yet, 88% say redesigning work and roles creates significant enterprise value. And HR is ranked as the No. 1 owner of that work. As a result, HR and business leaders are looking at how technology can support their need to continuously align people, skills, and work with evolving business priorities.

This is the journey to . Autonomous HCM is the future of human capital management, where AI automates end-to-end processes, drives context-aware decisions, and optimizes workforce operations at scale.

As we think about Autonomous HCM, we have defined three pillars:

1. Automate the HR function to release capacity from administrative work: HR teams currently spend a significant share of their time on operational activities such as payroll, service delivery, recruiting administration, and workforce management. AI can reduce much of that burden, creating capacity for more strategic work. But automation is not the destination. It’s the foundation. The true value comes from what organizations do with the time and resources they regain.
2. Redesign how tasks, workflows, roles, and teams are structured throughout the enterprise, across both people and AI: For decades, companies optimized around jobs, functions, and fixed processes. AI challenges many of those assumptions. The opportunity is no longer simply to make existing work more efficient. It is to rethink work itself. This is not just a technology initiative. It is one of the most important business transformation challenges organizations face today.
3. Reinvent how organizations recruit, develop, move, and reward their people: Most talent processes were built for a world characterized by stable jobs and predictable career paths, but that world is rapidly changing. Organizations that succeed will create talent ecosystems that can adapt as quickly as the business itself.

These three pillars are all interconnected: automation releases capacity, work redesign determines how value is created, and talent-system reinvention makes the new model sustainable.

What makes this possible is 麻豆原创鈥檚 unique ability to bring together trusted workforce data, connected business processes, ontology, and AI within a single business context. Together, this context enables organizations to move beyond isolated HR activities and make strategic workforce decisions that drive the most urgent business outcomes. This context is what matters.

During 麻豆原创 Connect, 麻豆原创 announced that it has entered into an agreement for 麻豆原创 to acquire TechWolf. TechWolf provides a leading AI work intelligence platform, which helps organizations understand the work their people do and the skills they have, giving them the right context and the right grounding. Once the transaction closes, TechWolf is expected to power workforce and talent strategies across the 麻豆原创 SuccessFactors portfolio, bringing skills mapping, workforce planning, and organizational redesign informed by context from across the Autonomous Enterprise to guide decisions about development, deployment, and workforce transformation.

New Innovations to 麻豆原创 SuccessFactors HCM Suite

While Autonomous HCM is our vision for the future, we have several new innovations spanning the entire 麻豆原创 SuccessFactors HCM suite, available this month, including:

A growing portfolio of AI assistants

New AI assistants orchestrate work end-to-end and support decisions in real time. Many of the agents that we announced at 麻豆原创 Sapphire are available this month, including assistants for payroll, HR service, learning, recruiting, onboarding, and career and development. We have more agents coming soon, including the new Workforce Planning Assistant to support customers using . It is powered by connected workforce, contingent labor, and financial data from 麻豆原创 SuccessFactors, , and , to help business and HR leaders forecast workforce needs and create plans for the most effective mix of hiring, reskilling, redeployment, and external talent to address changing workforce demands.

Significant updates to our global benefits solutions

Benefits are among the most important decisions employees make, and they can also be some of the most complex for HR teams to support. To help make benefits administration more efficient for HR and benefits decisions more personalized for employees, 麻豆原创 announced two new innovations built natively into 麻豆原创 SuccessFactors Employee Central. The new agentic admin console for U.S. benefits provides HR administrators with a centralized view of benefits enrollment activity and exceptions, helping them quickly identify and resolve issues with built-in monitoring and natural language support. By reducing time investigating enrollment issues and navigating reports, organizations can improve oversight and manage complex enrollment periods more efficiently. Additionally, the new benefits decision support tool uses employee data already in the system to recommend coverage aligned to individual needs and budgets, resulting in a more personalized and intelligent enrollment experience for employees. 

New integration of WalkMe Learning Arc with

Creating and deploying learning content can often take weeks, making it difficult for organizations to respond quickly to changing business needs. With this new integration, learning teams can describe learning requirements in natural language, and AI generates courses and quizzes while maintaining author control. Learning experiences can then be created and deployed directly within 麻豆原创 SuccessFactors Learning in hours rather than weeks.

Shaping Autonomous HCM with our customers

As we look forward, we know that what has worked in the past will not take us to the future. The goal is not simply to showcase technology, but to prove how connected AI can help organizations translate strategic decisions into measurable workforce and business results faster and more effectively. Rather than organizing our innovation around individual products or modules, we are focusing our innovation around the most important outcomes our customers are trying to achieve鈥攁nd in doing so, leaning into 麻豆原创鈥檚 strength in connecting data, workflows, and processes across the entire 麻豆原创 portfolio. We will co-innovate with select customers to define, validate, and measure outcome-driven approaches that connect workforce decisions directly to business value, proving the value of our innovations in real time.

The journey starts now

We are at a defining moment for HR leaders. The future of work will not be shaped solely by technology. It will be shaped by the leaders who can translate transformation into meaningful outcomes for their organizations and their people.

Autonomous HCM is the future of HCM. But it does not start tomorrow. The journey starts today.

To learn more about the latest 麻豆原创 SuccessFactors innovations and how 麻豆原创 is helping organizations advance their journey toward Autonomous HCM, .

Siva Sundaresan is general manager and chief product officer for 麻豆原创 SuccessFactors.

Many of the futures we have explored are no longer hypothetical. They are showing up in how work is organized and experienced today. The fundamental question now is whether organizations are shaping those changes deliberately or simply reacting as they unfold.

combines monitoring of more than 500 business, academic, government, and economic resources with original global mixed methods research involving 2,718 employees, 500 C-suite leaders, 60 HR executives, and founders of AI-native companies. It points to a fundamental concern: organizations may be optimizing the future of work for efficiency when they should be designing it for value.

