“It’s time to show you the Autonomous Enterprise in action underpinned by great customer stories,” SAP CEO Christian Klein told his keynote audience at the start of the event.
Klein reminded the audience that SAP introduced the Autonomous Enterprise at its SAP Sapphire conference in May 2026 as “the beginning of better.” Since then, he said, SAP has worked with hundreds of customers to implement Joule Work as the AI engagement layer for the Autonomous Enterprise.
A new UI for AI
“This month, we are rolling out Joule Work for all customers,” Klein said, describing it as a new UI for AI. He noted that for decades, users had to learn how SAP worked, but with Joule Work, SAP learns how people work. “From now on, the more than 400 million SAP users can talk in their own language to SAP, and Joule Work gets the job done.”
AI is reshaping jobs, skills, and ways of working at an unprecedented pace, pushing organizations to rethink not only their business models, but the workforce they need to support what’s next.
SAP Connect in 2026: Advancing the Autonomous Enterprise
According to research from the SAP SuccessFactors Future of Work Research Lab, 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. 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:
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.
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.
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 SAP’s 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 SAP Connect, SAP announced that it has entered into an agreement for SAP 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 SAP 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 SAP SuccessFactors HCM Suite
While Autonomous HCM is our vision for the future, we have several new innovations spanning the entire SAP 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 SAP 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 SAP Enterprise Planning. It is powered by connected workforce, contingent labor, and financial data from SAP SuccessFactors, SAP Fieldglass, and SAP Cloud ERP, 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, SAP announced two new innovations built natively into SAP 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.
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 SAP 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—and in doing so, leaning into SAP’s strength in connecting data, workflows, and processes across the entire SAP 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 SAP SuccessFactors innovations and how SAP is helping organizations advance their journey toward Autonomous HCM, watch the Success Connect keynote replay.
Siva Sundaresan is general manager and chief product officer for SAP SuccessFactors.
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At SAP Connect, we announced new and enhanced Joule Assistants for SAP Customer Experience, expanded SAP Order Management Services for complex B2B environments, and the general availability of SAP Commerce Cloud, cloud ERP edition.
SAP Connect in 2026: Advancing the Autonomous Enterprise
These announcements build on the Autonomous Customer Experience strategy we introduced at SAP Sapphire. That premise is straightforward: AI must understand customer intent, make context-aware decisions, and execute within business guardrails. Following through on a customer commitment requires AI grounded in real-time, enterprise-wide business data, with a deep understanding of the processes needed to orchestrate work from intent to outcome.
A quote needs accurate pricing and terms. An order depends on inventory, credit, payment, and fulfillment. A service interaction requires information about the customer, the product, and the commitments the company has already made.
Customers generally do not see this operational complexity. They experience whether the company followed through.
Joule Assistants move from providing answers to driving business outcomes
Many AI tools can reason about what should happen next and recommend actions. But executing complex enterprise processes requires more than that.
AI needs to understand the live state of the business, including customer commitments, products, pricing, agreements, orders, payments, policies, and operational constraints. It must then navigate the approvals, exceptions, and cross-application steps required to act. Without that grounding, proposed actions may appear reasonable but can be inappropriate, infeasible, or break down in execution.
This is the direction behind the latest Joule Assistant innovations. New and enhanced Joule Assistants for SAP Customer Experience combine role-specific intelligence with business and process context across marketing, commerce, sales, service, finance, operations, and compensation, helping users move from understanding what should happen to getting the work done.
The innovations apply this approach to moments where fragmented context, manual steps, and handoffs can slow the customer experience.
CampaignAssistant and ContentAssistant help teams move from campaign ideas to execution faster by reducing the effort required to plan, create, refine, and activate marketing campaigns.
ShoppingAssistant makes product discovery easier and more relevant to what the customer is trying to accomplish.
QuotingAssistant brings customer, pricing, and commercial context together so sellers can prepare quotes faster and spend less time assembling information across systems.
ServicePlanningandOperationsAssistant translates service demand into coordinated plans, reducing the manual work required to align people, resources, and customer commitments.
IncentiveCompensationAssistant and Recurring Receivables Assistant bring the same intelligence to critical processes behind the customer experience, helping resolve questions, reduce administrative work, and keep compensation and payment workflows moving.
The goal is not to add another conversational interface. It is to move work forward by bringing together the business context, process knowledge, and controls required to act.
Human judgment remains important where decisions require approval, oversight, or exception handling. Within defined guardrails, AI can assemble context, determine and execute appropriate actions, and escalate when human intervention is needed.
Campaign Assistant brings campaign performance, business context, and recommended actions together to help marketers move from insight to execution.
SAP Order Management Services coordinates execution across ERP landscapes
Order management becomes more difficult when an order crosses ERP systems, legal entities, plants, distribution centers, and business units.
