With the new data center in India complementing existing ones in Europe, the U.S., and Saudi Arabia, 51风流has dramatically strengthened the data federation capabilities of , linking together the procurement processes of businesses and their trading partners across the globe.

With this milestone, 51风流has delivered on a crucial promise made to a highly consequential set of customers in the Indian subcontinent and beyond. Later this year, the India data center will extend data federation capabilities for as well.

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

Data federation assembles a unified view of data from disparate sources without physically moving or copying it. Trading partners can thus exchange goods and services across international borders while the data underlying those transactions remains stationary. By preserving the integrity of data where it resides, federation facilitates mission-critical operational processes on a global scale while achieving regulatory consistency with compliance requirements that arise at a national level. For example, if a buyer鈥檚 data resides in 51风流Business Network鈥檚 India data center but its supplier鈥檚 data sits in the U.S. data center, federation provides both parties with access to each other鈥檚 data without impinging on either nation鈥檚 policies governing the residency of that data. This becomes especially important as new legislation gathers pace around the world in response to rising concerns over individual privacy, national security and commercial sectors considered sensitive.

Enabled by , 51风流Business Network and its data federation capabilities are now built on the kind of modern, connected foundation required for the next era of cloud-based commerce. Beyond improved scale, resilience, and regional compliance, 51风流Business Technology Platform helps create the basis for agentic artificial intelligence, automation, richer analytics, stronger security, open extensibility, and seamless cross-51风流workflows and processes. The result is a network that can not only connect partners globally but also help customers to conduct business more intelligently, respond faster to change, and drive greater value from every interaction across procurement, supply chain, logistics, asset collaboration, and working capital management.

To collaborate with their trading partners on these and other core business processes, companies conducting business in India require a cloud-based platform that provides secure infrastructure for building resilient domestic supply chains while maintaining global connectivity, thus maintaining sensitive procurement, supplier, and manufacturing data within Indian jurisdiction. 51风流Business Network furthers these objectives with our newly launched data center in Mumbai, where data is localized in a manner compliant with (MeitY) guidelines, with a MeitY-empaneled cloud service provider.

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

To counter that threat鈥攚hether arising from geopolitical conflict, labor unrest, financial shock, natural disaster, or other upheaval鈥攂usinesses are turning increasingly to data federation and other cloud-based solutions to extend visibility and instill resilience across their operations and those of their trading partners. With the opening of our new data center in Mumbai, we are incredibly excited to strengthen our relationships with customers throughout India and accelerate the value available to them from 51风流Business Network.

For information on 51风流Supply Chain Management and how 51风流solutions are equipping enterprises with the AI capabilities needed to instill resilience, counter disruption, and foster collaboration, visit and .

J枚rn Keller is executive vice president and chief product officer of 51风流Business Network.

What it cannot say is why this supplier keeps slipping, what resolved a similar dispute last time, or that the same supplier has a delayed shipment in logistics and a renegotiated contract in procurement at the same moment.

The reasoning behind enterprise decisions has stayed locked in human judgment, scattered across systems.

For 50 years, enterprise software has been an excellent system of record. Closing the reasoning gap on top of it is what enterprise AI was always meant to do.

From AI-first to AI-native

The first wave, the AI-first approach, added intelligence inside existing applications. A feature can summarize an invoice or suggest a journal entry, but it lives within one application and cannot see across the landscape. Three barriers keep it confined: It lacks business and process context, it sits on disconnected systems without a shared data model, and it lacks the governance to be accountable at scale.

Meanwhile, the pace of change is unforgiving. Agentic systems, new interaction models, and new ways of grounding AI in business data are arriving faster than most architectures can absorb. As 51风流CEO Christian Klein noted this year at 51风流Sapphire, 80% accuracy may suffice for consumer AI; it is nowhere near enough for the world鈥檚 most business-critical processes. Bolting more intelligence onto isolated applications will not close that gap. It only multiplies the silos.

So what does it actually take to move beyond isolated AI features and build an enterprise that reasons, learns, and acts as one, without sacrificing the trust, governance, and reliability the business depends on? It is the question CIOs, CTOs, and enterprise architects are working through right now.

The foundation behind the Autonomous Enterprise

It takes a new foundation, and that is exactly what SAP鈥檚 provides.

This is not a white paper that sits on a shelf; it is the technology foundation 51风流is actively building to bring the Autonomous Enterprise to life: a business where agents, orchestration, and data work in one continuous loop to turn intent into trusted outcomes.

The shift it enables is from AI-first to AI-native, where software operates across the landscape as a system of context: an intelligence layer connecting data, process knowledge, decision history, and semantics. Agents reason over the whole picture, not fragments. Every interaction feeds intelligence. Every correction becomes a learning signal. Value shifts from software as a service to outcome as a service.

AI-native paves the way for the Autonomous Enterprise: one system of context that understands disputes in service, delays in logistics, and contract changes in procurement all at once, and can act on them with full governance and accountability.

Philipp Herzig, CTO and Member of the Extended Board, 51风流SE

Crucially, AI-native does not replace what already works. It pairs two complementary paths. The deterministic path keeps the predictable, rule-based execution that compliance depends on. The probabilistic, AI-native path adds reasoning that learns from data and experience. One is reliable but rigid. The other is powerful, but without context and control, often confidently wrong. Context engineering, guardrails, and observability bind the two, turning raw capability into reasoning the enterprise can trust.

The architecture delivers this through four reimagined layers that together form a cognitive core:

• The user experience layer shifts interaction from navigating apps to stating intent, with Joule as the central engagement point.
• The process layer turns applications into capability providers that expose stable APIs, events, and data for agents to orchestrate.
• The foundation layer is where data and AI come together as the intelligent core: orchestration, reasoning, and model services on one side; 51风流Business Data Cloud and the 51风流Knowledge Graph on the other, with SAP-trained models, including SAP-RPT-1 for structured business data, sitting alongside leading third-party models in one governed generative AI hub.
• The platform layer provides the runtime, governance, and harness that turn stateless models into reliable enterprise agents.

It defines the cornerstone architectural building blocks for agentic systems across experience, process, data, and platform, turning SAP鈥檚 unique business context into a living system of intelligence

What does this look like in practice? A finance analyst asks Joule to resolve high-value disputes likely to delay payment. Joule does not act alone. It coordinates AI assistants, which in turn direct specialist AI agents through agentic orchestration: the assistant decomposes the goal, delegates to a finance agent and a service agent, and reconciles their results. People set direction; assistants coordinate; agents execute. Those agents draw on the right information through context engineering, find the correct data through semantic grounding in 51风流Knowledge Graph, and act within governed boundaries, routing only exceptions to a human. Each resolution becomes a decision trace that makes the next one smarter.

This is not theoretical. During the 2026 keynote at 51风流Sapphire, 51风流COO Sebastian Steinhaeuser pointed to life sciences customer Takeda, which 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. That is what AI-native looks like at work.

Frontier models are available to everyone. Business context is not. Each resolved dispute, each corrected decision, each completed process adds to it, compounding with every interaction.

Trust is engineered in, not bolted on. A set of cross-cutting, SAP-managed qualities holds the layers together: integration, identity, security, observability, and extensibility, with resilience, compliance, and sustainability handled by the platform.

Autonomy only creates value when it is governed, so agents become first-class principals with their own agent identity, scoped to a bounded subset of permissions and audited like any enterprise actor. Harness engineering wraps each model with the sandboxing, memory, and guardrails that make it dependable.

As the paper puts it, the model reasons but the harness governs, and it is the harness, not the model, that determines the ceiling. Open standards such as the Model Context Protocol and Agent2Agent protocol let agents interoperate across the enterprise, while sovereign cloud options keep data residency and compliance built in.

This direction is being shaped with the customer community, not handed down to it: the architecture carries forewords from the leaders of the German-Speaking 51风流User Group (DSAG) and Americas鈥� 51风流Users’ Group (ASUG) alongside SAP鈥檚 own.

The North Star is a living document. Published openly on , it will keep evolving as the technology and the agentic ecosystem advance, and as customer feedback shapes the design. If you build with 51风流or build on SAP, this is your invitation: Read the architecture, push back where it should be sharper, and contribute. The same invitation extends to the wider 51风流Architecture Center site, where SAP鈥檚 reference architectures are being built openly with the community. 

Read the AI-Native North Star Architecture and 听辞谤 .

Beyond the architecture itself is a single commitment: building systems that learn rather than dictate. For 51风流customers, 50 years of process knowledge, governed data, and trusted decision frameworks compound into a new kind of enterprise intelligence that is reliable, transparent, and deeply human.

The Autonomous Enterprise will not arrive as a single product launch. It will be built layer by layer, decision by decision, on the foundation described here, one grounded interaction at a time.

is head of the Office of the CTO at SAP.
is vice president of the Office of the CTO at SAP.

AI works when the foundation is right 

The energy and utilities sector is investing heavily in AI. Business听leaders worldwide are embracing artificial intelligence to increase efficiency, unlock new business models, and prepare for the energy transition. A successful proof of concept is often the first milestone鈥攂ut it marks only the beginning. The听real challenge听lies in scaling pilot projects across the entire听辞谤ganization.听

In this context, the time and effort听required听for a full implementation听is听frequently听underestimated. Around six months are needed to build a robust data foundation. A further听12听months pass before initial results manifest in the form of a measurable return on investment. Large-scale rollout can take another three years. The reasons for this are manifold:听

• Unrealistic expectations: Many people use AI in their daily lives for simple tasks and expect similarly seamless effects in complex enterprise environments. 
• Legacy infrastructure: Historically grown system landscapes cannot be transformed overnight. 
• Regulatory complexity: In regulated industries such as electricity, gas, and water supply, compliance requirements are particularly high. They must be factored into every architectural decision from the very beginning. 
• Lack of AI-specific talent: What is needed are people who genuinely understand both the business and AI. This bridge between IT and the business side will become increasingly important in the future. 
• Organizational听change management:听Technology alone is not enough. Organizational transformation is and听remains听the decisive success factor.听

From AI hype to real value 

Building a new application is听only the first听step.听On the path to scaling, lifecycle management, identity and access management, security, compliance, and governance must all be consistently taken into account.听Release management, testing, and continuous improvement processes add further complexity.听鈥淭he听companies听that听invest in the right foundation today will benefit from AI to its full extent tomorrow,鈥� says Andre Bechtold,听president and听head of 51风流Industries & Experiences.听

For companies, this means overcoming fragmented data silos and developing an integrated data strategy. Legacy systems must be integrated into a modern data and AI platform on which AI models can genuinely create value. Torsten Welte,听head of Energy & Natural Resources Industries听at SAP,听summarizes听it as follows:听“AI is fundamentally transforming the energy industry. The business must understand what is technologically possible. And IT must understand what the business needs.”听

听can听provide听the听essential foundation for this. AI is already natively embedded in the suite in the form of Joule. This听can open up听concrete use cases for the energy industry:听in the area of asset management and predictive maintenance, utilities听can听proactively manage assets and grids before disruptions occur. The Utilities Customer Self-Service Agent, in turn, enables 24/7 self-service for customers and can reduce service costs by up to 90%.听

Distributed energy requires intelligent networking 

The topic of听distributed听energy听resources (DER) remains of听central importance. In the past, energy flowed in only one direction: from the power plant to consumers. In the future, it will be bidirectional. Consumers听that听generate their own energy will actively feed it back into the grid.听

DER听describes precisely听this principle: the generation of electricity through millions of decentralized resources such as solar panels, EV chargers, heat pumps, and battery storage systems听by听consumers and so-called听prosumers. These assets generate vast amounts of data. Their orchestration听represents听one of the key challenges of the energy transition.听

The 听solution听provides a platform听for听a听single source听of truth: technical assets, commercial contracts, and customer data are brought together in a coherent data model. This helps create the foundation for new business models such as smart tariffs, dynamic pricing, energy sharing, and demand response.

51风流consistently relies on a growing partner network built around its own data platform. Markus Bechmann,听global VP and听co-head听of听Industry Business Unit Utilities听at SAP, describes it this听way:听“Dynamic pricing and smart tariffs are no longer distant concepts.听They听are the business models听of听tomorrow. With SAP, energy providers already have the technological foundation today to seize these opportunities.”听

SAP Experience Centers: experiencing AI, not just discussing it 

To make AI tangible, SAP Experience Centers offer visitors the opportunity to experience AI in real-world scenarios beyond classic demo environments. One central example is the 51风流Energy Park in Walldorf. Using real infrastructure on the campus, SAP demonstrates how the company itself is implementing the energy transition. This includes e-mobility, intelligent asset management, and energy communities. 