The productivity trap

In October 2025, we explored 10 predictions for work, workforces, and work practices, each with two possible futures. A year later, the evidence is strongest for what we call the “AI Upgrade” future, in which AI鈥檚 value is measured through efficiency, productivity gains, and time savings. Signals of broader work transformation are emerging, but they remain less established.

The emphasis on productivity is understandable because time savings, output, and cost reductions are relatively easy to measure. The harder question is what organizations do with the capacity AI can create. They can ask employees to produce more of the same work, or they can redesign work, roles, teams, and talent systems around what people and AI can achieve together.

Work transformation needs a north star

Related research from our found that 88% of employees said their jobs have changed because of AI, yet half of those changes occurred without meaningful guidance from managers or their organizations. Employees are using AI to simultaneously offload tasks and expand the scope of their work, often without a shared playbook or a clear view of the intended outcome. 

Before organizations can transform work intentionally, they need a clear north star for what work should become. Yet between 55% and 70% of employees said they had received no clear organizational guidance on the work shifts they are expected to navigate. At the same time, 72% of C-suite leaders said that most organizations claiming to transform work with AI are really automating existing jobs faster. Without a shared vision for work transformation, organizations risk defaulting to isolated experimentation and efficiency-first use cases, creating uneven outcomes and limiting the combined potential of people and AI.

Six shifts to guide better work design

We endorse six shifts in work and organizational design that are both enabled by AI and associated with work-enriching characteristics well established in organizational psychology as leading to increased employee motivation, effort, performance, and retention:

• From specialist to generalist: Apply core expertise across a broader range of problems and tasks.
• From static jobs to dynamic roles: Organize work around flexible responsibilities and outcomes that evolve with business needs.
• From pyramid to diamond organizational design: Reduce coordination layers and concentrate more people closer to where core work happens, enabling them to own end-to-end delivery.
• From output to impact: Evaluate work by the value it creates, not simply by activity or deliverables.
• From centralized authority to decentralized decision-making: Move decisions closer to the people and teams with the context to act.
• From people management to self-leadership: Give employees greater ownership of their direction, performance, and growth.

Through an experimental study, we validated how all six shifts can enrich work. For example, employees perceived 77% greater autonomy under decentralized decision-making, while dynamic roles were perceived as 49% more challenging than static jobs. The full report examines these effects across all six shifts, compares where organizations are today with where employees believe they need to be, and offers a prioritized path for leaders to get started.

Work transformation requires HR transformation

If work shifts this substantially, the function responsible for the people agenda cannot assume its own role and structure will remain the same. HR was built for fixed jobs, predictable career paths, established hierarchies, and talent systems designed for consistency. AI challenges each assumption.

With this context, we see HR鈥檚 new mandate as focused on three interconnected pillars:

• Automate: Use automation and intelligent systems to release capacity from administrative work and create space for more strategic contribution. C-suite leaders estimate that 49% of HR work will be fully automated within five years, compared with 35% of enterprise work overall.
• Redesign: Lead enterprise work redesign by determining how tasks, workflows, roles, and teams are structured across people and AI. Executives ranked work redesign as the transformation pillar that will create the greatest enterprise value over the next five years and identified HR as its leading owner.
• Reinvent: Overhaul recruitment, development, mobility, performance, and rewards to support how work now gets done and who succeeds in the new way of working. Seventy-five percent of executives agree that organizations can succeed in the AI era only if they reinvent how they measure, reward, and grow people.

In the full report, we also explore four plausible futures for how these pillars might come together to shape HR鈥檚 strategic contribution, depending on where leaders believe the people agenda can create the greatest value.

The future of work is a choice

The future of work is already being built. The opportunity now is to build it intentionally, creating better work for people and greater value for organizations. 

Explore how our 10 predictions from 2025 are tracking, the evidence behind six work shifts for better employee and business outcomes, and four possible futures for how HR can create strategic value in an AI-enabled enterprise. .

Dr. Autumn D. Krauss is chief scientist of the Future of Work Research Lab for 麻豆原创 SuccessFactors.

That’s why we’re proud that 麻豆原创 has been recognized as a Leader in the inaugural Gartner庐 Magic Quadrant™ for Workforce Management Technology.

We believe this recognition reflects 麻豆原创’s commitment to helping organizations connect workforce operations, workforce intelligence, and business outcomes through a unified human capital management (HCM) platform.听

Workforce management in the era of Autonomous HCM听

As organizations prepare for the next era of work, leaders need more than scheduling tools and time systems.听They need a connected understanding of their workforce.听

Who is available? What skills are needed? Where are emerging labor gaps? How can workforce decisions better support business priorities?听

These questions sit at the intersection of workforce management and workforce strategy.听

That’s听why workforce management plays听an important role听in 麻豆原创’s vision for听.听At听its core, Autonomous HCM is about helping organizations move more quickly from workforce insight to action.

Workforce management plays a critical role in that vision by providing the operational data and workforce visibility needed to make more informed decisions. 

By bringing workforce management together with core HR, payroll, talent management, and workforce planning, 麻豆原创 SuccessFactors solutions help organizations gain a more connected view of their workforce, streamline operations, and make more informed workforce decisions. 

Advancing workforce management 

麻豆原创 continues to invest in capabilities that help organizations connect scheduling, absence management, time and attendance, workforce planning, and workforce decision-making. Recent innovations include the general availability of , helping manufacturing and production organizations align labor demand, workforce availability, employee skills, and compliance requirements within a more connected scheduling experience. 

We also recently introduced a new , which helps employees and managers complete common workforce management tasks鈥攍ike automatically pre-filling time sheets, validating entries against compliance requirements in real time, and answering policy questions鈥攃utting employee time sheet completion effort by up to 40% and HR service tickets by up to 20%. 