Each transition can introduce different information about pricing, inventory, credit, fulfillment status, or ownership of the next action. Consolidating every ERP system before improving order execution is not always a practical starting point.
SAP is expanding SAPOrderManagementServices to provide highly scalable, resilient, real-time omnichannel order orchestration across SAP S/4HANA and other ERP systems.
Built on a cloud-native, event-driven architecture, SAP Order Management Services coordinates order execution across channels, systems, business units, and third-party partners without requiring organizations to consolidate their ERP landscapes first.
The expanded capabilities provide a common layer for validating orders, checking inventory across locations, coordinating transactions between business units, and monitoring progress through fulfillment.
This gives organizations greater flexibility to add, remove, and experiment across channels, while enabling the order management layer to detect disruptions, trigger exception workflows, and keep execution aligned with the original customer commitment.
In complex enterprise landscapes, this combination of scale, flexibility, and reliable integration helps businesses deliver consistent omnichannel experiences while improving operational efficiency.
SAP Order Management Services helps teams monitor orders, identify disruptions, and manage exceptions across complex fulfillment environments.
Complete business context across the customer journey
Customer intent enters the business long before an order reaches a fulfillment system. It begins when a customer discovers a product, engages with a campaign, requests a quote, or starts a purchase journey.
To deliver on that intent, customer-facing interactions must remain connected to the pricing, inventory, ordering, fulfillment, and financial systems that support them.
SAP Commerce Cloud, cloud ERP edition, is now generally available. First introduced at SAP Sapphire, the edition allows midsize and growing companies to extend SAP Cloud ERP with commerce capabilities that use ERP data for pricing, availability, orders, invoices, and other transactional processes.
For more than a decade, SAP Commerce Cloud has supported some of the world’s largest and most complex digital commerce environments. With SAP Commerce Cloud, cloud ERP edition, we are extending that approach to companies that want a more standardized, SAP-managed path to ERP-connected commerce.
By using SAP Cloud ERP as the system of record, organizations can connect digital commerce with pricing, ordering, fulfillment, and financial processes without building and maintaining those connections independently. The result is a faster path to value, lower operational complexity, and an ERP-aligned commerce model designed to scale as the business grows.
SAP Commerce Cloud, cloud ERP edition, provides ERP-connected commerce with trusted pricing, availability, and ordering.
The same principle applies as customer interactions move across teams. A new native connection between SAP Engagement Cloud, enterprise edition, and SAP Sales Cloud synchronizes contact and company information while bringing relevant engagement signals directly into sales workflows. Instead of reconstructing customer context, sellers can continue conversations with a clearer understanding of prior engagement.
Customer experience depends on execution
AI can understand customer intent, make context-aware decisions, and act within defined guardrails. The harder question is whether the business can carry that action across the systems, teams, and processes responsible for delivery.
The innovations announced at SAP Connect address different parts of that challenge. Joule Assistants bring business and process context into the flow of work and help execute the next step. SAP Order Management Services orchestrates orders across complex ERP landscapes. SAP Commerce Cloud, cloud ERP edition, connects digital commerce directly with ERP pricing, availability, ordering, fulfillment, and financial processes.
Together, they advance a common principle: Autonomous Customer Experience depends on connecting customer-facing intelligence with the operational context and processes required to act.
Customers ultimately do not experience recommendations, models, or workflows. They experience whether the business followed through and delivered.
As AI begins to act on behalf of the business, the quality of that follow-through will depend on the business context, process knowledge, and operational reality behind every action.
Additional information on the SAP Connect announcements, including availability details and product-specific innovations, is available in the SAP Connect Innovation News Guide.
Balaji Balasubramanian is president and chief product officer of SAP CX.
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Our Future of Work Research Lab at SAP SuccessFactors studies how jobs, organizations, leadership, and HR are changing and what those changes could mean for the future of work.
SAP Connect in 2026: Advancing the Autonomous Enterprise
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.
Our latest research 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’s 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 strategic work redesign program 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.
Fromcentralized 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’s 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’s 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. Read the full report.
Dr. Autumn D. Krauss is chief scientist of the Future of Work Research Lab for SAP SuccessFactors.
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Customer choice starts with clarity. With more than four years to go, now is the right time to understand what changes are coming at the end of 2030 and what they mean in practice.
At the close of the optional extended maintenance period, several support arrangements will expire simultaneously, including SAP’s current reselling and support agreements for third-party databases and Java. What we want customers to understand is what the expiring third-party agreements mean for their systems—particularly for systems running on third-party databases or Java. Customers using these technologies should prepare now and plan accordingly.