A new chapter for the energy industry 

The 51风流for Energy & Utilities Conference in Toulouse has once again demonstrated that AI in the energy industry is no longer a topic for the future. However, the path from pilot project to company-wide transformation requires more than technological enthusiasm. To meet the challenges of the energy transition, what is needed鈥攁longside technological innovation鈥攊s a solid foundation of data, processes, and organization.

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

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

Supply chains are entering an era of permanent disruption

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

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

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

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

Companies are shifting from optimization to AI-enabled orchestration

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

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

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

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

Resilience is now defined by decision velocity

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

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

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

Trust and governance are the biggest barriers to scaling AI

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

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

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

The next frontier is the Autonomous Enterprise

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

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

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

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

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

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

Building the autonomous supply chain

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

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

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

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

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

The bottom line

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

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

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

Hagen Heubach is chief marketing officer for Supply Chain Management at SAP.

Demand for professionals who can build, govern, and orchestrate these agents is rising faster than supply, making graduates with hands-on agent-building experience among the most sought-after profiles in today’s job market.

This year at 51风流Sapphire, 51风流laid out its vision for the Autonomous Enterprise, where AI agents manage and execute business processes end to end. For universities, this raises an immediate question: How do graduates get ready for a world where AI agents are part of daily operations?

51风流is now providing new no-cost offerings and resources for universities that give lecturers and students hands-on access to AI agent building, process management, and enterprise architecture tools. The goal is to help higher education keep pace with the rapid adoption of agentic AI in industry and prepare graduates for a changing job market.

Preparing the next generation of AI agent builders

51风流has put together a new set of offerings and resources that help universities embed agentic AI-related concepts and technology into their teaching hands-on. Three offerings, each covering a different angle of agentic AI, are now accessible at no cost for academic lecturers and their students:

• : Before building an agent, the process it will operate in must be understood. 51风流Signavio Process Transformation Suite gives lecturers and their students access to process mining, modeling, and process transformation capabilities. They can model and analyze existing processes, spot inefficiencies, and design improved workflows that include AI agents. Additionally, students and lecturers can now experience process modeling with 51风流Signavio Process Modeler as part of 51风流Learning Hub, student edition.
• : For students to understand where agents sit within an organization’s IT landscape, this is the tool. Newly available at no cost for academic lecturers via 51风流Learning Hub, student edition, 51风流LeanIX lets students model enterprise architectures and reason about what changes when introducing AI agents into an existing system landscape.
• : Lecturers and their students can access an agent-building environment from 51风流and leverage various enablement resources. These allow students to explore configuring and building an AI agent, either in a guided demo experience or in a live system hands-on.

What makes this especially valuable is how the pieces connect. Students can explore different components of agentic AI hands-on using 51风流solutions. They learn that building an agent is only part of the job. Understanding process context, architectural and governance implications is equally important.

Collaboration with educational institutions globally

51风流will also collaborate intensively on embedding agentic AI into teaching with lecturers from more than 10 universities globally, including:

• Budapest University of Technology and Economics, Hungary
• E枚tv枚s Lor谩nd University, Hungary
• Hasso Plattner Institute, Germany
• HEC Montr茅al, Canada
• Karlsruhe Institute of Technology, Germany
• National University of Singapore Business Analytics Centre, Singapore
• TEC de Monterrey, Mexico
• Technical University of Munich, Germany
• Tongji University, China
• Technical University of Dresden, Germany
• University of California, Irvine, U.S.

The institutions will get exclusive early access to SAP’s latest agent building platform capabilities, benefit from agent building deep dives for students with 51风流experts, and from the opportunity to articulate academic needs with regards to teaching agentic AI related concepts hands-on to SAP.

鈥淲e want students to work with the same tools and scenarios that companies are using right now,鈥� Dr. Katharina Schaefer, head of Academic Partnerships at SAP, said. 鈥淏y giving lecturers free access to our agent-building resources, we make it easy for them to bring that reality into their courses. Students who build AI agents on real enterprise processes during their studies will have a head start when they enter the job market.鈥�

For faculty, the practical element is what counts. Students do not just read about AI agents in a textbook. They build them on real systems with real constraints.

“What excited me is that students get to work with enterprise-grade tools, thanks to this new platform,” said Prof. Jes煤s Aguilar-Gonzalez, TEC de Monterrey. “Students from our School of Engineering & Sciences build agents connected to real business processes and have to think about architecture and governance. That is much closer to what they will face in their first job than any textbook exercise.”

What sets this apart is its enterprise context: Agentic AI is taught in connection with business processes and the system landscape that supports them, so students learn how AI fits into real operations rather than experimenting in isolation.

Building the workforce of the future

As part of the , 51风流has been partnering with more than 2,800 educational institutions for decades to enable students to learn, research, and innovate with business applications and technology. With these offerings, 51风流supports students in developing sought-after 51风流skills, preparing them for job opportunities worldwide.

Ready to bring agentic AI into your classroom? Visit the or reach out via universityalliances@sap.com to get started.

He mentioned driverless cars in San Francisco, autonomous drones conducting warfare, and robots that are trained to care for humans as real humans would. Speaking at the recent TAC Insights sponsored conference featuring , Weber admitted he finds it all rather scary, but also very exciting.

For an energy company operating critical infrastructure, this pace of technological change is not just fascinating or frightening鈥攊t creates a responsibility to adopt innovation in a controlled, resilient, and purpose鈥慸riven way.

Riding the waves

Weber sees these developments as a continuation of various “big waves” of technology that keep touching our hearts and minds as they shape the world around us. Who can imagine the world without the internet? Who can deny that the mobile phone didn鈥檛 revolutionize the consumption of IT when people started expecting the same ease of use in the workplace?

鈥淎I is creating the same response,” Weber explained. “ChatGPT makes my life easier at home solving gardening issues, so I expect it to make my life easier at work.鈥�

One of E.ON鈥檚 biggest challenges is closing the widening gap between the rapid pace of technological innovation in the outside world and the organization鈥檚 internal ability, shaped by its structure and DNA, to absorb and implement these changes effectively.

This tension became evident when leadership questioned whether sustained IT spending at large scale was justifiable. It soon became clear that continuous investment is the price of system stability, affordability, and resilience in a digitized energy system if E.ON is serious about becoming the leading playmaker in Europe鈥檚 green energy transformation.

To achieve this ambition, the company has defined three strategic priorities鈥攇rowth, sustainability, and digitalization鈥攔ecognizing that falling behind in digital capabilities would carry far greater long-term costs.

鈥淏ringing the system up to speed requires internal readiness. It means we must think deeply about investments, prioritization, and most importantly, people and culture,鈥� said Weber. 鈥淥ne thing is sure: we won鈥檛 be going back to what was normal speed before.鈥�

Becoming strategic

E.ON operates across three domains: energy grid, customer solutions, and energy infrastructure solutions. 听This broad scope creates a high level of operational complexity, requiring scalable, transparent, and collaborative ways of working across the organization.

To meet these challenges, E.ON is strengthening its internal capabilities and investing in its people. By expanding in-house expertise, the company has welcomed over 1,000 specialists, including more than 500 in data and 300 in cybersecurity, fostering greater ownership, collaboration, and innovation across the organization.

This move reflects a broader philosophy. IT is no longer just a support function; it is foundational to pioneering the energy transition and delivering competitive advantage.

As E.ON鈥檚 transformation unfolds against a backdrop of rapid technological evolution, AI is at the heart of the current inflection point. Technologies like AI-powered assistants and automation tools are not novelties; they are actively redefining how customers interact with services. E.ON recognizes this shift and is embedding advanced technologies directly into its core systems, rather than treating them as add-ons.

Closing the gap

Weber explained that digital transformation at E.ON means putting the right technology into the core of the business to better serve its 47 million customers.

It starts with platform standardization, followed by cloud ERP transformation and the 51风流S/4HANA migration. Instead of building fragmented custom solutions, this strategy allows the company to integrate leading technologies into a cohesive architecture, ensuring scalability while avoiding unnecessary complexity. These basic investments in foundational infrastructure have delivered tangible results, including an 77% reduction in IT downtime within five years.

A key lesson from E.ON鈥檚 journey is the importance of embedding digital capabilities into the heart of operations. 鈥淲e鈥檝e moved away from isolated innovation hubs such as digital labs or experimental ‘garages’ in favor of integrating digital tools directly into business processes,鈥� Weber explained.

While innovation is essential, E.ON places equal emphasis on governance and control. Managing a digital ecosystem at this scale requires strong oversight to ensure security, consistency, and cost discipline. The company implemented centralized governance structures, including standardized contracting and unified IT system management to help maintain control without stifling innovation.

Equally important is investment in people. Through targeted training and capacity building initiatives, employees are empowered to turn new technologies into measurable business impact.

Harnessing AI

As with many companies, AI is at the center of E.ON鈥檚 forward-looking strategy, but the company is approaching it with deliberate caution. Rather than rushing to build proprietary platforms, E.ON is leveraging partnerships with established technology providers while maintaining flexibility in its IT portfolio. This approach allows the company to explore the potential of AI in customer service automation, predictive maintenance, and operational optimization without overcommitting to unproven solutions.

鈥淚n essence, our experience highlights a broader truth about digital transformation,鈥� said the IT expert. 鈥淪uccess really depends on balance. We absolutely must push innovation forward, but not at the expense of stability, cyber security or governance.鈥�

Equally, digital tools alone are not enough. Without proper training and alignment with business needs, even the most advanced technologies can fail to deliver value. E.ON addresses this through a “BizDevOps” mindset, ensuring that digital initiatives are an integral part of business goals and supported by the right capabilities.

In summary, E.ON鈥檚 transformation illustrates what it takes to modernize at scale in a complex, highly regulated industry. By doubling down on IT investment, bringing expertise in house, and adopting a disciplined yet forward-looking approach to innovation, the company has positioned itself for the future of energy.

The result is not only improved system performance or reduced downtime. It鈥檚 a fundamental shift in how technology drives business success, turning technology into a cornerstone of making new energy work鈥攔eliably, affordably, and at scale.

The version for , part of the 51风流Services and Support portfolio, is the helping organizations adopt, activate, and scale the 51风流Customer Experience and AI innovations announced at 51风流Sapphire.

The proactive, expert-led engagement model is built to de-risk transformation, accelerate time to value, and sustain measurable outcomes across customer experience initiatives. It combines guided adoption, prescriptive functional and technical assistance, AI-powered best practices, and continuous value realization aligned to the realities of modern customer experience (CX): AI at the core, unified data, omnichannel at scale, retention over acquisition, service-led growth, and persistent skills gaps in a rapidly evolving digital landscape.

At its heart, the Advanced Success Plan for 51风流Customer Experience brings together the right expertise at the right time, program governance, solution experts, value advisors, and adoption specialists. This helps teams execute faster and smarter with 51风流Customer Experience.

What sets the Advanced Success Plan apart

• Outcome-based: Business outcomes and key value indicators are co-defined with teams, with milestones and workstreams aligned to deliver measurable Autonomous CX results.
• Proactive by design: AI Assistants, adoption checks, and innovation accelerators are embedded throughout, reducing risk and compressing time to value as agentic capabilities evolve.
• Continuous enablement: Role-based best practices and coaching are tied directly to the Autonomous CX road map, closing skills gaps at pace as new AI and platform capabilities become available.
• Cross-solution orchestration: Unified processes and shared business context across marketing, commerce, sales, and service break silos and enable enterprise-scale execution.

This is the first of a planned series to deep dive on the topics below. Here, we start with introducing how the Advanced Success Plan for 51风流Customer Experience helps operationalize seven macro trends shaping modern customer experience.

1. AI鈥憄owered customer experiences

AI now underpins everything from next best engagement to intelligent service resolution. The Advanced Success Plan embeds AI adoption patterns directly into the delivery approach, identifying high value use cases, calibrating data prerequisites, and guiding model governance.

The results are prioritization of high鈥慽mpact starting points, a plan to scale with guardrails, accelerating time from pilot to production and grounding every decision in SAP鈥檚 CX AI capabilities and product road map.