For professional services organizations, this focus on streamlining time extends further. The new consolidated timesheet experience across 麻豆原创 S/4HANA Cloud Public Edition and 麻豆原创 SuccessFactors Time Tracking helps unify project time and HR attendance in a single flow from resource planning to revenue recognition.  

From frontline workers on the production floor to project professionals, these capabilities reflect 麻豆原创’s commitment to industry-specific depth in workforce management. 

Beyond workforce operations, 麻豆原创 recently introduced new workforce planning capabilities within , helping leaders connect workforce decisions directly to HR, business, and financial priorities through a unified planning foundation.  

In addition, AI-enabled organizational modeling capabilities can support scenario planning and impact analysis, enabling business and HR leaders to evaluate organizational changes and workforce decisions before they are implemented. 

Together, these innovations help organizations connect workforce operations, workforce planning, and workforce decisions in new ways, supporting 麻豆原创’s broader vision for Autonomous HCM. 

Delivering meaningful outcomes 

Organizations across听more than听126听countries and 29听industries are using 麻豆原创 SuccessFactors workforce management solutions to help improve workforce visibility, streamline time and scheduling processes, strengthen compliance, and create better experiences for employees and managers.听

 deployed 麻豆原创 SuccessFactors Time Tracking to comply with new labor regulations requiring detailed workforce scheduling and time management. The organization achieved 99% clock-in and clock-out compliance, reduced neglected clock-outs by 44%, and decreased data-uploading errors by 25%, helping improve workforce visibility, compliance, and operational efficiency.  

 implemented 麻豆原创 SuccessFactors Time Tracking, 麻豆原创 SuccessFactors Employee Central, and payroll solutions to support a global workforce of 10,000 employees. By automating time management, overtime calculations, and payroll processes, the company achieved 40% operational savings, improved compliance, and delivered greater flexibility across HR and workforce operations. 

These examples illustrate how workforce management is becoming a strategic capability that helps organizations connect workforce operations with broader business priorities. 

Looking ahead听

We believe our recognition as a Leader听in听the Gartner庐 Magic Quadrant™ for Workforce Management Technology reflects 麻豆原创’s continued investment in helping organizations build more connected, agile, and resilient workforces鈥攁nd the trust of our customers, partners, and teams whose collaboration and innovation help shape what’s next.听

With many organizations actively reviewing their workforce management technology,听there’s听never been a better time to see what 麻豆原创 can offer.听

Discover why 麻豆原创 is recognized as a Leader in  and learn more about .

Gartner, Magic Quadrant for Workforce Management (WFM) Technology, By听,听,听,听, 14 September 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.

As AI reshapes the way organizations attract, develop, and support talent, leaders need more than systems of record. They need intelligent solutions that help them understand what’s happening across their workforce, anticipate what’s next, and take action with confidence.

We believe this recognition reflects 麻豆原创’s continued investment in AI-powered innovation across 麻豆原创 SuccessFactors solutions and our commitment to helping organizations build a more connected, intelligent, and proactive approach to workforce management.

鈥淎I is rapidly expanding what HCM platforms can do, but buyers need providers that combine innovation with real operational depth and consistent execution,鈥� said David Wilson, CEO and founder of Fosway Group. “麻豆原创 SuccessFactors has accelerated its rollout of AI features across HCM and expanded its integration with AI agents, offering more options to HR leaders. It is a Strategic Leader in the 2026 Fosway 9-Grid™ for Cloud HR, and 麻豆原创鈥檚 Excelling Trajectory in 2026 reflects its increased market performance and customer advocacy as well as continued innovation in both AI and core capabilities.”

Building the foundation for Autonomous HCM

This recognition comes at a pivotal moment for HR.

As AI continues to reshape work, organizations are moving beyond questions of efficiency and automation and focusing on a broader challenge: how to build more agile, adaptable, and resilient workforces.

The next era of HCM will be defined not by automating processes, but also by helping organizations make better decisions. That’s why we introduced our vision for Autonomous HCM earlier this year at 麻豆原创 Sapphire.

As part of 麻豆原创’s broader vision for the Autonomous Enterprise, Autonomous HCM brings together trusted workforce and business data, embedded AI, and HR processes to help organizations connect workforce decisions more closely to business outcomes.

As skills requirements evolve and business priorities shift, leaders need more than workforce data. They need the ability to understand implications, evaluate options, and act quickly.

At its core, Autonomous HCM is about closing the gap between knowing and doing. By bringing together workforce data, business context, and AI, organizations can move from understanding workforce challenges to taking action on them.

Traditionally, organizations have relied on reports, dashboards, and manual processes to identify workforce issues and determine next steps. While these tools provide valuable insights, they often leave leaders to interpret information and coordinate actions across disconnected systems and processes.

Autonomous HCM envisions a different approach. By combining AI, workforce intelligence, and business context, organizations can surface recommendations, automate routine work, and help employees, managers, and HR teams take action directly within the flow of work.

Whether identifying emerging skills gaps, recommending learning opportunities, supporting hiring decisions, streamlining employee support, or helping managers respond to workforce trends, AI can help organizations move more quickly from insight to action and achieve better outcomes.

Turning AI into action

Over the past year, 麻豆原创 has continued to invest in innovations that help organizations connect workforce insights with better decisions and outcomes, including:

• , helping employees, managers, and HR teams get work done more efficiently
• , bringing workforce and business data together to support better decision-making
• , helping streamline HR service delivery and employee support
• The acquisition of SmartRecruiters, extending our connected HCM approach to talent acquisition by linking hiring decisions more closely to workforce planning, skills intelligence, and the broader employee lifecycle

Next month at , we’ll share new innovations and customer stories that demonstrate how organizations are using our solutions to adapt more quickly to change, create more agile workforces, and move toward the vision of Autonomous HCM.