According to Michael Bloch, member of the Board at the German-speaking SAP User Group (DSAG), “Early information is essential for companies operating SAP landscapes. We appreciate the open communication about the support implications after 2030. This transparency gives customers an important basis for planning. The significance of these developments will differ across organizations depending on their individual circumstances. What matters now is drawing the right conclusions and establishing a clear strategy for the way forward. However, any decision should be based on a comprehensive assessment of all available alternatives and their respective long-term consequences.”
What ends on December 31, 2030
At the close of the optional, extended maintenance at the end of 2030, several support arrangements expire simultaneously. Here are more details of what this means for our customers.
SAP’s current reselling and support agreements with major third-party database providers for these legacy environments
The existing reselling and support arrangements enable SAP and the technology providers to work closely together to build and improve tooling optimized for SAP workload on third-party databases and to support, when an issue evolves at the integration between SAP software and a third-party database or Java. SAP’s current reselling and support arrangements with major third-party database providers are scheduled to end for these legacy environments. With expiration of these arrangements, the foundation for providing these joint services to SAP customers ceases to exist.
Once these agreements expire, SAP will no longer provide database-specific support for third-party databases in these legacy environments, including for customers that originally licensed their third-party database through SAP and enrolled in SAP Maintenance and Support.
For all affected third-party databases, SAP support will no longer cover the database-related corrections available today. What does that mean in practice? Today, when a customer raises a support ticket on a third-party database issue, SAP handles it end-to-end, routing it through integrated internal processes directly to the database vendor’s team. After 2030, that integrated support path will no longer exist.
SAP’s support arrangements for Java
SAP’s current support arrangements for Java (Java 8/JEE5) used with SAP NetWeaver Application Server Java 7.5 (SAP NetWeaver AS JAVA 7.5) are scheduled to conclude at the end of 2030. This is the central constraint: once these arrangements expire, SAP maintenance, including customer-specific maintenance, cannot replace the support and rights they provide. SAP NetWeaver AS JAVA 7.5 with all the add-ons will fall into customer specific maintenance starting 2031 without a follow-on release.
What happens after December 31, 2030
Implications for customer-specific maintenance
After the extended maintenance period expired at the end of December 2030, on-premise SAP Business Suite 7 systems will run under customer-specific maintenance. However, what SAP can deliver under customer-specific maintenance is even further restricted specifically for the third-party database or Java side.
For such systems, SAP will not be able to provide comprehensive support for issues involving third-party databases or Java. This includes kernel patches and kernel security patches for third-party database environments. Also, SAP may no longer be able to provide support and even downloads of database tooling associated with third-party databases. This includes databases, administration tooling, backup tooling, and upgrade and migration tooling for third party databases.
Again, this is a reminder of an important consequence of the expiring agreements with third parties. An issue may occur that cannot be resolved within the support framework available after 2030. That is, as laid out, especially the case for third party DB or Java issues. Customers should therefore not regard customer-specific maintenance for affected environments as a sustainable long-term operating model of business-critical systems.
Implications for conversion
Timing matters for another reason. A system conversion from SAP Business Suite 7 on a third-party database to SAP S/4HANA or SAP Cloud ERP will only be available before the end of reseller/support agreements end of 2030. After that point, only greenfield transition scenarios (new implementations) will be possible.
For SAP solutions that rely on AS Java, SAP provides solution-specific transition recommendations. Detailed product impacts and technical guidance are documented in the relevant SAP Notes.
Recommended paths for our customers
SAP’s strategic recommendation
Customers should use the time available to move toward SAP Cloud ERP and the SAP Autonomous Suite. This is the path to continued innovation and a fully supported, future-ready environment. The right sequence will depend on each organization’s starting point, business priorities, and landscape complexity.
Customers should plan to complete their transformation to SAP Cloud ERP, together with the appropriate go-to solutions in the SAP Autonomous Suite, by the end of 2030. Starting early gives organizations greater control over scope, timing, and risk.
Transition option for SAP ERP
Qualifying customers whose transformation is underway, but that need additional time can consider Transition Option for SAP ERP. This time-bound subscription offering is intended for the largest and most complex SAP Business Suite 7 customers that may not complete their move by the end of extended maintenance. It is designed to support business continuity from 2031 through 2033 while enabling a structured path to SAP Cloud ERP. Systems must be moved to SAP ERP, private edition on SAP HANA before December 31, 2030, and further eligibility requirements apply. The transition option does not support Java-dependent capabilities.
In select cases, switching to SAP HANA database
Customers that intend to continue operating SAP Business Suite 7 on premise can remove the third-party database dependency by moving the relevant system to SAP HANA before the end of 2030. This does not extend mainstream or optional extended maintenance. The system would still enter customer-specific maintenance, with the limitations that this entails, and SAP does not recommend this as the strategic long-term path.