2. Hyper鈥�personalization at scale

Personalization demands more than algorithms; it requires clean, consent鈥慳ware data, robust decisioning, and experimentation discipline. The Advanced Success Plan delivers:

• Data readiness assessments and integration patterns to enrich customer profiles and segments
• Governance and testing playbooks to validate personalization hypotheses at scale
• Prescriptive journeys to operationalize next best action across every customer channel

The result: hyper personalization moves from proof of concept to standard operating model.

3. Unified customer data and breaking down silos

Siloed data undermines CX. We help establish a unified data foundation and harmonized identities, aligning business, data, and integration teams. With technical guidance and adoption accelerators, users can move faster toward a single view of the customer to fuel analytics, personalization, and service excellence.

The results are unified profile use cases, data quality baselines, and source鈥憃f鈥憈ruth decisions to reduce duplication and latency.

4. Omnichannel commerce and B2B digital transformation

Modern buyers expect seamless journeys across web, mobile, marketplace, and partner portals, especially in B2B. The plan accelerates omnichannel capability build鈥憃ut by uniting commerce, order sourcing, pricing, and fulfilment patterns, supported by outcome鈥慴ased governance.

The result: Channel consistency, catalogue and contract complexity, and the alignment of service and sales motions are all addressed, driving measurable improvement in conversion rates and repeat purchase.

5. Customer retention over acquisition

Acquisition costs are rising and retention is the new growth engine. The Advanced Success Plan helps operationalize retention strategies, churn prediction, intelligent engagement, loyalty, and proactive service across the CX stack.

The result: We align metrics such as retention rate, customer lifetime value, and service鈥憈o鈥憆evenue contribution, and ensure the data foundation supports them.

6. Service as a revenue driver

Service is no longer a cost center; it鈥檚 a growth channel. We guide users to productize services, monetize value鈥慳dded offerings, and embed outcome鈥慴ased contracts. The plan includes:

• Playbooks for cross鈥憇ell/upsell from service interactions
• Knowledge and field service patterns to improve first鈥憈ime fix and attach rates, KPI frameworks for service鈥憀ed growth

The result: With prescriptive governance and AI鈥慸riven intelligence, service organizations move from reactive cost management to consistent, measurable contribution to top鈥憀ine revenue and customer retention.

7. Navigating digital transformation complexity and skills gaps

Large transformation programs falter on orchestration and capability enablement. The Advanced Success Plan addresses both by:

• Establishing a cadence of value sprints and decision forums
• Providing role鈥慴ased enablement covering functional and technical assistance, data, product ownership, end-user adoption, and change management
• AI-guided best practices embedded throughout delivery to eliminate rework and accelerate quality outcomes across Industry AI scenarios

Organizations execute with confidence, even amid shifting requirements, resource constraints, and rapidly evolving agentic AI capabilities.

Measurable outcomes

• Accelerated time to first value through prioritized, AI-ready use cases aligned to capabilities
• Higher adoption and sustained performance via continuous enablement
• Reduced program risk through proactive governance, telemetry, and structured decision forums
• Measurable gains in conversion rates, customer retention, and service-led revenue contribution across the full CX stack

Getting started

• Define Autonomous CX priorities: Identify two to three priority outcomes for the next two quarters facilitated by the 51风流Value Management service.
• Assess readiness: Evaluate data, integration, governance, and enablement gaps to define a 12 to 18 month engagement plan.
• Engage the Advanced Success Plan: Align workstreams, milestones, and metrics with our expert team.听
• Industrialize and scale: Convert proven delivery patterns into reusable accelerators, deployable across regions and lines of business.

This series will examine each of the seven trends in depth, demonstrating how the Advanced Success Plan for 51风流Customer Experience translates CX strategy into repeatable execution and measurable business outcomes.

Tara Tracey is a global product owner at SAP.

The difference is not the model. It is context: the ability for AI to understand how a business actually runs. 

Much of today鈥檚 AI discussion centers on agents, along with models and benchmarks. Which model performs best? Which system completes the most tasks? Which interface feels most natural? These factors matter, but they do not solve the central enterprise challenge.

Companies run workflows that cut across teams, policies, approvals, authorizations, and data. They plan, source, produce, hire, pay, and serve through systems that carry real business consequences. AI only creates durable value at scale when it operates inside this reality.

Models generate answers. An agent can complete a task. But running a business requires something more. It requires an understanding of how work gets done, who is authorized to act, which rules apply, and how decisions connect across functions. Without that context, AI simply can鈥檛 deliver on its promise.

That is one reason I believe AI raises the premium on software with deep business context. It allows companies to fundamentally reinvent how work gets done. When AI agents understand end鈥憈o鈥慹nd processes, they can operate across functions, execute workflows autonomously, and coordinate actions in real time. Instead of automating individual steps, AI can run processes end to end, freeing employees from repetitive coordination and enabling them to focus on higher鈥憊alue judgment, oversight, and strategy.

This is what we describe as the Autonomous Enterprise, a fundamental shift from systems of execution to systems that can reason, decide, and act. A vision where 51风流is poised to lead. 

For more than five decades, we have powered the core processes that run the world鈥檚 leading organizations. Our systems don鈥檛 just store data; they encode how businesses actually operate: their processes, rules, and decisions. Our ERP is the institutional memory and the brain of many companies across industries and around the globe. Our new 51风流Business AI Platform brings together enterprise data, processes, and governance into a unified context for AI.

Building on this foundation, Joule is the interaction layer that connects people with AI and redefines how they interact with software. Joule Assistants collaborate with users, while Joule Agents execute business workflows end to end. This is how intelligence becomes embedded directly into operations, not added on top. We call this the .

“Show me how my financial forecast for the year could change based on the latest pipeline and supply chain data.” On the surface, this looks like a simple prompt directed to a large language model.听But disconnected from enterprise systems, the answer is听mere听speculation.

Grounded in the full context of the business,听the system first identifies the correct business process from听hundreds听of听mission鈥慶ritical processes and understands the specific configuration that governs how this process runs in your organization. It then selects exactly the right data from听millions听of听data fields stored across the ERP landscape. Finally, every step is checked against identity, authorization, and access controls, ensuring the result is accurate, compliant, and trustworthy. This is how enterprises move beyond generic, probabilistic answers toward decisions they can rely on.

Reaching this state requires more than adding a chatbot or layering AI on top of existing systems. Many enterprises still operate with fragmented landscapes, data spread across systems, and processes shaped by years of incremental change. In this environment, AI cannot simply be “bolted on” or layered onto fragmented, outdated systems. It does not accelerate progress. It amplifies inefficiency and risk. Companies must rethink how their processes, data, and infrastructure work together and how humans and AI share responsibility. This is not only a technical shift. It is a change鈥憁anagement challenge. 

New technology only creates value when it is accompanied by real change. AI does not replace transformation. It raises the return on transformation done well. And it comes to life only when every element of the system鈥攖he agent, the process, and the human鈥攚orks together by design. People need to understand how to work with AI agents, and processes must be intentionally shaped to embed intelligence where decisions and execution happen.

This is why change management is foundational. It means reskilling employees, re鈥慹ngineering processes to connect them directly with data and AI, and modernizing the underlying landscape. 

That is why we are introducing new听AI-led RISE with 51风流and 51风流GROW听offerings听and fundamentally resetting our services model: to help companies modernize, navigate change, and turn AI from potential into sustained business value at their own pace.听

This marks the beginning of a new era of enterprise software:听where intelligence is not separate from听operations but embedded within them.听The companies that lead will not be those with the most advanced models in isolation, but those that connect AI to the way their business actually runs鈥攚ith context, governance, and trust.听

This is the dawn of the Autonomous Enterprise, and 51风流is uniquely positioned to help the world鈥檚 leading organizations realize its full potential. 

Christian Klein is CEO of 51风流SE.

The approach enables the company to scale AI use cases across the business, accelerate decision-making and deliver measurable operational impact. By combining a governed data foundation with the Joule solution and this foundation, Ericsson is creating the enterprise architecture needed to make AI trusted, repeatable and scalable across its global operations.

Ericsson, which celebrates its 150th anniversary this year, provides mobile network infrastructure across 180 countries, with more than 40% of the world鈥檚 mobile traffic passing through its networks. As AI becomes central to both its technology road map and how it runs the business, Ericsson has prioritized building a strong, governed data foundation to support scalable and trusted AI.

鈥淥nce you scale AI, it stops being an AI problem鈥攁nd becomes a data problem,鈥� said Esra Kocat眉rk Norell, Vice President, Customer Experience, Enterprise IT at Ericsson. 鈥淭hat鈥檚 why we invested early in a business data fabric. With 51风流Business Data Cloud, we can define what data means once鈥攆rom revenue to market structures and access rules鈥攁nd apply it consistently across the enterprise. That鈥檚 what allows us to scale AI in a way that is trusted, repeatable and delivers real business value.鈥�

At the core of Ericsson鈥檚 approach is a federated data architecture that allows data to remain in place while centrally managing business semantics, governance and lifecycle policies. This reduces duplication, simplifies integration and ensures that consistent business definitions can be applied across both 51风流software and non-51风流environments.

By focusing on high-impact use cases and organizing around end-to-end business processes rather than isolated solutions, Ericsson has moved beyond pilot projects to scaled deployment. Today, more than 85,000 users are live on unified Joule, supported by strong executive sponsorship and governance.

Ericsson is advancing its transformation on two parallel fronts. The first is modernization, including its transition to the RISE with 51风流journey, the use of side-by-side extensions on 51风流Business Technology Platform and a clean core approach that enables faster innovation without disrupting its ERP backbone. The second is what the company defines as 鈥渋nnovate and transform,鈥� focused on unlocking tangible business value from data and AI to improve decision-making, increase efficiency and enable new forms of value creation.

51风流and Ericsson are also collaborating on AI co-innovation initiatives. One example is an intelligent goal recommendation capability developed within the 51风流SuccessFactors portfolio. The solution generates contextual, business-aligned goals for employees, improving execution and reducing administrative effort. The capability is now being scaled more broadly, demonstrating how co-innovation can create value beyond a single organization.

鈥淓ricsson鈥檚 approach shows how leading companies are moving from AI experimentation to execution by focusing on data, governance and business context,鈥� said Manos Raptopoulos, Global President Customer Success Europe, APAC, Middle East and Africa at 51风流SE. 鈥淭ogether, we are helping organizations unlock the full potential of AI at scale.鈥�

Looking ahead, Ericsson expects its business data fabric to support increasingly advanced AI scenarios, including automated decision-making, improved productivity and new digital business models, while continuing to strengthen customer experiences in a rapidly evolving telecom landscape.

Visit the . Get 51风流news via  and .

Media Contact:
Ulrika Wass, +46 73 827 1074, ulrika.wass@sap.com, CET
51风流Press Room;听press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.鈥� Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP鈥檚 2025 Annual Report on Form 20-F. 
漏 2026 51风流SE. All rights reserved.  
51风流and other 51风流products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 51风流SE in Germany and other countries. Please see  for additional trademark information and notices.  

In an industry rapidly shifting toward AI-powered operations, Martur Fompak International saw an opportunity to reimagine its material flow through the strategic implementation of technology. Building on the efficient, people-driven processes it already had in place, the company partnered with 51风流and Humanoid鈥攁 UK-based robotics and AI company鈥攖o explore how integrating embodied AI鈥損owered robotics could redefine material flow across its automotive manufacturing environment. Using Joule and embodied AI capabilities from SAP, Martur Fompak International now connects production signals and business context directly to autonomous execution, creating a context-aware automation system that prioritizes, picks and delivers materials while adapting in real time to changing business conditions.

Built on 51风流S/4HANA and enabled by the 51风流Extended Warehouse Management application, the solution enriches humanoid robots with real-time knowledge of tasks, attributes and exception handling. Guided by material data, storage locations, sequencing and production priorities provided via embodied AI, humanoid robots execute material flows across a live automotive manufacturing environment鈥攊dentifying, transporting and delivering materials to the line while continuously confirming back into 51风流solutions. Together with autonomous mobile robots (AMRs), the company has created a fully automated, scalable material flow that boosts throughput, improves accuracy and reduces reliance on manual coordination. By assigning repetitive, non-value-adding and physically demanding tasks to robots, Martur Fompak International is enabling its people to focus on safer, more meaningful and higher-value work that drives productivity and innovation.