Delivering meaningful outcomes

The journey toward Autonomous HCM is already underway for many organizations.

is using 麻豆原创 SuccessFactors solutions and Joule to transform payroll and employee support experiences. By implementing AI capabilities, such as Explain Pay, the company has reduced payroll processing time by 90%, from five days to four hours, and expects to reduce payroll support costs by 80% while delivering faster, more personalized assistance to employees.

is embracing AI as part of its broader workforce transformation strategy. Through 麻豆原创 SuccessFactors solutions and Joule, the company is using AI to support talent acquisition, skills development, and employee growth while creating a more personalized and accessible employee experience. The company is also advancing its journey toward becoming a skills-based organization, using AI to help connect people with learning and development opportunities.

These examples highlight how organizations are using AI not just to automate work, but to improve decision-making, enhance employee experiences, and create measurable business value. They also demonstrate how the journey toward Autonomous HCM is already taking shape across organizations today.

Looking ahead

AI is creating new opportunities for organizations to rethink how work gets done and how people can thrive.

Our focus remains on helping organizations connect workforce insight with action through trusted data, embedded AI, and end-to-end HR processes. By bringing together workforce and business data in a unified foundation, 麻豆原创 SuccessFactors solutions help organizations build toward Autonomous HCM and create better outcomes for employees and the business.

We are grateful to our customers whose trust, partnership, and innovation make recognitions like this possible.

听and how 麻豆原创 SuccessFactors solutions are helping organizations build the foundation for Autonomous HCM and the future of work.听

About the Fosway 9-Grid™
Fosway Group is Europe鈥檚 #1 HR industry analyst. The Fosway 9-Grid™ is a five-dimensional market analysis model that helps organisations compare solutions based on Performance, Potential, Market Presence, Total Cost of Ownership and Trajectory.
The Fosway 9-Grid™ for Cloud HR provides a unique assessment of the principal Cloud HR options available to organizations in EMEA. The analysis is based on extensive independent research and insights from Fosway鈥檚 Corporate Research Network of over 250 organizations, including BP, HSBC, PwC, Sanofi, Shell, and Vodafone.
Visit the Fosway website at .

Payroll presents a unique paradox. It鈥檚 one of the business functions most suited to AI and automation because it鈥檚 highly structured, data-intensive, and compliance-driven. At the same time, it鈥檚 one of the most trust-sensitive functions in the enterprise because even small errors can have immediate consequences for employees’ financial well-being and confidence in their employer.

Payroll professionals often joke that nobody notices payroll when it goes right, and everyone notices when it goes wrong. Behind that observation is an important reality: every payroll run becomes a moment of trust between employer and employee. That trust has measurable consequences. According to new research* by 麻豆原创鈥檚 , 38% of employees worldwide have experienced a payroll error. These employees are significantly less likely to trust both their organization (13% lower trust) and their payroll function (17% lower trust). Trust declines even further with each additional payroll error experienced.

As National Payroll Week takes place across both the and the , we have an opportunity to recognize the payroll professionals who earn and maintain that trust every day, while reflecting on the transformation taking place across the payroll function itself.

As payroll teams navigate growing complexity, they’re being asked to do more with less while maintaining the accuracy, compliance, and reliability employees depend on. Employees increasingly expect faster, more flexible payroll experiences, including more frequent pay cycles and greater visibility into earnings and deductions, while tax laws, wage rules, leave requirements, and reporting obligations continue to evolve across countries, states, and local jurisdictions. At the same time, today’s workforce is more dynamic than ever, with employees changing roles, locations, schedules, and compensation arrangements in ways that can create downstream payroll impacts. Managing these changes manually is becoming increasingly difficult and raising the risk of errors, delays, and compliance gaps, positioning payroll not simply as an administrative process, but as strategic infrastructure supporting employee experience, compliance, finance, and business operations.

This combination of rising complexity and rising expectations is driving the next evolution of payroll: autonomous payroll.

Scaling trust in an era of complexity

Autonomous payroll is designed to help organizations navigate growing payroll complexity while maintaining accuracy, compliance, and confidence at scale. By combining AI, intelligent automation, integrated data, and real-time payroll monitoring, organizations can move beyond reactive payroll operations and proactively identify issues before they affect employees.

The goal isn’t to remove people from payroll, but to enable them to focus on higher-value activities by reducing manual effort and increasing visibility. Our global research suggests that employees do not see AI and human involvement as mutually exclusive. In fact, nearly half (49%) say they would trust AI in payroll more if they still had access to a human when AI fails. Additionally, 43% of employees say that the ability to request a human review of AI-generated outcomes would increase their trust in the use of AI in payroll. Trust is built not only through accuracy and efficiency, but also through the confidence that employees can escalate concerns, seek clarification, and access human support when needed.

Emerging capabilities such as AI-powered payroll agents and continuous payroll are helping organizations move from processing payroll to actively managing it. These capabilities can assess payroll readiness, detect anomalies, validate changes, and monitor workforce events across HR, payroll, and time data. By identifying how changes in roles, locations, schedules, compensation, or leave may affect payroll outcomes, organizations can anticipate impacts and resolve exceptions before they become costly errors. The result is improved reliability, stronger compliance, and greater trust across the workforce.

The shift is significant. Rather than finding errors at the end of a payroll cycle, organizations can increasingly investigate and resolve them throughout the cycle. But technology alone isn’t enough. As payroll becomes more autonomous, organizations must ensure intelligent systems operate with appropriate oversight, transparency, and accountability.

Automation requires accountability

As AI becomes more embedded in payroll operations, the conversation shifts from adoption to accountability. Trust becomes paramount, raising important questions about where AI can operate autonomously, where human review adds value, and where human accountability must remain visible.

Our global research shows that employee comfort with AI varies by payroll task. Employees are most comfortable with AI supporting calculation-heavy activities such as payroll calculations and anomaly detection, while they prefer human involvement for tasks requiring judgment, investigation, or employee interaction. Final decisions on payroll disputes remain the area where employees most strongly prefer a human. These findings reinforce an important point: the goal is not to replace human expertise, but to apply AI where it adds the most value while preserving human oversight where trust and judgment matter most.