Moving forward together
Our customers do not need to make these decisions alone. We are working with customers, partners, and our user groups to make the implications transparent and support realistic planning.
The maintenance dates announced in 2020 remain in place. On top, after 2030, dependencies on affected third-party databases and SAP NetWeaver Java cannot be comprehensively supported even under customer-specific maintenance. Our customers have defined paths forward, but some choices must be implemented before the end of 2030.
Now is the time to assess affected systems, clarify dependencies, and discuss the best path together with SAP or an SAP partner. Acting early gives organizations the freedom to sequence the work around their business priorities, reduce uncertainty, and protect continuity.
We will continue to communicate transparently and support our customers as they move towards SAP Cloud ERP and the SAP Autonomous Suite.
WALLDORF and GHENT, Belgium — SAP SE (NYSE: SAP) and TechWolf today announced they have entered into an agreement for SAP to acquire TechWolf, provider of a leading AI work intelligence platform.
Automate end-to-end processes, drive context-aware decisions and optimize workforce operations at scale
TechWolf gives enterprises a continuously updated view of the work their people do and the skills they have, using its proprietary data model called context graph for work. The acquisition will bring this context graph, along with TechWolf’s AI models and applied AI research team, into SAP, establishing work intelligence as a strategic SAP asset. The deal is expected to close in Q4 2026, subject to usual closing conditions, including regulatory approval. Terms of the deal were not disclosed.
TechWolf works from existing HR and business systems that customers connect. It builds its model of the organization at three levels: the work itself, down to the tasks inside a job; the skills people have and apply; and the external labor market. It maps that against the customer’s business strategy, so the leaders responsible for hiring, reskilling and redeployment are working from better information.
TechWolf is expected to become an intelligent core of the SAP SuccessFactors portfolio, supporting the company’s talent and work intelligence strategy. TechWolf will power workforce and talent strategies across SAP SuccessFactors, bringing skills mapping, workforce planning and organizational redesign informed by context from across the Autonomous Enterprise. Once the transaction closes, TechWolf and SAP will unify skills and work data to inform HR and business leaders to guide decisions about development, deployment and workforce transformation.
“TechWolf’s proprietary context graph for skills and work provides an excellent grounding layer for agent queries regarding work and skills planning and talent management,” said Manoj Swaminathan, president and chief product officer for SAP Autonomous Suite and member of the Extended Board of SAP SE. “This grounding layer perfectly matches our strategy. It makes token usage more efficient, lowers the cost of deploying workforce agents and will make Joule more intelligent in AI-driven HR scenarios such as skills-based hiring, workforce planning and role redesign.”
Joint SAP and TechWolf customers using the technology are seeing measurable results from the partnership the two companies have had. Building on that foundation, SAP and TechWolf will jointly co-innovate a concrete set of new AI-powered workforce and skills optimization products to be designed and developed post-close. SAP plans to integrate TechWolf’s solutions to a greater degree, offering customers even better insights and work intelligence to help organizations plan reskilling, internal mobility and hiring.
“Organizations everywhere are trying to figure out how AI is reshaping work, and what their workforce needs to look like because of it,” said Andreas De Neve, CEO and co-founder of TechWolf. “We have spent eight years building the evidence layer to answer those questions. It’s always been our mission to connect skills, tasks and work to help employers solve AI transformation, and joining SAP will allow us to extend that mission across a broader set of business context and larger scale. In this next chapter, we plan to build a world-class AI company.”
Subject to closing and required consultation, SAP’s current plans are for TechWolf to remain as an independent entity under CEO Andreas De Neve in its Ghent headquarters, with offices in London, New York and San Francisco, and for its platform to remain available to both SAP and non-SAP customers. J.P. Morgan served as exclusive financial advisor to TechWolf.
TechWolf is a leading applied AI company that helps large enterprises understand how AI is transforming work and what that means for their workforce. Its platform brings together skills, work, and market intelligence, into a single context graph for work; Its open-source models have been downloaded more than two million times. TechWolf co-exists with systems enterprises already use, including SAP SuccessFactors and non-SAP applications, and connects with AI tools and agents. Customers include HSBC, Atlas Copco Group, GSK, Ericsson, AMD, MetLife, PayPal and Booking.com. The company offers EU and US data-residency, standard encryption, access controls and certifications including ISO/IEC 42001 and ISO/IEC 27001 that support EU AI Act governance and security. Learn more at www.techwolf.ai.
About SAP
As a global leader in enterprise applications and business AI, SAP (NYSE: SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.
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Joule Work, Joule Assistants and SAP Business AI Platform help organizations turn business AI into trusted outcomes across every core function.
LAS VEGAS —SAP SE (NYSE: SAP) today showcased the Autonomous Enterprise in action at SAP Connect, demonstrating how Joule Work and Joule Assistants generate value for customers across every line of business.