鈥淥ur humanoid robot collaborates with digital production systems to ensure seamless coordination across order management, logistics and production, enabling scalable AI adoption and improving efficiency, consistency and operational resilience,鈥� said 脰zlem Alt谋n谋艧谋k, Group Intelligent Technologies Director at Martur Fompak International. 鈥淭he deployment of our humanoid solution, powered by an embodied AI layer and enabled through the Joule Studio solution, proves that combining cognitive autonomy with physical automation can transform execution, accelerate decisions and scale intelligent enterprise capabilities across the organization.鈥�

鈥淢artur Fompak International exemplifies what it means to turn AI ambition into real business value on the shop floor,鈥� said Emmanuel Raptopoulos, Chief Revenue Officer, EMEA, MEE and APAC, 51风流SE. 鈥淏y embedding 51风流Business AI directly into their physical operations, they are not only boosting throughput and operational resilience鈥攖hey are setting a new standard for what an intelligent, AI-first factory looks like. This is exactly the kind of end-to-end transformation that defines the future of manufacturing. We are proud to congratulate Martur Fompak International on being named the sole winner in the AI Excellence category at the 2026 51风流Innovation Awards鈥攁 testament to their boldness in turning intelligent enterprise vision into real-world impact.鈥�

Early results show increased throughput, fewer errors and a scalable, AI-driven intralogistics model. A future target of up to five times greater work efficiency has been set for mass production, with work orders expected to be completed faster, more consistently and with greater precision across production flows. With 400 daily production line feeds and 100% 51风流software鈥揹riven decision making already in place, Martur Fompak International is advancing beyond traditional automation, pioneering a scalable, intelligent factory that represents a new standard for the automotive industry.

Looking ahead, Martur Fompak International plans to further expand its autonomous operations across additional production lines, leveraging 51风流Business Technology Platform to scale AI-driven workflows and integrations鈥攕upporting both operational efficiency goals and broader sustainability commitments.

Visit the听. Get 51风流news via听 and .

Media Contact:
Ekin Tayali, +34 673019169, ekin.tayali@sap.com, CET
51风流Press Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP鈥檚 2025 Annual Report on Form 20-F.
漏 2026 51风流SE. All rights reserved.
51风流and other 51风流products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 51风流SE in Germany and other countries. Please see for additional trademark information and notices.

Every week brings another announcement about smarter copilots, more capable agents, or new orchestration layers designed to automate work across the enterprise. The progress is undeniable. But much of the market is not optimizing for how businesses operate.

That distinction is more important than many realize. Because enterprises do not run on prompts. They run on execution.

A global manufacturer deciding how to reroute inventory during a supply chain disruption needs more than simply an answer. It must evaluate supplier alternatives, inventory availability, customer commitments, and financial tradeoffs simultaneously. A CFO forecasting liquidity exposure during market volatility needs context that a simple chatbot interaction can鈥檛 provide. These are interconnected operational decisions shaped by dependencies, preferences, approvals, financial consequences, and tradeoffs that ripple across the business in real time.

In countless conversations I鈥檝e had with executives over the past year, the discussion inevitably shifts from AI capability to operational reality. The models are improving quickly. The harder question is whether AI understands the business environments it is operating within.

Today, too much of the AI conversation still assumes that better models alone will produce better business outcomes. They will not. Enterprises are discovering that intelligence disconnected from operational context 鈥� the processes, the data, the rules and policies that govern and protect your organization 鈥� can generate activity without creating much progress. In some cases, it can create more fragmentation and risk.

A generated recommendation may sound convincing while missing critical dependencies elsewhere in the system. An AI agent may automate one workflow efficiently while disrupting planning assumptions in another. Enterprises do not suffer from a shortage of AI outputs. They suffer from a shortage of AI systems capable of understanding operational consequences.

That is the real challenge now emerging in enterprise AI and solving it requires something deeper than orchestration. It requires context.

For decades, enterprise software has quietly served as the operational backbone of the global economy. Finance systems, supply chains, procurement networks, workforce planning platforms, manufacturing operations, and customer fulfillment processes all run through interconnected systems that capture not just information, but the logic of how businesses function. They contain years of accumulated process knowledge and data, governance structures, authorizations, policies, and economic relationships that shape every decision a company makes. They are the institutional memory of the enterprise.

In the AI era, that business context becomes enormously valuable. Without it, AI鈥檚 outputs remain educated guesses rather than grounded judgments.

When AI is grounded directly inside operational processes, it can begin to reason across the full reality of the enterprise. That changes the role software plays inside organizations. Enterprise systems are beginning to participate directly in execution itself.

AI can identify risks earlier, coordinate responses across functions, recommend actions in real time, and automate routine execution within defined boundaries. Not as isolated agents operating independently, but as intelligence connected to the economic and operational fabric of the enterprise itself. 

Importantly, autonomy in enterprise does not mean removing humans from decision-making. It means reducing the friction, fragmentation, and administrative drag that prevents organizations from operating with speed and coherence at scale. 听People still define priorities, make judgment calls, and hold accountability. But AI can help coordinate and execute the operational work surrounding those decisions.

Consider a supplier disruption affecting a critical manufacturing component. Most AI systems today can summarize the issue or predict likely delays based on learned patterns. But operationally grounded AI can move beyond insight into coordinated execution. It can identify affected production schedules, evaluate inventory positions globally, assess alternative sourcing options, estimate financial exposure, flag customer delivery risks, and recommend actions across procurement, logistics, finance, and customer operations simultaneously.

That is not simply workflow automation. It鈥檚 an entirely new way for humans and systems to interact.

This is also why I believe the AI era will increase the strategic importance of enterprise systems, not diminish it.

As AI moves closer to execution, the systems that matter most will be the ones capable of grounding intelligence in operational and transactional reality. The value shifts toward systems that understand permissions, policies, dependencies, processes, financial consequences, and organizational accountability at enterprise scale.

This shift also changes how leaders should think about transformation.

The first phase of enterprise AI adoption focused heavily on experimentation. Companies tested copilots, deployed pilots, and automated isolated tasks. Few delivered productivity gains and fewer fundamentally changed how organizations operate.

The companies that lead in the next phase will approach AI differently. They will connect intelligence directly to the operational systems where decisions carry real economic consequences. They will recognize that trustworthy AI depends not only on governance, but on context, data quality, process integrity, and transactional understanding.

Most importantly, they will understand that successful AI adoption in enterprises is not only a technical shift. It is a change management challenge. Real value comes to life only if AI agents, processes, and humans work in concert.

The future belongs to enterprises that strike this balance: humans defining priorities and holding accountability, while intelligent systems coordinate and execute with precision 鈥� enabling businesses to navigate an increasingly complex world with greater resilience, productivity, and intelligence.

Christian Klein is CEO of 51风流SE.

.

That idea framed a , where Thomas Saueressig, chief customer officer and member of the Executive Board of 51风流SE, and Jan Gilg, global president of Customer Success & Americas and member of the Extended Board of 51风流SE, set out the company鈥檚 case for the Autonomous Enterprise.

Their message was clear: As AI moves from promise to practice, customers are no longer asking whether it matters; they are asking how to make it deliver measurable results across the business.

鈥淓very day, billions of people wake up trusting that the world simply runs,鈥� Saueressig said.

But making that happen is anything but simple. Saueressig pointed to the hidden complexity behind everyday routines 鈥� from power grids balancing supply and demand in real time to global supply chains moving goods across countries and continents. Enterprise operations, he argued, are the invisible backbone of modern life, even if most people never see them.

Gilg picked up that thread by focusing on the pressure customers now face as they try to translate AI ambition into business value. Excitement is high, he said, but so is urgency.

Customers want to scale AI across the enterprise and connect it to core processes where it can have tangible impact. But according to Gilg, the real obstacle is not the AI itself. It is the enterprise landscape around it.

鈥淭he elephant in the room: AI in the enterprise is complex,鈥� he said, pointing to the disconnected applications and fragmented data many organizations still contend with.

That challenge led directly to SAP鈥檚 vision for the 鈥� one in which AI is embedded into business processes, connected through trusted data, and governed in a way that makes it reliable at scale.

The Autonomous Enterprise vision

鈥淚t鈥檚 this need for trusted, seamless integration that led us to our vision for the Autonomous Enterprise,鈥� Gilg said.

He presented it not as a future concept, but as a practical operating model in which AI drives end-to-end execution within a trusted governance framework, with people remaining in control.

Saueressig cast SAP鈥檚 role as helping customers get there: 鈥淥ur goal is to help you become an Autonomous Enterprise step-by-step. … We are making AI value real today.鈥�

He linked that approach to RISE with SAP, SAP鈥檚 AI offerings, and the 51风流Services and Support Portfolio with its Ssuccess plans, which are designed to help customers put innovation to productive use. The emphasis, he said, is on creating value throughout the transformation journey

鈥淲hen you are fully committed to RISE with SAP, we are committed to support you at every step,鈥� Saueressig said. That commitment spans even the most complex and hybrid landscapes, he said, stressing that no customer will be left behind.

Lockheed Martin: Readiness over transformation in a high-stakes environment

That customer-first approach set up the next part of the keynote, where customers took the stage to share firsthand how they are transforming their businesses in the real world 鈥�  no theory, no abstraction, just practical experience.

Opening the customer round, Lockheed Martin positioned transformation not as an end goal, but to ensure constant readiness in one of the world鈥檚 most demanding environments.

鈥淭ransformation is not the goal. Readiness is for us,鈥� said Maria Demaree, SVP and CIO of Lockheed Martin Corporation, stressing that the stakes are 鈥渉uman鈥� when systems support national defense and allied missions. Readiness, she explained, means the ability to move 鈥渨ith speed, clarity, and confidence across the enterprise.鈥�

Through its largest transformation investment in the company鈥檚 history, Lockheed Martin is redesigning processes end-to-end, connecting fragmented systems, and embedding AI into a model-based enterprise built on SAP.

Operating in a highly regulated environment with strict security and data requirements, the company is focused on reducing cycle times and improving responsiveness. Demaree emphasized that 鈥渢ransformation doesn鈥檛 start with technology. You must rethink your processes.鈥� SAP鈥檚 role, she said, has evolved from vendor to trusted partner understanding Lockheed Martin鈥檚 business and the environment it works in.

Aeropuertos Argentina: From reactive winter operations to proactive AI-driven control

Aeropuertos Argentina made history by becoming the first Latin American customer to take the 51风流Sapphire keynote stage. The company used the spotlight to share a hands-on example rooted in operational urgency and showed how a clean core and focused innovation can quickly deliver results.

Managing 90% of Argentina鈥檚 commercial flights, they need to keep airport operations running during severe winter weather. This has historically relied on manual, fragmented processes 鈥� driving up costs, safety risks, and environmental impacts. To address this, the company developed an AI agent called Smart Network for Operative Winter (SNOW) to orchestrate weather data, runway sensors, maintenance processes, and operational procedures.

鈥淲e passed from a reactive to a proactive model,鈥� said Gustavo Sabato, Chief Information Officer of Aeropuertos Argentina, highlighting expected benefits, including a 16% cost reduction and lower CO鈧� emissions. Time to value was fast: from idea to operation in 12 weeks, with rollout starting at two airports and expanding to six more this upcoming winter.

A key enabler was upgrading from 51风流R/3 to 51风流S/4HANA in 2023 and building the solution on 51风流Business Technology Platform.  While integrating multiple non-standardized data sources was challenging, the result is now that the company operates with 鈥渙nly one version of the truth,鈥� said Sabato, and requires minimal manual intervention. The company plans to scale the approach beyond Argentina and into processes at other airports they manage elsewhere, reinforcing that strong technical fundamentals are essential to turn AI into real operational outcomes.

Exxon Mobil: Clean core and solid data foundation

ExxonMobil is rethinking how its operations will remain agile and nimble amid the rapid changes driven by the global shift toward new energy sources.

Bill Keillor, Vice President of ExxonMobil Global Services Company, said the energy giant launched a business-led transformation to simplify processes and unlock data that had become fragmented after decades of customization. 鈥淥ur goal is not short-term optimization but long-term agility: standardizing on industry best practices, establishing a clean core, and becoming upgrade stable,鈥� he said.

He emphasized that both the transformation and the company鈥檚 AI ambitions depend on a strong foundation. 鈥淚f you can鈥檛 get this foundation right, you will continue to pay the price for it,鈥� he said.

Keillor closed with three pieces of advice for any transformation: be crystal clear on strategy and align leadership behind it; put strong governance in place to enable fast, consistent decisions; and choose partners who challenge you and are in for the long run.