The most successful applications of AI in payroll won’t simply automate tasks. They’ll strengthen trust by improving consistency, reliability, transparency, and the overall payroll experience employees depend on.

In other words, the future of payroll isn’t human or AI. It’s human expertise amplified by AI.

Building the foundation for Autonomous HCM

The implications of autonomous payroll extend well beyond payroll operations.

At 麻豆原创, we believe autonomous payroll is a key enabler of Autonomous HCM. Trusted AI experiences depend on trusted data, connected processes, and embedded intelligence, and payroll plays a critical role in making that vision possible.

Every hiring decision, compensation adjustment, promotion, workforce change, or organizational initiative ultimately affects payroll. As a result, payroll remains one of the most trusted and comprehensive sources of workforce data across the enterprise.

Realizing the full potential of autonomous payroll requires a unified foundation across HR, payroll, and time data. When organizations establish a single source of truth, they can reduce complexity, improve payroll accuracy, strengthen compliance, and enable AI to deliver more meaningful insights and recommendations.

This foundation is essential because AI cannot solve payroll challenges if it鈥檚 simply layered on top of fragmented systems and disconnected processes. Instead, organizations need connected data and integrated workflows that allow intelligence to operate across the entire workforce lifecycle.

When payroll, HR, and time data come together on that foundation, organizations can create more intelligent workforce experiences, make better decisions, and increase organizational agility.

Looking ahead

National Payroll Week is an opportunity to celebrate the professionals who keep one of the most important business functions running every day. It’s also an opportunity to recognize how dramatically that function is evolving.

For decades, payroll was viewed primarily as an administrative necessity. Today, it is increasingly recognized as a strategic capability that influences employee experience, compliance, operational resilience, and organizational trust.

The organizations that lead in the years ahead won’t simply process payroll more efficiently. They’ll create payroll operations that are more intelligent, more connected, and better positioned to support both employees and the business.

As payroll continues its evolution from a transactional function to a strategic business capability, the opportunity is not simply to automate existing processes. It’s to build payroll operations that can scale trust, resilience, and confidence in an increasingly complex world.

Because when payroll works, it does more than deliver pay. It helps build confidence in the organization behind it.

Discover how helps organizations simplify payroll, reduce complexity, and accelerate their journey to autonomous payroll.

*Data from a global survey of 1,576 full-time employees in July 2026.

We believe this recognition reflects our ongoing commitment to helping organizations navigate an increasingly complex world of work through innovation, global scale, and AI that helps connect workforce decisions to business outcomes. 

A new era of HCM 

Organizations today face unprecedented workforce challenges.

Skills requirements are evolving rapidly. Workforces are becoming increasingly distributed. Business priorities shift faster than traditional planning cycles can accommodate. At the same time, leaders are being asked to make workforce decisions with greater speed, precision, and confidence. As these pressures increase, the role of HR and HCM technology is fundamentally changing.

Organizations no longer need systems that simply record workforce data or automate HR processes. They need connected, intelligent systems that can help anticipate workforce needs, surface recommendations, remove friction from everyday work, and help people make better decisions. This is why we announced our vision for Autonomous HCM at 麻豆原创 Sapphire in May.

As part of 麻豆原创’s broader vision for the Autonomous Enterprise, Autonomous HCM brings together trusted workforce and business data, embedded intelligence, AI, and HR processes to help organizations respond more effectively to changing workforce needs. The goal is not simply to automate more tasks. It’s to help organizations understand what’s happening, determine what to do next, and execute with greater speed and confidence. Achieving this requires trusted workforce and business data working together to provide the context needed for better decisions and better outcomes. 

Bringing Autonomous HCM to life

Over the past year, 麻豆原创 has continued to invest in capabilities designed to help organizations move more seamlessly from workforce insight to workforce action. From new Joule and AI agents to and , these capabilities help connect workforce intelligence, decision-making, and execution across HR processes. Our acquisition of SmartRecruiters extends this approach to talent acquisition, helping connect hiring decisions to workforce planning, skills intelligence, and the broader employee lifecycle. Next month at at 麻豆原创 Connect, we’ll share new innovations and customer stories that further demonstrate how 麻豆原创 SuccessFactors can help organizations automate work, adapt more quickly to change, and drive better workforce outcomes, ultimately moving towards Autonomous HCM.

Creating measurable impact

Organizations around the world are already working towards this reality.

has embedded AI capabilities within 麻豆原创 SuccessFactors solutions to support employee development, goal setting, recruiting, and career conversations. By giving employees and managers access to AI-assisted tools and insights, Timken is simplifying HR processes, improving employee development conversations, and enabling more informed workforce decisions.

is demonstrating how AI can help organizations move from workforce insight to workforce action. With 麻豆原创 SuccessFactors solutions, the company has streamlined recruiting processes across more than a dozen industries, reducing recruitment duration by 75% and improving hiring efficiency fourfold. AI-generated job descriptions, competency-based interview questions, and workforce insights are helping create a more efficient, consistent, and skills-based approach to talent management.

These examples demonstrate an important shift. AI is no longer limited to providing information. It’s helping employees, managers, and HR teams make better decisions and take action more quickly and effectively.

Looking ahead

We are grateful to our customers whose continued trust and innovation make this recognition possible.

As we look ahead, our focus remains on helping organizations connect workforce insight with action, enabling leaders to make better decisions, respond more quickly to change, and create better outcomes for employees and the business. about our position in the 2026 Gartner庐 Magic Quadrant™ for HCM Suites for 1,000+ Employee Enterprises.

Gartner, Magic Quadrant for HCM Suites for 1,000+ Employee Enterprises, By , , , , , , 31 August 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. 