“This is a breakthrough moment for business AI,” said Christian Klein, CEO of SAP SE. “The Autonomous Enterprise has arrived. With Joule and SAP Autonomous Suite, built on SAP Business AI Platform, we’re helping organizations like Novartis, Morgan Foods, Nestlé and PwC connect intelligence across every function to deliver trusted business outcomes.”
SAP Connect in 2026: Advancing the Autonomous Enterprise
At SAP Connect, these customers shared how the Autonomous Enterprise is already driving measurable value across their businesses:
“We’ve co-developed and recently launched a pilot of SAP’s Joule Sourcing Assistant,” said Christoph Buerki, Head of Procurement, Novartis. “Our vision is for AI agents to handle the manual heavy lifting, enabling sourcing professionals to focus on strategy, supplier engagement and value creation.”
“At Morgan Foods, we’re already putting the pieces in place for agentic adoption, especially through our technical foundation. The biggest shift will be moving from reactive to predictive, where agents can connect demand signals, inventory levels and supplier status faster than ever before,” said Steve Hankins, Chief Financial Officer, Morgan Foods, “Our superpower will come from people on top of agents. Our approximately 1,000 employees are what make our supply chains work—the technology helps make them even better.”
“Our SAP S/4HANA transformation across 140 countries is creating a connected digital core with consistent processes, trusted data and greater visibility across markets and functions. With that foundation, Joule and the Accounts Receivable Assistant can automatically prioritize collections work based on risk and business context, recommend the next best action and help our finance teams respond faster to change,” said Luca Dell’Orletta, Global Head IT Innovation & Enterprise Architecture, Nestlé.
“In professional services, billing can be one of the more error-prone processes, with accuracy playing an important role in the client experience. SAP’s Billing Assistant brings greater intelligence to this critical process, helping identify potential issues earlier so our people can deliver better client outcomes and build stronger relationships,” said Jill Notz, Chief Accounting Officer, Controller, Business Services Leader, PwC. Building on the success of the Billing Assistant, PwC and SAP are extending their collaboration into new areas of joint AI innovation.
SAP’s Autonomous Enterprise Scales Up
Joule Work is beginning its customer rollout as a new AI user interface that lets employees interact with SAP solutions in their own language and complete work across SAP and third-party data. Grounded in business context from SAP Knowledge Graph, which maps more than 7 million data fields, Joule provides information users can rely on. At SAP, Joule Work is already live with 110,000 employees, with the company seeing 20% productivity gains across finance, HR and procurement. A select group of customers also is using Joule Work in their business environments.
“After 28 years as an SAP customer, partnering with SAP on our AI journey and the Joule Work desktop early adopter program has delivered more momentum in just a few months than we saw in all the years before,” said Peter Wied, Director of Complexity Management, Maschinenfabrik Reinhausen. “What once required up to an hour of manual effort across our SAP S/4HANA environment is now accessible in seconds through natural language—fundamentally changing how our teams interact with business data.”
“The dedicated team has been phenomenal. Their proactive communication, focus on accelerating architecture activation, rapid remediation of defects and overall support have enabled us to become Joule ready much sooner than would have been possible had we needed to navigate these challenges on our own,” said Keith Smith, SAP Platform Architect, CONA Services. “The CONA team is excited about the progress made to date and looks forward to exploring and testing Joule’s capabilities in greater depth over the coming months as we continue our adoption journey.”
When a query is not enough, Joule Assistants execute operational work directly within business workflows, using established data, authorizations and audit trails. Customers control the level of autonomy. SAP’s approach is also open: through the Agent2Agent protocol, Joule can connect with third-party AI and agents, bringing governed business context into broader AI workflows.
At SAP Connect, SAP showcased how these capabilities generate outcomes across SAP Autonomous Suite:
In finance, controllers can automate revenue recognition, disclosures and trade compliance, with early deployments of the International Trade Assistant reducing trade classification effort by up to 50%.
In supply chain, planners can turn multi-hour disruptions into one-click resolutions across planning, manufacturing and logistics.
In HR, leaders can determine the best way to close workforce gaps, while employees can make smarter benefits choices tailored to their needs.
In procurement, decision-makers can identify savings opportunities against peer benchmarks and manage the full contingent workforce life cycle.
In customer experience, organizations can turn customer engagement into sales opportunities with AI-powered campaigns, quoting and customer workflows.
Across industries, SAP is collaborating with customers to apply AI to specialized industry processes, helping organizations in manufacturing, retail, commodity trading and asset-intensive industries improve decision-making, automate routine actions and build more resilient operations.