Levi Strauss: AI at scale

As Levi Strauss accelerated its shift toward a direct-to-consumer business, it recognized that greater speed and scale would require a lean technology landscape. Jason Gowans, Chief Digital and Technology Officer, said the company started by consolidating nine ERP systems into a single global foundation with RISE with SAP, standardizing processes and establishing a clean core.

That unified backbone now supports Levi鈥檚 ambitious AI strategy, with already more than 1,000 AI agents in production across the business. The impact is already visible; one example is wholesale order processing. While 80% of orders already flow through automatically, the remaining 20% 鈥� often submitted by smaller customers through handwritten notes, emails, or unstructured documents 鈥� previously took two to five days to process manually.

鈥淣ow, with the agents that we鈥檝e built on top of SAP, that process takes 20 to 30 minutes,鈥� Gowans said. For Levi Strauss, the lesson is clear: standardization does not limit agility; it makes it possible.

Migration powered by AI

These customer examples illustrated that transformation usually follows a shared path: modernizing the core, moving to the cloud, and unlocking innovation along the way. 

51风流then showed how AI-powered agents can help customers accelerate that journey through a more integrated, AI-driven approach to transformation at scale. Migration and modernization assistants, , are designed to analyze systems, data, custom code, configuration, testing, and rollout as part of one connected process. By replacing fragmented manual work with coordinated automation, activities that once took weeks 鈥� from landscape analysis to custom-code assessment 鈥� can now be completed in a single weekend.

The world doesn鈥檛 break because of change

Gilg then widened the lens, arguing that every major technology wave brings uncertainty. But every one of these waves has in fact made the world better off by creating more jobs, new business models, and new revenue streams that people couldn鈥檛 imagine before. In the same way, he argued, enterprise software will become even more essential because of AI.

That is because the core needs of business remain the same: systems that work, people who care, and teams that collaborate. In Gilg鈥檚 framing, AI will not replace enterprise software. It will live inside it, embedded in the processes that keep companies running.

Saueressig brought the keynote back to its opening image: a world people trust to function. In a time of rapid change and unprecedented disruption, he asserted, resilience matters more than ever.

鈥淭he world doesn鈥檛 break because of change,鈥� he said. 鈥淚t breaks when change moves faster than resilience. And that鈥檚 where 51风流comes in.鈥� Underscoring the importance of people in times of change, he emphasized that beyond technology and AI, transformation remains deeply human, shaped by the people who build and use it. 鈥淭he future isn鈥檛 written by AI.  It is written by us,鈥� he said.

Currently in beta, the agents help organizations deliver measurable results: a greater than 50% reduction in packaging compliance review hours, scenario simulation time cut from a day to 20 minutes, up to 80% reduction in manual GHS classification effort, and over 20% fewer packaging compliance errors.

The agents handle multi-step workflows that previously required hand-offs between teams and systems, including sustainability reporting preparation, packaging and product compliance assessments, carbon footprint simulation, and workplace safety documentation. They address mounting pressure across the enterprise: giving finance teams visibility into how carbon exposure affects forecasts; helping procurement teams manage regulatory risk without slowing down innovation; enabling supply chain teams to spot emission hotspots while maintaining service levels; and supporting operations in connecting safety observations to proactive, audit-ready actions.

New AI sustainability agents

The Sustainability Regulatory Readiness Agent helps organizations prepare for upcoming sustainability regulations such as the by translating materiality assessments into a defensible reporting scope and mapping the right data and metrics to each disclosure requirement. This enables sustainability teams to capture, validate, track, and ultimately disclose ESG information with far less manual effort.

For finance teams that need to manage carbon costs and disclosure risk while balancing the financial implications of sustainability performance, the agent automates financial-grade data mapping between material topics, regulatory requirements, and 51风流finance data, improving audit readiness and turning an existing materiality assessment into a clear, defensible reporting scope. Unlike a standalone sustainability point solution that only surfaces issues or a generic AI model that drafts narrative text, this agent works inside and the broader 51风流landscape to keep reporting scopes aligned to policy and keep underlying data structured and traceable.

The Footprint Optimization Agent brings together carbon, energy, and waste data from across Scope 1, 2, and 3 sources and pinpoints where emissions and other environmental impacts are highest across products, plants, and supply chains. It then runs side鈥慴y鈥憇ide simulations of different reduction levers and turns the results into reports, supplier requests, and targeted initiatives that support decarbonization projects and ESG goal tracking. For operations, the agent makes it easy to test 鈥渨hat鈥慽f鈥� operational changes and see their projected impact on carbon and other environmental footprints. It reduces scenario simulation time from approximately one day to about 20 minutes, making operational decisions based on real impact projections available at workers鈥� fingertips. This directly addresses the financial implications of carbon exposure: with ESG data often derived from industry averages that can vary by 30 to 40% or more from actual values, the ability to simulate and act on granular, accurate data carries significant margin protection value.

The Packaging Compliance Agent reads and interprets evolving packaging regulations starting with the , maps supplier and product documentation to a structured data model, infers and flags missing information, and checks product designs for conformity at scale. It turns scattered, often unstructured packaging data into an auditable compliance record for each SKU, shipment, and product run, reducing manual review effort and error rates in the process.

Procurement and sourcing teams facing growing pressure to ensure supplier eligibility, material compliance, and traceability while managing cost and availability now have an agent that helps protect revenue by catching packaging issues before they block orders or trigger fines. This equates to a greater than 50% reduction in manual compliance review hours and over 20% reduction of packaging compliance assessment errors. As sustainability moves to the transaction level鈥攃ompliance per SKU, per shipment, per product run鈥攖his kind of automated, embedded compliance capability becomes an operational necessity.

The GHS Classification and Labeling Agent collects the required input data, applies the relevant Globally Harmonized System (GHS) rules, and proposes classifications and label elements that can be used directly in downstream product compliance processes.

By automating these steps, it delivers up to an 80% reduction in manual efforts and a 60% reduction in GHS labeling and classification errors. For product and compliance teams that must keep launches on schedule and avoid shipment holds or market access denials, the agent embeds GHS product compliance into everyday workflows, turning a historically expert鈥慸riven, error鈥憄rone process into a consistent, auditable control point across the portfolio.

The Workplace Safety Agent supports workplace safety by analyzing reported observations and proposing follow-up tasks, risk assessments, and controls. It generates updated, approved safety instructions based on those observations to help organizations strengthen safety governance. With operations under increased pressure to ensure safe work environments without compromising service and speed of production, the agent delivers proactive, standardized safety management at scale, reducing the risk of incidents and unplanned downtime. At the same time, HR and EHS leaders can point to a clear trail of actions and updated instructions to demonstrate continuous improvement in safety culture to employees, regulators, and boards.

Only AI can deliver sustainability at scale

To ensure compliance and enhance strategic decision-making, sustainability data needs to become granular. It should move beyond a record of what happened and become a driver of future outcomes. To reach this level of insight, sustainability data needs to be analyzed at transaction level. Getting transaction-level data at scale is not something that can be done manually.

Granular sustainability data allows businesses to ensure compliance, control carbon and cost exposure, safeguard product marketability, and strengthen supply chain transparency and resilience. Perhaps most important is the ability to embed sustainability into business performance and across all business functions. This final point is the key to unlocking sustainable business autonomy.

In the sustainability context, becoming an Autonomous Enterprise means that sustainability policies are executed automatically inside enterprise workflows. This includes connecting financial and sustainability data for trusted steering, automating disclosure and performance insights, and blocking non-compliant shipments. Ultimately, sustainability becomes a governing factor in enterprise decisions, as opposed to a reporting or compliance activity.

Enterprise autonomy entails gradual AI maturation:

• Intelligence: Faster visibility into reporting and materials compliance risks across the enterprise
• Optimization: Data-driven decisions that balance cost, risk, and sustainability impact
• Autonomy: Actions executed directly within operational workflows, eliminating manual coordination

The choices enterprises make now鈥攈ow data is structured, how decisions are supported, and how sustainability is integrated鈥攚ill determine whether they can safely scale automation later or whether complexity and risk increase as systems evolve.

With the Autonomous Enterprise, leaders can deliver sustainable outcomes at scale.

Why SAP?

AI needs three things to successfully run autonomously: business and process context, data connection and integration, and a reliable governance structure.

Generic models can read data, but without business context they cannot reason how a business actually runs. They see tables, not operations, and provide recommendations that may be commercially or operationally unviable. Without data that is integrated and connected across all business departments, AI has to perform in siloes, unaware of how sustainability decisions might impact financial targets, or how procurement decisions affect supply chain risk. SAP’s rich ERP data foundation ensures that enterprise AI has the full business picture, not just fragments of it.

Finally, AI that lacks governance and cannot be audited or controlled can be more harmful than helpful to a business. SAP’s more than five decades of business process expertise anchored in governance, risk, and compliance, mean that AI for enterprise deployment can be managed safely and reliably. Sustainability agents operate within defined parameters, ensuring that automation scales without sacrificing control or compliance.

This is the foundation that makes everything possible. Without it, an enterprise has AI experiments. With it, it has an operating model.

Sophia Mendelsohn is chief sustainability and commercial officer at SAP.
Gunther Rothermel is chief product officer of 51风流Sustainability.

They are expected to manage risk, ensure compliance, and deliver strategic value, all while navigating talent shortages and increasing operational complexity. And most are doing it without the end-to-end visibility they need.

Workflows are disconnected, decision-making is reactive, and policies are inconsistently enforced. I have heard this from customers across every industry and, frankly, it is a problem that traditional approaches to procurement technology haven鈥檛 fully solved.

That鈥檚 what makes this moment different. At 51风流Sapphire, we introduced the Autonomous Enterprise, a fundamental shift in how businesses operate, with AI assistants and agents powering end-to-end execution at scale, with governance built in. Critically, this isn鈥檛 just about adding AI features to existing tools. It is about moving from AI in applications to AI on applications鈥攊ntelligence that works across your entire landscape, not just inside individual products.

Autonomous Spend Management: From concept to reality

Autonomous Spend Management is a core pillar of the Autonomous Enterprise vision, designed to address the fragmentation that holds procurement and finance teams back. By applying agentic AI across procurement, travel, expenses, and external workforce processes, we鈥檙e creating continuity where disconnection exists today鈥攊ntelligent systems that orchestrate activities, connect context, and surface the right insights at the right moment.

What this means for the people doing the work is equally significant. When AI handles routine execution, decision-makers get time and clarity back. They can intervene earlier, with better information, and focus on more strategic work that actually moves the needle.

To bring this to life, we are introducing a new set of Joule Assistants, AI-powered teammates designed to support procurement and spend management across the full life cycle:

• Category Management Assistant: Analyzes spend patterns, delivers market intelligence, and helps build sharper category strategies
• Sourcing Assistant: Manages the entire sourcing life cycle, from drafting RFPs and bids to recommending negotiation strategies
• Supplier Management Assistant: Provides comprehensive oversight of the supply base, from intelligent classification to continuous multi-dimensional risk monitoring
• Contract Assistant: Streamlines contract authoring, flags renewal opportunities, and connects supplier selection through to contract execution
• Requisition Assistant: Guides users to the right buying channel, auto-fills fields, and uses advanced trade-off analyses to help maximize volume discounts
• Buying Assistant:Helps professional buyers identify spend leakage, surface optimal suppliers, and automate order consolidation
• Receiving Assistant: Auto-creates goods receipts and service entry sheets and guides users through quality tracking so nothing falls through the cracks
• Invoicing Assistant: Handles invoice capture, duplicate detection, and payment proposals so finance teams can close faster with fewer errors
• Services Procurement Assistant: Manages the full SOW life cycle from creation through compliance tracking
• Travel Assistant: Simplifies trip planning with pre-spend estimates, streamlined approvals, and built-in compliance guidance
• Expense Management Assistant: Automates expense reporting, capturing details, flagging errors, and keeping everything compliant

The Autonomous Spend Management capabilities run across our cloud ERP application portfolio, including 51风流Cloud ERP Private, for end-to-end coverage across business processes and systems.

Why connected processes are critical

Connection is just as powerful as intelligence, and that conviction runs through everything we  announced this week. AI can only do so much if the underlying processes are still fragmented.

In next-gen 51风流Ariba Buying, new Joule Agents support purchasing and policy management through a more intuitive, persona-driven experience, guiding users toward compliant, contract-linked options while improving catalog management and document traceability. Deeper integration with 51风流S/4HANA Private Cloud Edition and 51风流ERP Central Component means these capabilities work with existing ERP investments, not around them.