As a result,听people听analytics is evolving from a reporting function into a strategic capability. By connecting workforce, skills, talent, and business data, organizations can gain a deeper understanding of their workforce and anticipate future talent needs.听听

This听evolution is helping lay the foundation for听Autonomous HCM,听where connected data and AI-powered intelligence help organizations make more informed workforce decisions.听

People analytics: a cornerstone of Autonomous HCM 

The future of HR isn’t simply about automating processes. It’s about providing leaders with the workforce intelligence needed to align talent strategies with business priorities. Industry research, including the , points to growing demand for solutions that bring together people analytics, workforce planning, performance data, and AI-powered insights. Together, these capabilities can help organizations move from reactive decision-making to a more proactive and strategic approach to workforce management. For HR leaders, that means spending less time gathering and reconciling information and more time focusing on actions that improve workforce performance, organizational agility, and business results. 

Connecting workforce insights to business outcomes 

At 麻豆原创, our vision for Autonomous HCM starts with connecting workforce and business data to create a shared understanding of people, skills, and organizational priorities.听Through听, organizations can bring together workforce, skills, talent, operational, and business data to gain a more complete view of their workforce,听identify听emerging opportunities and risks,听anticipate听future talent needs, and make decisions with greater context.听听

This outcomes-based approach helps organizations answer critical questions like:听What capabilities exist across the workforce today, and where are critical gaps听emerging?听What skills will be needed to support future business goals?听How can talent be aligned more effectively to strategic priorities? Where are emerging workforce and retention risks? What actions can help improve workforce and business performance?听

From workforce intelligence to workforce action 

麻豆原创 is transforming its own approach to people analytics through People Intelligence. By bringing workforce and business information together, leaders can move beyond static reporting and better understand workforce trends, skills needs, and organizational priorities.  

Traditionally, acting on workforce insights has often been a manual and fragmented process. HR teams听identify听an issue, such as a skills gap or retention risk, and then coordinate across recruiting, learning, workforce planning, and business leaders to听determine听and execute the听appropriate response. While analytics can help surface the problem, turning insight into action frequently requires significant time, effort, and cross-functional collaboration.听

The听next evolution is connecting intelligence directly to action.听As AI becomes more deeply embedded in workforce processes, organizations can move beyond听identifying听a workforce challenge to听exploring听potential responses and acting on approved decisions. For example, workforce intelligence could听identify听an emerging skills gap, help leaders evaluate different ways听to address it, and connect those decisions to actions across hiring, learning, internal mobility, or workforce听planning.听

Over听time, AI agents will help accelerate this shift听by connecting workforce intelligence with the actions needed to address it, helping organizations move more seamlessly from insight and decision to听execution.听

The path forward for Autonomous HCM 

People analytics helps organizations understand what is happening. Workforce intelligence helps them decide what to do next. Autonomous HCM helps them act by connecting insights, decisions, and execution. 

The future of workforce management is not just about understanding workforce dynamics, but about helping organizations respond with greater speed, confidence, and precision. By connecting听people听analytics, workforce intelligence, and AI-powered execution, Autonomous HCM enables organizations to move听beyond insight to action, creating a more adaptive, resilient, and business-aligned workforce.听

Learn more 

Explore the  to learn more about the trends shaping the future of workforce intelligence, planning, and decision-making, and why 麻豆原创 was recognized as a Leader. 

This recognition reflects 麻豆原创鈥檚 broader vision for AI-driven, skills-based workforce orchestration, where hiring is no longer a standalone process but part of a continuous, intelligent system connecting people, skills, and business outcomes. With innovations across 麻豆原创 SuccessFactors solutions and the addition of SmartRecruiters to the portfolio in September 2025, 麻豆原创 is enabling organizations to move beyond transactional recruiting toward agentic, autonomous talent strategies that continuously adapt to change.

SmartRecruiters for 麻豆原创 SuccessFactors: AI at the center of hiring

combines a modern, AI鈥憂ative recruiting platform with 麻豆原创鈥檚 core HCM to help create a more connected and intelligent hiring experience at global scale. Hiring becomes part of an integrated flow of workforce decisions鈥攍inked directly to skills, planning, mobility, and long-term business strategy.

With embedded AI across the hiring lifecycle, organizations can:

• Deliver intuitive, consumer鈥慻rade candidate experiences at scale, from first interaction through new hire onboarding.
• Empower recruiters and hiring managers with AI鈥慹nabled insights and automation directly within daily workflows.
• Strengthen hiring decisions by connecting recruiting data to skills, roles, and workforce plans.
• Scale globally with confidence, balancing centralized governance with local market flexibility.

SmartRecruiters鈥� AI hiring companion, Winston, works alongside to help automate repetitive tasks, surface top candidates, and explain recommendations transparently, which allows recruiters to focus on higher鈥憊alue decision鈥憁aking while moving faster and with greater confidence.

New capabilities, including agentic interviewing and real鈥憈ime candidate engagement, are helping organizations accelerate hiring while improving candidate experience at scale. For example, early adopters of AI鈥慸riven screening have seen up to a in time鈥憈o鈥慸ecision, demonstrating how AI can streamline evaluation without sacrificing quality.

At the same time, innovations like agentic CRM are helping organizations activate existing talent pools鈥攕urfacing, ranking, and re鈥慹ngaging candidates automatically鈥攖urning recruiting from a reactive process into a continuous, dynamic pipeline.

From recruiting to Autonomous HCM

SmartRecruiters plays a key role in 麻豆原创鈥檚 broader shift toward Autonomous HCM鈥攚here AI-driven agents can continuously orchestrate workforce decisions across hiring, planning, development, and mobility.

Rather than treating hiring as an isolated function, 麻豆原创 is embedding AI across 麻豆原创 SuccessFactors solutions to create a unified, skills-based system of action. Workforce planning, learning, and talent acquisition are directly connected, enabling organizations to align skills with business and financial priorities in real time.