The Platform Powering Business AI You Can Trust
SAP Business AI Platform gives organizations one place to build, contextualize and govern AI across SAP and third-party environments. With Joule Studio, business users and developers can build and extend skills and agents from no-code to pro-code workflows, choosing from more than 70 AI models. SAP Business Data Cloud and SAP Knowledge Graph ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption.
SAP-managed governance helps organizations scale AI with transparency, accountability and control. SAP AI Agent Hub in SAP LeanIX solutions provides a central inventory of enterprise agents, while SAP’s independently ISO/IEC 42001-certified governance architecture supports regulatory requirements, established authorizations and auditable AI operations.
To help organizations adopt AI at scale, SAP’s Business Transformation Management portfolio, including SAP Signavio, SAP LeanIX and SAP WalkMe solutions, provides the toolchain to analyze processes, govern applications and agents, and drive adoption across the enterprise.
SAP Brings Embedded Payments to Cloud ERP
SAP also announced that it is entering the payments market with SAP Pay, powered by Tereina, an SAP company. Embedded directly in SAP Cloud ERP, SAP Pay executes and reconciles payments within the same workflow when an invoice is due, reducing manual file handling and external processing dependencies, while giving customers greater control.
Partners Expand the Reach of Autonomous Business
SAP is extending the Autonomous Enterprise beyond SAP’s own application portfolio through new partnerships that bring specialized intelligence directly into SAP workflows.
A new partnership between SAP and Moody’s Corporation is designed to embed Moody’s supplier risk monitoring data into SAP Ariba Supplier Lifecycle and Performance. This gives procurement teams continuously updated insights into supplier financial health, operational risk and regulatory status at the point of decision. Organizations will be able to move from periodic risk reviews toward continuous monitoring, enabling Joule Agents to flag supplier risk signals and surface alternatives before disruption affects the business.
An expanded partnership with ORO Labs brings procurement orchestration to SAP customers as a solution extension. SAP Ariba Procurement Orchestration by ORO Labs is a purpose-built orchestration layer that connects procurement workflows end to end across heterogeneous enterprise environments, giving business users a seamless experience for intake, actions and visibility.
As a global leader in enterprise applications and business AI, SAP (NYSE: SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.
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SAP has been named a leader in the IDC MarketScape: Worldwide Agentic Marketing for B2C Enterprises 2026 Vendor Assessment (doc #US54113426, September 2026).
Deliver personalized, AI-driven engagement across every channel and touchpoint
We believe this recognition reflects SAP’s commitment to helping enterprises deliver intelligent, personalized customer experiences, enhanced by AI, built on trusted data and connected end-to-end business processes, and grounded in real-life business context. Joule Agents, Joule Assistants, SAP Business Data Cloud, and SAP Engagement Cloud together provide the agentic marketing backbone to advance this vision of the Autonomous Enterprise.
AI is evolving from assisting marketers to executing and acting on their behalf, creating a fundamental opportunity for organizations to completely rethink how they engage customers. Agentic marketing enables AI agents and assistants to understand context, take action, and help brands deliver more relevant personalized experiences.
Trust is the foundation to this shift. As AI takes on greater responsibility, organizations need solutions built with security, compliance, governance, and trusted business data so customers can confidently rely on AI-driven interactions and decisions.
Why agentic marketing matters
Consumers are becoming more comfortable using AI, reshaping their expectations of the brands they love and the organizations they interact with. SAP’s 2026 Global Customer Loyalty Index indicates that 33% of consumers now trust AI assistants to complete purchases on their behalf, while 31% say interactions with AI assistants make them more loyal to a brand. The trend is even more pronounced across younger consumers. Across generations, we see AI playing an influential role in purchasing decisions and long-term customer loyalty. For example, a consumer might ask an AI assistant to reorder a household product, book a trip, or recommend a new product based on past preferences. For those interactions to succeed, customers must trust that the AI is acting on accurate information, protecting their data, and making decisions within appropriate guardrails.
Organizations from manufacturers to fashion brands are seasoned in using generative AI to create content, build audiences, and improve marketing efficiency. Attention is turning to agentic marketing: moving from AI that recommends to AI that acts.
IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of technology and suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each supplier’s position within a given market. The Capabilities score measures supplier product, go-to-market and business execution in the short-term. The Strategy score measures alignment of supplier strategies with customer requirements in a 3-5-year timeframe. Supplier market share is represented by the size of the icons.
Marketing context meets business reality
Most marketing platforms understand customer interactions well: clicks, opens, purchases, and browsing behavior. Those signals matter, but they only tell part of the story. The most valuable signals often live elsewhere across the enterprise in inventory availability, order status, fulfillment performance, product profitability, return behavior, and subscription and replenishment cycles.