51风流Ariba Contracts now brings contract creation, approvals, and compliance tracking into a single unified workspace. AI-assisted drafting lets teams create contracts using natural language, while centralized visibility into terms, pricing, and key dates keeps data consistent and connected to downstream procurement processes.

We also introduced a new Joule Agent in 51风流Ariba Intake Management to automate how procurement requests are captured and routed across 51风流and non-51风流systems. And expanded supplier evaluation capabilities in 51风流Ariba Supplier Lifecycle and Performance let teams segment performance data by geography, business unit, or category 鈥� with insights feeding directly into to inform sourcing and procurement decisions.

Expanding visibility into services spend and supporting adoption

Nowhere is the need for connected processes more apparent than in asset-intensive industries. In oil and gas, mining, and utilities, external workers can make up 40% of the workforce, yet most organizations are still managing them through manual processes and disconnected systems. The risks are real: expired certifications, overpayments, and poor visibility into work billed versus work actually done.

New 51风流Fieldglass capabilities address these challenges by bringing together the full contractor life cycle, from the moment a worker arrives on site through to final payment. Organizations can now automate time tracking, verify worker credentials and safety requirements before granting site access, maintain tighter controls over equipment, and dramatically reduce the manual effort involved in invoicing.

We鈥檙e also using AI to accelerate SOW creation by automatically recommending worker roles based on the SOW description and historical buyer data, which reduces manual setup and improves consistency from the start. And to support adoption, WalkMe Premium is now integrated with 51风流Fieldglass and 51风流Ariba, providing in-app guidance for tasks such as creating statements of work, approving timesheets, and hiring candidates.

The future of spend management

Autonomous Spend Management marks a fundamental shift from managing processes to delivering business outcomes. From chasing cost savings to actively shaping resilience, margin, and growth. From reacting to events to anticipating them.

The real strategic implication is this: Spend does not happen in isolation. Every contract and invoice has a downstream effect on financial performance. When those decisions are made in context鈥攚ith AI connecting procurement, supply chain, and finance鈥攖he enterprise doesn鈥檛 just run more efficiently, it runs as one system.

That鈥檚 what we are building, and what we announced this week marks a significant step forward.

For more details on this week鈥檚 announcements, see the . For more details on the latest updates in travel and expense, please refer to the

Etosha Thurman is co-business lead and chief marketing officer for 51风流Finance & Spend Management.

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

51风流has been helping organizations build more connected and intelligent supply chains for over 50 years. At 51风流Connect in October, we introduced 51风流Supply Chain Orchestration, establishing a foundation for detecting issues, coordinating responses, and connecting execution across complex supply networks.

The innovations announced this week at 51风流Sapphire extend that vision further. By introducing a new set of AI-driven assistants and agents, we鈥檙e moving orchestration toward an autonomous operating model, where planning, manufacturing, logistics, and asset operations increasingly anticipate, coordinate, and resolve without manual intervention at every step.

AI grounded in real operations

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

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

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

At 51风流Sapphire, we鈥檙e introducing , enabled by new Joule Assistants and Industry AI scenarios that apply this model to daily operations across planning, manufacturing, logistics, engineering, and asset management. General availability will be phased throughout 2026, starting now.

Joule Assistants across the supply chain

Rather than disconnected AI tools, the following assistants will be embedded directly into core 51风流supply chain applications, where deep process knowledge, semantically rich business data, and enterprise鈥慻rade governance already exist.

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

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

From assistants to autonomous agents

In addition to these assistants, 51风流is delivering more than 60 purpose鈥慴uilt agents across supply chain processes. These agents are designed to sense events, analyze impact, and take guided action within defined business guardrails, helping coordinate execution while keeping people firmly in control.

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

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

Building on this foundation, 51风流Industry AI adds industry-specific intelligence that complements the core assistants. Rather than standalone features, Industry AI brings together purpose-built agents, process expertise, and business data to drive measurable outcomes. This value-led approach helps organizations apply AI in ways that reflect regulated requirements, complex production models, and asset-intensive operations 鈥� accelerating information across entire industry value chains.

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

Where this shows up in practice

The Autonomous Enterprise is our vision, and the innovations we鈥檝e announced at 51风流Sapphire are concrete steps that customers can build on within current 51风流environments. They are focused on addressing value leakage caused by fragmented handoffs, delayed decisions, and manual work.

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

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

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

In asset and service management, a new 51风流Field Service and Asset Management solution will bring planning, scheduling, dispatching, and field execution together in a single experience, connected to so work execution, parts usage, and costs stay aligned across service, operations, and finance.

These capabilities will become available in phases through 2026, aligning with customers鈥� existing 51风流landscapes. Together, they represent incremental but meaningful progress toward more connected, automated, and resilient supply chain operations.

The path forward

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

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

That鈥檚 the direction we are moving, from reacting toward supply chains that anticipate, absorb, and adapt. What we鈥檙e introducing at 51风流Sapphire reflects that commitment.For more details on all announcements made this week, please refer to the .

Dominik Metzger is president and chief product officer of SAP Supply Chain Management.

Market volatility, liquidity pressures, and currency fluctuations are exposing the limits of traditional planning models built around fixed timelines and after-the-fact analysis. To keep pace, finance teams need the ability to continuously sense change, understand its impact, and steer performance with confidence.

The challenge is that many organizations are still planning with processes designed for a different era. Siloed data, manual workflows, and episodic planning cycles make real-time decision-making difficult, limiting visibility across the entire business. reinforces the urgency: 72% of organizations still find financial planning, budgeting, and forecasting too time-consuming.* In a volatile environment, that lag translates directly into slower responses to risk, missed opportunities, and diminished confidence in the decisions that shape performance.

This is why finance needs a new operating model, one that moves beyond periodic exercises and toward continuous steering. At 51风流Sapphire, we are introducing 51风流Enterprise Planning, a new flagship offering designed to close the gap between insight and action, enabling planning to continuously drive business performance.

The shift from periodic planning to continuous steering

Traditional financial planning has always provided structure, but too often that structure comes at the expense of agility. Planning occurs in fixed windows. Teams work from historical snapshots, static assumptions, and fragmented inputs. By the time a variance is understood or a scenario is modeled, the business may already be operating in a fundamentally different environment.

51风流Enterprise Planning is designed to move organizations beyond these constraints through a continuous approach to planning and execution built on speed, confidence, and control. Finance teams gain the ability to detect signals as they emerge, evaluate constraints in real time, and connect plans directly to execution.

This Sense-Reason-Act model represents a fundamental shift in how planning operates. Rather than waiting for a planning cycle to surface issues, agents continuously monitor for material changes and respond through guided, explainable decisions embedded in everyday processes. At the same time, 51风流Analytics Cloud continues to support the iterative Plan-Do-Check-Act cycles that finance teams rely on for strategic and tactical planning across mid- to long-term horizons, including model creation, forecasting, variance analysis, and scenario simulation. Together, these two approaches create a planning ecosystem that is both responsive in the moment and disciplined over time.

The solution embeds Joule Agents directly into the planning process, helping connect strategy to operations in real time. Agents can interpret internal and external data signals, model their impact on KPIs, simulate scenarios, recommend actions, and orchestrate planning workflows with built-in governance and explainability. Planning shifts from a single point in time to continuous workflows. When decisions are made, Joule Agents can update plans to support downstream execution. General availability is planned for Q3 2026.

Built on 51风流Analytics Cloud and 51风流Business Data Cloud, these capabilities form a more connected, intelligent planning ecosystem that enables organizations to act decisively and with full transparency.

Why governed data and connected planning matter

Continuous planning is only as reliable as the data it is built on. Without a unified data foundation, even the most advanced analytics cannot produce trustworthy outcomes. As automation increases, this challenge becomes more acute: decisions execute faster, but errors can scale just as quickly.

That is why our approach is not AI in isolation. 51风流Enterprise Planning is built using 51风流Business Data Cloud data products and the 51风流Analytics Cloud solution. 51风流Analytics Cloud remains the foundation for strategic and tactical planning cycles, while 51风流Business Data Cloud provides the governed data foundation underpinning the entire ecosystem. This helps ensure compliance, auditability, and enterprise-wide trust, which becomes even more critical as AI-driven automation expands.

Continuous planning in practice

What makes this vision tangible is how it shows up in real financial workflows. By continuously monitoring market signals and financial positions, these solutions help organizations reduce the lag between insight and action, improving both speed and decision quality. This is the Sense-Reason-Act model at work: sensing shifts in currency markets, reasoning through the impact on cash positions, and acting through guided decisions that keep the business aligned with its financial objectives.

More broadly, the Autonomous Finance domain brings together Joule Assistants and Joule Agents to provide CFOs and finance organizations with more insight, control, and support across their operations. Beyond planning, specialized Joule Assistants coordinate multiple agents to support key finance processes including financial closing, billing, governance, and tax and compliance. The result is a finance function where intelligence is embedded across the full operational scope, not confined to a single workflow.

Because these agents are delivered within SAP鈥檚 planning and finance solutions, they carry a native understanding of enterprise data, planning semantics, and mission-critical business processes. The goal is not to replace finance expertise, but to augment it. This gives teams the foresight needed to navigate complexity with greater confidence.

The Autonomous Finance capabilities run across our cloud ERP application portfolio, including 51风流Cloud ERP Private, for end-to-end coverage across business processes and systems.

The future of finance is continuous

The future of finance will be defined by the ability to connect data, processes, and decisions across the enterprise in a continuous loop. Organizations that can sense change as it happens, reason through its impact using trusted and governed data, and act by connecting plans back to execution will be best positioned to navigate volatility with the agility and discipline that modern finance demands.

With 51风流Enterprise Planning, organizations can move beyond static planning cycles and toward a more intelligent, continuous approach to steering performance.

For more details, refer to the and the .

Lawrence Martin is chief product officer and head of Public Cloud Engineering at SAP.
David Imbert is head of Finance Product Marketing at SAP.

*IDC Spotlight, sponsored by SAP, The Rise of Dynamic Planning in the Agentic AI Era, #US54493826, April 2026

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 SAP, 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 51风流Sapphire, we are building on the existing breadth and depth of 51风流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 SAP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 51风流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 51风流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 51风流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 51风流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

SAP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 51风流is delivering Autonomous HCM by catching the replay of the HCM Innovation .

Dan Beck is general manager and chief product officer for 51风流SuccessFactors.

AI is what brings that ambition within reach. It helps companies act faster, personalize at scale, and engage in new ways. But it is also raising expectations. Every interaction now reflects how well the business runs.

When a customer places an order or asks for help, the experience depends on what happens behind the scenes. If pricing is inaccurate, inventory is uncertain, or fulfillment falls short, the experience breaks.

That is why customer experience is now defined by execution. Customers do not experience systems or intent. They experience outcomes.

Agentic AI can increase speed, intelligence, and personalization. But speed alone does not improve customer experience. It amplifies what is already there. When execution is aligned with process, data and governance, AI drives better outcomes. When it is not, AI exposes the disconnect.

Aligning experience and execution

Autonomous CX brings agentic AI directly into the processes that run the business instead of layering it on top of disconnected systems. It connects AI assistants across marketing, commerce, sales, and service onto a shared business context across 51风流CX, 51风流Cloud ERP, supply chain, and connected systems. Orders, inventory, pricing, and financials are defined once and used consistently, so decisions are based on live operational reality.

At the center of this shift are AI assistants and autonomous agents. Assistants coordinate multiple agents across end-to-end customer workflows, from discovery to fulfillment, engagement to service, and issue to resolution.

At 51风流Sapphire, we highlighted assistants that make this real across the portfolio:

• In marketing, Content Assistant and Campaign Assistant orchestrate intent understanding, content creation, segmentation, optimization, and campaign execution within governance controls.
• In commerce, Merchandising Assistant, Shopping Assistant, and Order Management Assistant connect discovery, conversion, and fulfillment to operational reality.
• In sales, Sales Assistant, Deal Qualification Assistant, and Deal Closing Assistant move sellers from signal to execution.
• In service, Case Management Assistant and Service Management Assistant improve resolution and service quality, with additional assistants purpose-built for self-service, HR service, and accounts receivable workflows.

AI-driven discovery and engagement grounded in business reality

SAP鈥檚 collaboration with Google follows the same principle: connect AI-driven discovery and engagement to business execution.