At , this vision came to life through innovations that increase agility and responsiveness. Intelligent agents can identify skill gaps, recommend hiring or redeployment strategies, and take action鈥攖urning talent management into a dynamic, continuously optimized system.

Within this model, hiring becomes one of several coordinated levers in an adaptive workforce strategy, ensuring every decision is guided by real-time data, skills intelligence, and evolving business needs.

Customer impact: AI鈥慸riven hiring in action

Organizations across industries are already seeing the impact of AI鈥慸riven, connected hiring.

Retailer selected SmartRecruiters to improve the candidate experience and reduce drop-off in a high-volume hiring environment. Today, the company processes 50,000 applications each month, reducing the application processing time from 28 days to just four and cutting time-to-fill from 56 days to just 20鈥攄emonstrating how speed and experience directly improve hiring outcomes.

Global real estate services firm implemented SmartRecruiters to increase visibility into recruitment activity and create a more consistent experience across its EMEA business. As a result, Colliers achieved a direct hiring rate above 80%, reduced agency reliance to roughly 7% of hires, and improved first鈥憏ear retention by 25%, showing how connected hiring can lower costs while strengthening long鈥憈erm talent outcomes.

and discover how AI鈥慸riven, connected hiring can help turn talent acquisition into a true strategic advantage.

About the Fosway 9-Grid™
Fosway Group is Europe鈥檚 #1 HR industry analyst. The Fosway 9-Grid™ provides a unique assessment of the principal talent supply options available to organizations in EMEA. The analysis is based on extensive independent research and insights from Fosway鈥檚 Corporate Research Network of over 250 organizations, including BP, HSBC, PwC, Sanofi, Shell, and Vodafone. Visit the Fosway website at www.fosway.com for more information on Fosway Group鈥檚 research and services.

As one of the听industry鈥檚 most trusted independent听peer review听platforms,听TrustRadius听is known for its rigorous verification process and commitment to unbiased, customer鈥憀ed insights. These听awards are based听on real听user experiences,听making听them听especially meaningful.

This recognition reinforces a clear message: organizations are turning to听麻豆原创 SuccessFactors solutions not just to manage HR but to modernize it. As companies move towards more autonomous, AI-driven ways of working, they need HCM solutions that bring together data, insights, and action.听That鈥檚听exactly what the 麻豆原创 SuccessFactors portfolio can deliver.

Momentum across the portfolio

This year鈥檚听results highlight strong and growing momentum.

麻豆原创 SuccessFactors听increased from听12听Top Rated awards听in 2025听to 19听in 2026, reflecting听deeper customer satisfaction across听the HCM landscape.

Recognized categories include:

• HR Management
• Workforce Analytics
• Talent Management
• Compensation Management
• Workforce Management
• Applicant Tracking
• Talent Intelligence
• Corporate Learning Management
• Payroll
• International Payroll
• Pay Equity
• Recruiting Automation
• Employee Performance Management
• HR Compliance
• HR Service Delivery
• Employee Onboarding
• Succession Planning
• Diversity, Equity, and Inclusion (DEI)

This breadth reflects the strength of 麻豆原创 SuccessFactors solutions as a unified suite鈥攃onnecting people, processes, and data across the workforce. 麻豆原创听SuccessFactors听solutions can provide听the foundation to turn those connections into real-time insight and action.

What听our听customers are听saying

Across听thousands听of听verified听reviews,听customers听consistently听point to one thing: impact.听From operational efficiency to better decision-making and improved employee experiences, 麻豆原创 SuccessFactors solutions are helping organizations move faster and work smarter.

• 鈥淲ith 麻豆原创 SuccessFactors HCM AI, we get helpful, actionable insights to make the best decisions. For instance, the insights we gain help us streamline HR operations, especially when it comes to managing our payroll.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors is our core platform and supports our finance and HR processes. We use every module for recruiting, compensation, and learning. It supports our HR transformation and lays the foundation for our data.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors HCM stands out among other human capital management solutions due to its comprehensive suite of听cloud鈥慴ased听tools, strong global compliance capabilities, and seamless integration with other 麻豆原创 systems.鈥� 鈥斕�

• 鈥淔or enhancing employee experience, AI offers personalized recommendations for their learning and development, which increases their productivity and engagement.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors HCM is considered a 鈥榖est of breed鈥� for a reason. The fact that it does allow for听in鈥慸epth听customization, and its ability to be tailored not only to individual business needs, but also it allows for best practice听follow鈥憉p听while ensuring organizations remain compliant with several legal requirements.鈥� 鈥斕�

• 鈥淲e听leverage听听(ECP)听for our payroll engine and for our payroll calculations.听Having ECP makes everyone’s life easier鈥� the payroll control center will simulate the payroll before you run the actual payroll. That gives you a lot of analytics and KPIs to analyze results or potential issues well in advance.鈥� 鈥斕�

• “In our organization, we mainly use Joule in 麻豆原创 SuccessFactors to automate and complete tasks through natural conversation, which听eliminates听manual steps. [It] plays听a big role in eliminating the constant back and forth and guesswork involved in finding accurate information, as well as completing routine tasks, for example, workforce insights, budget and planning, document retrieval, etc. Additionally, it makes navigating [麻豆原创听SuccessFactors] seamless.鈥� 鈥斕�

Looking听ahead

We鈥檙e听incredibly grateful to the customers that shared their experiences on听TrustRadius听with insights that continue to guide our innovation.

Building on听the听introduction of听Autonomous HCM at 麻豆原创 Sapphire,听our focus is clear: helping HR听move beyond managing听processes to听orchestrating work. By听bringing听together AI, data, and workflows, 麻豆原创 SuccessFactors solutions enable organizations to听operate听with greater speed, clarity, and confidence, so they can not only adapt to change but actively shape what comes next.

Learn more about the impact customers are seeing with听.