Marketing often sees customer behavior, while ERP systems see business reality. The greatest opportunity for AI emerges when those worlds come together. Because SAP sits at the heart of how many of the world’s leading enterprises operate, marketers can access the operational intelligence that lives within the systems running the business, enabling AI to make decisions based not only on what customers are doing, but on what the business can actually deliver. In an age of agentic marketing, that distinction matters.
Why SAP was recognized as a Leader
SAP was recognized for the following strengths by the IDC MarketScape:
With the agentic layer of Joule, marketers get real-time, context-aware personalization without having to reconcile SAP and non-SAP data themselves, since Joule Agents and Joule Assistants draw on a harmonized SAP Business Data Cloud foundation. Teams receive role-based guidance for navigating complex workflows across Autonomous Domains, while everyday tasks such as retrieving information, connecting enterprise data, and completing multi-step processes happen independently, freeing staff from manual execution. In SAP Engagement Cloud, this means personalization and segmentation scale on their own, and the 4Q25 CX release lets customer service issues resolve autonomously, backed by SAP’s enterprise data layer and SAP Knowledge Graph, instead of requiring escalation.
Because Joule Studio is low code, organizations with reasonable levels of in-house development capabilities can build custom agents themselves, without waiting on IT or writing code, while still connecting to Joule, the SAP Customer Experience portfolio, and third-party systems grounded in SAP Knowledge Graph and SAP Business Data Cloud. For sales and marketing teams, this means faster deal cycles and higher conversion: a sales-assistant agent, for example, automatically surfaces buying patterns and product recommendations from purchase history, sparing reps the manual analysis.
Marketers running campaigns across email, digital ads, wallet, conversational, and web can manage them all from a single platform instead of stitching together point solutions. Because the engagement events service connects external data sources into real-time segmentation, campaigns stay relevant as customer behavior shifts. AI-assisted tools such as natural-language product search, AI-generated consumption summaries, and an AI-assisted report builder cut down the manual work of building segments and reporting, enabling marketers to focus on strategy while AI handles recommendations, translation, prediction, and reporting at scale.
AI that drives business results
Organizations around the world are using SAP’s AI-powered customer engagement capabilities to create more connected experiences and drive business results. For example:
Adler Mannheim uses an AI-powered data foundation to boost fan subscriptions by 50% and improve pre-game fan engagement by 80%.
Molton Brown combines AI-enhanced commerce and personalization to create seamless customer experiences that strengthen loyalty while maintaining 100% uptime during peak periods.
Douglas connects AI-driven shopping experiences, such as virtual beauty tools, and personalized product recommendations to deliver engaging and elevated customer experiences.
Advancing toward the Autonomous Enterprise
Being named a Leader in the IDC MarketScape: Worldwide Agentic Marketing for B2C Enterprises 2026 Vendor Assessment is an important milestone for SAP and the evolution of agentic marketing as a category. As organizations move from experimenting with AI to deploying agents that can reason, recommend, and act, we believe this recognition validates SAP’s approach of combining AI, trusted business data, and connected business processes to help customers navigate this next phase of transformation.
The vision of the Autonomous Enterprise is one in which AI-powered agents help organizations connect customer, operational, and business data to make and execute decisions with greater speed, relevance, and scale. In this future, AI doesn’t replace human expertise; it amplifies it. Intelligent assistants and agents can help teams act faster and more effectively, with governance and guardrails that keep people responsible for the strategy, creativity, and judgment that build lasting customer relationships.
Ultimately, the success of agentic AI will depend not only on what it can do, but on how much customers and businesses trust it to act on their behalf.
New York Climate Week has long been known for big announcements, but this year it felt more like a working week: the focus on delivery and implementation, rather than ambition.
With more than 1,500 events across the city running alongside the UN General Assembly, the event was hailed as the biggest Climate Week yet.
Delegates arrived feeling three pressures that had been building all year: an energy price shock, a summer of climate disasters, and a fast-growing argument about the resources artificial intelligence consumes. What came out of the week was a clearer picture of where sustainability now sits in business: inside the numbers that decide whether companies grow, stall, or get stopped.
Sustainability is back, on different terms
For a few years, sustainability seemed to be slipping down the corporate agenda. Last week suggested it is returning, but not in the form it left.
Energy is the clearest example. UN Climate Chief Simon Stiell put the cost of energy shortages linked to the Iran war at more than $100 billion in higher fuel prices for American consumers alone. The UK’s Ed Miliband urged governments to treat climate and nature loss as a matter of national security. Clean power is increasingly an argument for independence and competitiveness.