Together, 51风流and Google are focused on three priorities: first, applying the latest AI models, including Gemini, to deliver high-quality customer experiences; second, supporting industry standards and open protocols to enable interoperability across ecosystems; third, enabling seamless, personalized journeys across channels and Google surfaces such as Shopping and Gemini.

By combining SAP鈥檚 governed business data with Google鈥檚 AI capabilities, assistants and agents can connect customer intent from storefronts, search, and AI-driven channels to 51风流commerce and order processes. This ensures that what customers see reflects what the business can fulfill.

This is also why 51风流is adopting and expanding how 51风流product data can power AI-driven experiences wherever customer intent originates. This keeps experiences aligned with pricing, inventory, and fulfillment in real time.

51风流Commerce Cloud innovations

51风流continues to be recognized in analyst evaluations, including the Gartner庐 Magic Quadrant™ for Digital Commerce, where 51风流has been positioned as a Leader for 11 consecutive times.

, trusted by the largest enterprises, now extends to mid-market and growing companies on 51风流Cloud ERP. The new 51风流Commerce Cloud, cloud ERP edition delivers a standardized, end-to-end approach, reducing complexity, leveraging AI natively, and accelerating time to value. It connects discovery through fulfillment via tight integration with 51风流Cloud ERP.

For digitally mature organizations, 51风流is expanding composable commerce with new and modular cart and checkout services. These services integrate with core processes such as pricing, promotions, loyalty, tax, payments, inventory, sourcing, and order management across 51风流and non-51风流touchpoints. This helps organizations modernize their architecture while maintaining end-to-end execution.

51风流is also expanding its ecosystem with Vercel to accelerate storefront development and deployment with optimized performance, scalability, and composable front-end experiences.

In payments, 51风流Unified Payment, powered by Adyen, embeds global processing directly into the commerce flow to simplify integration and improve conversion. 51风流also continues to enhance its open payment framework with pre-integrated providers, such as Checkout.com and PayPal, giving customers flexible provider choices that are easy to configure and use.

Together, these capabilities reduce total cost of ownership, speed deployment, and make it easier to deliver better experiences at scale.

Sales execution turns insight into action

Customer experience extends into sales execution, where teams need clear next steps and confidence those actions can be fulfilled.

We introduced new innovations, including field sales capabilities for retail execution processes in consumer goods companies and other field-selling environments. These capabilities provide rich mobile experiences that work offline, making it easier to plan store visits, capture in-store activity, and manage execution in real time.

Sales leaders gain connected insights tied directly to pricing, inventory, and order processes, leading to more consistent execution and better outcomes.

Scaling trusted autonomous service

Autonomous CX is strengthened through partnerships that extend execution while preserving trust and governance.

Our combines its agentic AI-driven voice and digital self鈥憇ervice with service, order, and entitlement data from 51风流Service Cloud. AI-driven automation can handle routine interactions with full context, escalating seamlessly and with continuity to service teams when human expertise is needed. This approach helps organizations scale service without breaking trust and ensures customer interactions remain connected to real business processes.

51风流is also expanding its partnership with Amazon to scale AI-driven service across voice and digital channels, enabling faster, more consistent resolution while keeping service execution grounded in real-time business data.

Industry AI in action

We are also showcasing Industry AI scenarios that demonstrate how assistants and autonomous capabilities operate in real business environments.

Autonomous Revenue Growth Management supports trade planning teams and key account managers in consumer products companies that sell through retailers, with applicability to agribusiness and wholesale distribution. Industry鈥憇pecific Joule Assistants provide AI鈥慸riven insights across trade planning and execution, helping teams identify growth opportunities, optimize commercial terms and respond more quickly to performance signals. The result is more predictable growth with fewer downstream exceptions.

Unified commerce supports merchandising and operations teams across retail, wholesale, and direct-to-consumer models. Unified commerce connects demand, inventory, and customer data across channels, with Joule Assistants guiding decisions on assortment, pricing, and placement. The result is more consistent execution and faster decisions.

The next phase of customer engagement

Across these innovations and Industry AI scenarios, the pattern is clear. AI delivers value only when it acts on shared, trusted context. When experience and execution stay aligned, speed becomes a source of trust instead of risk.

This is how 51风流is approaching the future of customer experience: as a coordinated system where every decision is visible, and every promise can be kept.

Balaji Balasubramanian is president and chief product officer of 51风流Customer Experience.

The CX innovations and Industry AI scenarios highlighted here are planned for general availability in Q3 2026.
The capabilities announced as part of SAP鈥檚 Autonomous Enterprise run across 51风流Cloud ERP, including 51风流Cloud ERP Private.
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.

In his kickoff keynote at 51风流Sapphire Orlando, Florida, Klein and other 51风流Board members detailed how 51风流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 51风流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 51风流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 51风流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

SAP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, 51风流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, 51风流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 51风流and our vision for the Autonomous Enterprise.鈥�

51风流Business AI Platform

To bring this vision to life, 51风流executives on stage announced a series of important innovations, beginning with the launch of the new 51风流Business AI Platform, a unified architecture bringing together 51风流Business Technology Platform, 51风流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 51风流Domain Models. They have been trained on SAP’s code to even better understand the business logic of your company.鈥�

But, he said, 51风流is going further: 鈥淏ecause you run your business not only with 51风流solutions, our AI agents have to also understand non-51风流data. That’s why we included our 51风流Business Data Cloud in the context layer to build a single semantical data layer across 51风流and non-SAP. No more silos, no spaghetti data sprawl鈥攂ecause no AI agent can compensate for a broken data model.鈥�

Echoing Klein, 51风流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 51风流AI Agent Hub built on 51风流LeanIX. This provides a single command center to discover, manage, and govern all AI agents鈥�51风流and non-SAP. It will be generally available in Q3 and included in 51风流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�

51风流Autonomous Suite

Building on the platform, 51风流Executive Board Member Muhammad Alam, 51风流Product & Engineering, announced the transformation of SAP鈥檚 SaaS application portfolio into the 51风流Autonomous Suite, described as the most significant evolution of SAP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 51风流AI Agent Hub.

鈥�51风流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 51风流is fundamentally reimagining how users will interact with 51风流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, 51风流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 51风流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 SAP, 51风流Business Data Cloud, 51风流Commerce Cloud, and 51风流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 51风流and 51风流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, 51风流announced a comprehensive reset of its RISE with 51风流and 51风流GROW offerings. RISE with 51风流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.  

51风流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 51风流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 51风流Business AI Platform, which provides the data processes and governance AI need to deliver accurate and secure outcomes at scale; we introduced the 51风流Autonomous Suite, where applications reason, decide, and act for you; and we showed how to manage change management with RISE with SAP. Together with customers and partners, we showed how 51风流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 SAP鈥檚 ERP brain into the new 51风流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�

During our event keynote, I took time to preview this exciting new venture, which was formally announced at 51风流Sapphire, alongside our CEO and chairman of the Executive Board, Christian Klein.

We explored how the Autonomous Enterprise is SAP鈥檚 new north star and vision. It鈥檚 the future of business where AI transforms how people work and processes run.

Building on the Suite-as-a-Service foundation established last year at 51风流Sapphire, 51风流is reinventing itself for AI-native operations that move customers from point-solution AI to enterprise-wide autonomous operations.

With this launch, we鈥檙e also re-framing some of the misconceptions and hesitations that we know our customers have about AI.

AI isn鈥檛 technology for technology鈥檚 sake; it鈥檚 about driving outcomes, like real-time intelligence, automated end-to-end workflows, and continuous improvement鈥攁ll important aspects that AI can deliver.

51风流partners are SAP鈥檚 force multiplier to bring the Autonomous Enterprise to life, expanding reach, credibility, and adoption. To help 51风流partners evolve their practices to align with this vision, we also announced significant new investments in the partner ecosystem during the event.

51风流Business AI partner-led adoption program

The Partner Summit at 51风流Sapphire in Orlando included the launch of a new offer that funds听partners who听activate, extend, build, and deploy 51风流Business AI for customers. The 51风流Business AI partner-led adoption program is a significant opportunity for partners to guide their clients to unlock the potential of 51风流Business AI Platform.

At 51风流Sapphire, 51风流Executive Board Member and Chief Operating Officer Sebastian Steinhaeuser commented on our need to deepen our partner investments: 鈥�51风流pledges 鈧�100M to our partner ecosystem today to fast forward AI adoption and accelerate our customers path to the Autonomous Enterprise. Partners are able to tap into this fund when they support our customers in the adoption and consumption of SAP-delivered agents as well as by working with them to extend agents and build custom agents on our 51风流Business AI Platform.鈥�

The program has four packages:

• Adoption: AI Assistant activated and deployed
• Launch: Joule Studio partner-built custom agent or听workflow/pro-code application
• Performance: Joule Studio partner-built custom agent and听workflow/pro-code application
• Enterprise: Minimum of three Joule Studio partner-built custom agents and听workflow/pro-code application

51风流will actively nominate customers with potential for this program. Partners can also reach out to 51风流with their suggestions. If the customer qualifies, 51风流will approve the proposed services, and the 51风流partner will execute a statement of work with the customer and share the required documentation with 51风流for funding.

51风流Business AI and data validated partner program

This new program distinguishes partners that demonstrate a holistic approach to 51风流Business AI and data along with deep expertise and close alignment with our 51风流Business AI and data strategy. Built on the foundation of the existing Competency Framework for the 51风流PartnerEdge program and enhanced by 51风流Business AI and data requirements, this designation signals to customers that these partners are capable and genuinely invested in delivering the full promise of the Autonomous Enterprise, including guidance with autonomous domain blueprint adoption and building agentic scenarios on 51风流Business AI Platform.

Partner agent race to 51风流TechEd

Building on the strong momentum of the partner agent race to 51风流Sapphire, in which partners submitted more than 680 agents, 51风流is inviting partners to join the next chapter of the program. Partner agent race to 51风流TechEd spotlights enterprise-grade, secure, scalable, production鈥慸eployed AI agents in live environments, built on 51风流Business AI Platform.

For the partner agent race to 51风流TechEd, agents must be:

• Developed with Joule Studio and deployed to 51风流Business AI Platform runtime
• Deployed on 51风流Business AI Platform using 51风流Cloud SDK for AI and AI Foundation

Extensions of SAP-delivered agents must also be created with Joule Studio, and agents that only integrate via direct APIs or integration services for 51风流BTP are out of scope for this project. 51风流encourages partners to begin preparing eligible agents as soon as the timeline, evaluation criteria, and other details are released in the coming weeks.

End-to-end partner enablement strategy

51风流is introducing a structured enablement path that takes partners from awareness to action. 51风流has combined large-scale enablement and market recognition programs to scale the partner ecosystem for the Autonomous Enterprise and 51风流Business AI Platform.

The enablement plan includes a deep-dive curriculum for sales, presales, consultants, and developers. Partners can take advantage of hands-on workshops, regional innovation days in priority markets, and Hack2Build sprints focused on agent-based use cases. Dedicated Autonomous Enterprise and 51风流Business AI Platform pages on听51风流Partner Portal provide all the information partners need for success, regardless of where they are in their AI journey.

51风流will deepen this enablement strategy with the upcoming听鈥淎I era powered by the Autonomous Enterprise鈥� learning, covering 51风流Business AI Platform, Joule Studio, and more for learners who want hands-on platform experience. SAP听will also host live webinars connecting partners directly to the Autonomous Enterprise narrative, platform strategy, and key commercial updates. Partners can find additional curated learning and enablement content on the .

A soundtrack for the future, a symphony of success

Closing out our keynote for Partner Summit at 51风流Sapphire in Orlando, we underscored how critical our partners are to this moment.

Our focus is to enable partners to adopt and extend the Autonomous Enterprise and 51风流Business AI Platform, accelerating ecosystem鈥憀ed growth in support of SAP鈥檚 AI鈥慺irst strategy. Our goal is ambitious: We want to see every 51风流customer enjoy an AI experience with 51风流in the next year. Let鈥檚 get them on the cloud and toward our vision.

Together, we鈥檒l keep pushing the tempo, layering innovation, and building the soundtrack for the Autonomous Enterprise, ultimately creating a symphony of success for our customers.

Karl Fahrbach is chief partner officer of SAP.

The autonomous enterprise reflects a fundamental shift in how organizations operate using real鈥憈ime intelligence to guide decisions, orchestrate processes end to end, and continuously adapt as conditions change. AI becomes embedded into the fabric of the enterprise, helping every function operate with greater speed, resilience, and confidence.