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

The conversation has moved beyond what AI can do into how it should be applied, placing HR at the center of decisions that will shape people, culture, and business outcomes for years to come.

While we have often talked about the 鈥渇uture of work,鈥� the simple fact is that future is already here. The question is whether organizations are ready to operate differently.

AI requires a fundamental rethinking of how work gets done, grounded in the data, systems, and processes that run today鈥檚 organizations. And getting it right starts with one clear principle: humans must remain firmly at the center鈥攏ot as operators of process, but as leaders of judgement, strategy, and change.

What Autonomous HCM means for HR leaders

At 麻豆原创, this is the foundation of our vision for the Autonomous Enterprise, announced at in Orlando, where AI assistants can run core HR processes end-to-end, so people are empowered to focus on their most meaningful work while staying firmly in control of outcomes.

brings together agentic AI, HR applications, and real business context鈥攇rounded in deep process expertise and enterprise-grade governance鈥攖o help organizations anticipate workforce needs and respond with greater precision as business priorities change.

With the new HCM innovations announced at 麻豆原创 Sapphire, we are building on the existing breadth and depth of 麻豆原创 SuccessFactors with new AI-native functionality that amplifies how HR can help shape the business and elevate what employees are capable of.

Automate work with Joule Assistants

The first shift is automation; not as task replacement, but as a new way of working. A new generation of , delivered through Joule as 麻豆原创鈥檚 AI engagement layer, bring this to life by orchestrating agents to execute work end-to-end and support decisions in real-time.

These assistants are not just automating tasks; they are guided by employees to reduce manual effort and support a growing range of HR scenarios:

• Payroll becomes proactive, not reactive: The coordinates multiple to prepare payroll runs, identify issues early, and guide administrators to faster resolution, shifting payroll from reactive process to proactive execution. Working alongside the Core HR Assistant and , it helps organizations manage employee data, track time and attendance, and pay employees with greater accuracy and less manual work.
• Talent acquisition flows more seamlessly end-to-end: The helps keep hiring moving from intelligent matching to interview coordination, providing real-time guidance to recruiters and hiring managers. Once a candidate accepts, the takes over to support a smooth transition for new employees. These new Joule Assistants connect talent acquisition processes between and the broader 麻豆原创 SuccessFactors HCM suite.
• HR services become faster and more intuitive: The helps administrators resolve common HR questions instantly, directing employees to the right next step and reducing service center volume while improving the overall employee experience.

Reimagine the workforce with AI-driven planning

As AI becomes part of how work gets done, organizations must rethink workforce planning as a continuous leadership discipline, not a periodic exercise. Today, 62% of C鈥憇uite executives say they are dissatisfied with how well people data connects to business performance, according to , making it harder to turn strategy into action. The new workforce planning capability within 麻豆原创 Enterprise Planning supports a shift toward strategic work redesign, inclusive of both agents and people, by helping leaders link workforce decisions directly to HR, business, and financial needs.

This workforce planning capability connects data from , , and 麻豆原创 SuccessFactors, creating a unified foundation for workforce decision鈥憁aking across employees and contingent labor. Together, this moves workforce planning beyond static models. Leaders gain clear scenario insight and the ability to combine human judgment with AI to align workforce and investment decisions.

At a more granular level, constant change means business and HR leaders are often dealing with organizational changes. The new AI鈥慹nabled organizational modeling for replaces slow, disconnected modeling approaches with an integrated experience that supports scenario planning and impact analysis, enabling leaders to evaluate organizational choices with greater accuracy and alignment. With this approach, leaders can quickly explore alternative organizational structures and understand implications before changes are implemented. Whether adjusting roles, teams, or reporting lines, organizational modeling becomes a practical leadership tool, supporting thoughtful change while maintaining data integrity and minimizing disruption. The result is a clearer, more proactive approach that helps organizations make smarter workforce decisions in a constantly evolving business landscape.

Elevate people through continuous upskilling

When it comes to skills, the rise of generative AI has once again accelerated the pace of change. New jobs are emerging, new skills are required, and processes that have worked for decades are being completely reimagined.  The new Workforce Upskilling Assistant delivers personalized, AI-driven learning directly where work happens, in collaboration tools, mobile, desktop and 麻豆原创 SuccessFactors鈥攈elping organizations keep skills aligned with where the business is headed. By orchestrating multiple Joule Agents, it supports content creation and generation, adaptive micro-learning, and reinforcement, enabling leaders and managers to identify critical skill gaps and accelerate upskilling, particularly in fast-moving areas such as AI.

By delivering learning in the tools and channels employees already use, the Workforce Upskilling Assistant turns workforce and business data into timely, bite鈥憇ized learning moments. Rather than relying on scheduled courses or standalone systems, HR learning teams can quickly convert existing content to deliver learning to the right person at the right time.

A new standard for human-centered Autonomous HCM

麻豆原创鈥檚 Autonomous Enterprise vision sets a new standard for how HR leads in an AI-driven world, one where AI assistants and agents take on the work of coordination, so people can focus on leading and shaping outcomes. As AI becomes embedded into how work runs, HR is uniquely positioned to guide what matters most, moving from coordinating processes to guiding decisions, building resilient teams, strengthening trust, and ensuring the workforce is ready for what鈥檚 ahead.

That is the promise of an Autonomous HCM platform: human expertise elevated by AI, delivering meaningful impact for both people and the business.

Learn more about how 麻豆原创 is delivering Autonomous HCM by catching the replay of the HCM Innovation .

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

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

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

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

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The business AI imperative

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

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

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

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

ERP as the foundation for business AI

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

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

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

麻豆原创 Business AI Platform

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

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

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

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

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

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

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

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

麻豆原创 Autonomous Suite

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

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

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

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

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

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

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

Industry AI: H&M and Sector-Specific Transformation

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

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

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

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

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

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

Closing: The Autonomous Enterprise

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

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

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