Physical risk is the second. Iceland’s Prime Minister Kristrún Frostadóttir described resilience as a foundation laid well before the storm arrives. By Thursday, the General Assembly had approved its first declaration on sea-level rise, aimed at replacing fragmented initiatives with sustained, coordinated, and properly funded action. The UN has acknowledged that overshooting 1.5°C is now inevitable. For business, the stakes are large: an MSCI analysis estimates corporate business interruption losses from climate hazards at more than $1.1 trillion a year, most of which never appears as a line on a balance sheet.
But knowing a risk exists is not the same as being able to act on it. A flood forecast only becomes a business decision when someone can put a value on what sits in its path: the asset, the revenue that depends on it, and the cost of protecting it.
That is the gap most companies face. Everyone is reporting climate risk, yet far fewer are deciding with it. That is why SAP and Jupiter Intelligence came together this week, connecting Jupiter’s physical climate risk intelligence with SAP’s enterprise data and reporting foundation. The starting point is disclosure that holds up to scrutiny. The direction of travel is climate risk that informs where companies invest, protect, and build.
The real question about AI is permission
At SAP, we deliver ethical AI through human-centered innovation that augments human capabilities
If one subject dominated the week, it was AI. Views were sharply divided: Stiell warned that AI leaders are “on thin ice” when it comes to their license to operate, while speakers from all across business and academia argued that AI is too important to give up and will ultimately help tackle climate change.
Both sides are responding to something real. But the issue that will decide AI’s path is not capability, which is already abundant, but whether the people who host AI, power it, and work alongside it keep agreeing to it. Every model runs on land, electricity, water, and cooling. Every data center needs a community willing to have it, and every rollout needs a workforce willing to adopt it. Groups weighing a new data center don’t separate the water question from the jobs question, and companies can’t afford to either.
Governments are starting to set expectations. Türkiye’s COP31 presidency launched the Antalya Pledge on AI, with the COP31 President-Designate saying companies are expected to be transparent about their energy use and to power their operations with clean energy. A draft is due before the summit, which will have a dedicated day on technology and AI.
That pressure applies to every company’s climate commitments, SAP’s included. We have run our own offices and data centers on 100% renewable electricity since 2014, we consider environmental impact at the design stage of our AI architecture, and we have started sharing the footprint of our cloud services with customers, with a beta view for selected products now in SAP for Me. While none of that makes the challenge go away, it makes it visible, and measuring a footprint is where accountability starts.
The week also showed the other side of the ledger. Working from connected data, AI can weigh cost, carbon, availability, and regulation in a single decision, which no planning team can do by hand at scale. Instead of checking whether every product is compliant, companies can ask which products are at risk, why, and what design or supplier change would fix it.
“The question for sustainability leaders is no longer how to manage AI’s impact. It’s how to shape where AI investment goes,” said Sophia Mendelsohn, chief sustainability and commercial officer at SAP. “AI can weigh cost, carbon, and risk together, but only if sustainability is in the data it works from. Leave it out, and AI will optimize it away.”
Governance is the other half of the answer. Speed won the first phase of AI adoption. The next phase will go to organizations that can show how an automated decision was reached and who is accountable for it. In 2025, SAP reviewed 860 AI use cases against its AI ethics principles and escalated 44% as high-risk for senior review. Where no ethically acceptable trade-off could be found, the project did not go ahead in its original form.
Implementation runs on systems
The organizers asked delegates to move from ambition to implementation. The main obstacle to that remains disconnected data. When sustainability information sits apart from procurement, manufacturing, and finance, even good AI produces confident wrong answers: recommending a lower-carbon supplier, for instance, that is not approved for the market in question. The organizations making progress treat sustainability data with the same discipline as financial data, with the same quality standards, audit trail, and controls.
Industrial manufacturer HARTING, for example, connected its sustainability data to the systems it already runs, moving product carbon footprint calculations from manual work to AI-assisted mapping across its material portfolio.
Nowhere does that discipline matter more than in the supply chain.
“Every climate target eventually becomes a supply chain decision: what you source, where you make it, how you move it,” Mendelsohn said. “That’s where commitments are won or lost, and that’s where the data has to be.”
The road to Antalya
New York Climate Week was the last major business gathering before COP31 in Antalya in November, and the COP31 presidency used the week to launch a global pledge to raise electricity’s share of final energy consumption to 35% by 2035, and a new pledge on how AI is powered and measured.
Pledges set the direction, but the pace is set by business decisions. Away from the main stages, the conversations with customers last week sounded different from a few years ago. The questions focused on what carbon costs, where supply chains are exposed, and whether the numbers will hold up to an auditor. Those are commercial questions, and they have commercial answers. The tools, the economics, and the business case are largely in place. What remains is connecting them inside the processes where decisions are actually made.
That is truest of all for AI, the technology that dominated last week. It will scale only as far as the energy, data, and trust beneath it allow. In other words, AI’s future runs through sustainability, and the companies that act on that now will set the pace for everyone else.