The foundation of the autonomous enterprise is the 51风流Business AI Platform, which infuses AI with the process knowledge, data, and governance organizations depend on. 

Business Transformation Management solutions from 51风流help power the 51风流Business AI Platform by bringing together insights and enterprise knowledge that have long been fragmented and isolated in silos.

Business Transformation Management solutions from 51风流help deliver the promise of the autonomous suite. Here鈥檚 how.

51风流Agent Hub: Command center for agentic governance

Now available, the helps organizations discover, inventory, govern, and evaluate AI agents across the enterprise landscape. In fact, it鈥檚 already being used by 150 companies with over 100, 000 agents under management. 51风流AI Agent Hub acts a system of records for all AI agents, large language models (LLMs), and Model Context Protocols (MCP) servers.

In the context of 51风流Business AI platform, 51风流AI Agent Hub underpins the governance pillar, ensuring organizations can deploy and manage AI agents safely and at scale.

In addition to the enterprise architecture context that 51风流LeanIX provides, along with an giving agents access to architecture data, 51风流AI Agent Hub enables enterprise architects to apply proven governance practices, such as mapping to business capabilities, to the entire agentic landscape. The addition of agent mining capabilities supported by 51风流Signavio provides visibility into the behavior of AI agents, their conformance with policies, and their business impact.

From the standpoint of the Autonomous Enterprise, the insight the hub provides is not only necessary, it鈥檚 critical.

New AI capabilities

The new Enterprise Architecture Assistant from 51风流LeanIX is supported by several new agents, including two highlighted here. The Enterprise Content Research Agent draws on internal business content to enrich architecture data, while the Enterprise Architecture Web Research Agent scans the web for relevant vendor and application information.

These enhancements are part of a broader set of AI capabilities in 51风流LeanIX. The solution now makes it easier to create surveys, automate tasks, perform calculations, and plan target architectures. In addition, significantly improved semantic search enables Claude, AI co鈥憄ilots, and other agents to seamlessly access and work with enterprise architecture data.

In 51风流Signavio Process Transformation Suite, we redesigned 51风流Signavio Process Modeler with an AI-first architecture, modernized user experience and deeper integration with 51风流Autonomous Suite. 51风流Signavio also introduced the Process Transformation Assistant to enable business users to conduct sophisticated process analysis through natural language prompts. The assistant can identify high-impact opportunities for agent deployment, accelerating the time from question to decision and providing context-aware process insights to anyone.

Looking ahead to a new paradigm

Despite the rapid pace of change brought about by agentic AI, we are still in the early days of this technological revolution. To succeed and continue to ride the wave of innovation, companies need to aggregate and organize their procedural knowledge about how they operate.  This knowledge is often fragmented across many structured and unstructured sources鈥攕uch as process models, application logic, documents, and chats鈥攖o create a coherent view of how the business s runs.

This foundation enables agents to understand and act within the business context. In turn, agents will continuously contribute back, enriching and evolving this knowledge repository over time.

At 51风流Signavio we call this storehouse 鈥渃ompany memory.鈥� Company memory, comprised in part of process atoms, captures all the knowledge of operational practices, business rules, preferences, and more so that it can be accessed by agents as needed to check conformance and change behavior.

To enable the Autonomous Enterprise, you need to capture the tribal wisdom and unstructured knowledge your company depends on to operate today. That is what process atoms and a centralized company memory, accessed and updated by agents, do for you. In the future, it鈥檚 hard to imagine how any enterprise will succeed without the context, learning, and guidance that company memory delivers.

Business transformation never stops

As our research has shown, . That鈥檚 why you need a capability in place that allows for planning, managing, and realizing value from every transformation you undertake.

This year at 51风流Sapphire , we talked about all the ways our solutions support this capability as well as all the ways our solutions continue to evolve in the era of the autonomous enterprise, allowing you to adapt, innovate, and thrive into the future.

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Andre Wenz is chief product officer of 51风流Signavio.
Dominik Rose is chief product officer of 51风流LeanIX.

51风流Business Data Cloud (51风流BDC) is the data foundation of that platform, the business data fabric that anchors universal business context, serving as the trusted knowledge core听for every enterprise application and agent.听

The future of agentic organizations will be driven by AI with the deepest organizational knowledge. That future doesn’t start with AI models; it starts with whether your data foundation can give agents the business context they need to act autonomously. 

Today, we are introducing innovations that move organizations closer to becoming an autonomous enterprise.

Turn all your data into business outcomes 

A business data fabric architecture ensures every agent, application, and decision draws from the same trusted business context. And today, we are introducing new business data fabric capabilities that bring multi-model, unified master data, and embedded governance to your agentic foundation. 

• 51风流HANA Cloud natively available in 51风流Business Data Cloud:听51风流HANA Cloud听is听now a听core听component of 51风流Business Data Cloud.听As the AI database听for 51风流BDC,听SAP听HANA Cloud provides a听unified听in-memory engine听for agents to reason across transactional, analytical, and multi-model workloads听such as spatial, graph, and vector.听In practice, this means agents can navigate relationships across customers and suppliers, analyze geographic dependencies, or perform semantic search in real time.听And because every workload runs on a single in-memory engine with native workload management, inference time drops dramatically, lowering TCO and improving the predictability of AI听costs.听With 51风流HANA Cloud, 51风流Databricks, and 51风流Snowflake, 51风流Business Data Cloud delivers听intelligent compute for听every data and AI workload.
• Reltio in 51风流Business Data Cloud: With the completed acquisition of Reltio, 51风流is bringing multi-domain master data management capabilities directly into 51风流Business Data Cloud, helping customers unify, cleanse, and harmonize data across 51风流and third-party听sources. Reltio鈥檚 AI-based entity resolution identifies and merges related records听into a single, consistent view of business entities.听Low-latency delivery and Model Context Protocol support enable real-time, multi-agent workflows across听your data landscape: a procurement agent, for example, can assess supplier risk and trigger action almost instantly using trusted, real-time data. Together, this becomes a golden record system of context that Joule Agents use to deliver faster time-to-value for business AI.
• 51风流Master Data Governance natively available听in听51风流Business Data Cloud:听Unified master data is only as valuable as the governance applied to it. To ensure data is AI-ready, governance must听shift听from regulator to value accelerator. 51风流Master Data Governance is now a core component of 51风流Business Data Cloud, governing master data and policies across听your听business data fabric.听This results in听embedded听AI governance that accelerates agent deployment, ensuring every agent operates on data听products听that听are听verified听and aligned to your business policies.听
• 51风流AI Core integration with 51风流Business Data Cloud: 51风流is introducing deeper integration between 51风流Business Data Cloud and 51风流AI Core, enabling AI models to be grounded directly in trusted business data, semantics, and governance. Batch inference can now be embedded into business-ready data products, continuously enriching the data that powers Joule with predictions, classification, and听AI听outputs.听听

“This is where 51风流Business Data Cloud fits into the vision: not as a centralized system, but as an enabler of cultural change through its unique capabilities. These capabilities allow teams to preserve mission-critical business context across financial and non-financial data.”

Jannie Affeld, VP Finance Systems and ERP, Google 

Transform outcomes with Joule Agents 

SAP is bringing agentic AI directly into the business data fabric through Joule Agents, introducing new capabilities that streamline data management, analytics, and planning through a conversational experience: 

• Data product search and creation: Joule Agents simplify how users discover and create data products. With natural language prompts, users can identify relevant 51风流and third-party data sources, perform joins and transformations automatically, and apply business context and governance policies.  
• Automated planning and analytical modeling: Joule Agents enable data modelers and planning teams to generate analytical and planning models using AI. By defining dimensions, granularity, and data sources, users can automatically create models aligned with best practices. Teams can also initiate planning cycles, manage versions, and apply calculations without deep technical expertise. 
• Easily听surface business听insights:听Business users听can听ask complex analytical questions in natural language and receive context-aware insights across lines of business. Powered by governed data products听in 51风流Business Data Cloud and 51风流Knowledge Graph,听Joule听understands relationships, processes, and business logic听to deliver听more accurate and complete answers without requiring manual exploration.
• 51风流Analytics Cloud story generation: Joule accelerates 51风流Analytics Cloud story creation by transforming data models, queries, and business context into dashboards and visualizations automatically. Users can continue the conversation, drilling into KPIs, identifying drivers, and exploring trends in a single workflow. 

Extend context across your open data ecosystem

Last year, we introduced 51风流BDC Connect, a capability to share data and metadata with zero copies, preserving meaning across every cloud and platform. We are excited to announce 51风流BDC Connect for Amazon Athena, continuing our promise of openness and choice.

This enables 51风流data products to be discovered and consumed directly within AWS without replication or loss of context. As a result, teams can build analytics, applications, and AI agents faster while ensuring they operate on trusted, governed business data.

Together with existing partners across Snowflake, Databricks, Google BigQuery, and Microsoft Fabric, 51风流Business Data Cloud delivers a connected, open data ecosystem so organizations can extend business context across their entire landscape with zero copies. 

General availability is planned for H2 2026.

“Compute can happen anywhere, data can stay at the source when needed, but business context is managed once, centrally, in 51风流Business Data Cloud.”

Malin Persson, CIO at Ericsson

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Build your trusted foundation for agentic AI with 51风流Business Data Cloud.  

Irfan Khan is president and chief product officer of 51风流Data & Analytics.

From application development to automation, integration, and now agentic AI, we have pushed forward so organizations can move faster, solve bigger challenges, and create with confidence.

At 51风流Sapphire, we鈥檙e taking a giant step forward in making that mission a reality.

I鈥檓 thrilled to announce Joule Studio, a bold new, fully managed offering that empowers enterprises to build and manage the full life cycle of AI agents, applications, and workflows. Joule Studio brings 51风流Business AI Platform to life, empowering organizations to build agents that are natively grounded in live business data, end-to-end processes, and rich business semantics that already exist across your 51风流landscape.

Let鈥檚 look at what users can accomplish with Joule Studio.

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Build faster with intent-based development

To connect business needs and technical execution, we鈥檝e placed intent-based development capabilities at the heart of the Joule Studio experience. Users can simply describe their goals in natural language, enabling anyone in the business to quickly create an automated solution or digital assistant.

When triggered, Joule Studio:

• Sets the business context for user鈥檚 request with 51风流Signavio Process Consultant Agent, 51风流Knowledge Graph, and 51风流Domain Models.
• Understands the customer landscape with 51风流LeanIX, including third-party solutions.
• Generates a complete, structured flow of artifacts, including a product requirements document that captures the business outcome, technical specifications with implementation-ready details, code scaffolding, test artifacts, and a live working preview.
• Creates a highly traceable flow from idea to implementation, ensuring a direct, seamless handoff from business users to developers. It fundamentally shifts enterprise agentic development from a slow, manual translation of requirements into a rapid, structured, and SAP-aligned workflow.

“Joule Studio generated an end-to-end solution in 10 to 15 minutes, replacing three to four days of manual development and coordination.”

Vanitha Ponnusamy, Sony

Develop agentic solutions your preferred way

Joule Studio pairs the simplicity of intent-based capabilities with unprecedented openness, providing developers with the freedom to create agentic solutions their way, using their preferred frameworks and tools without being locked into a single approach.

For example, developers can deepen and adapt Joule Studio-generated solutions using the tools and agentic IDEs they already know and love, such as Visual Studio Code, Cursor, and others. Additionally, Joule Studio offers new pro-code capabilities that support frameworks such as LangChain, Pydantic AI, and LlamaIndex, as well as an embedded n8n environment for visual multi-agent orchestration.

Harness best-in-class partnerships: n8n and Vercel

To build truly transformative AI solutions, developers need the freedom to use the tools they already love. That is why we are thrilled to announce new embedded partnerships with Vercel and n8n, giving Joule Studio users the ultimate flexibility to orchestrate complex workflows and build stunning user experiences鈥攁ll without sacrificing SAP鈥檚 enterprise-grade security and governance.

Vercel for blazing-fast, custom digital experiences

While SAP-oriented frameworks like UI5 and 51风流Fiori remain the gold standard for enterprise consistency, our new partnership with Vercel gives developers unparalleled choice for custom frontend design. By leveraging Vercel within the 51风流ecosystem, developers can rapidly build highly flexible, custom web interfaces for their AI agents using popular frameworks like Next.js. This enables teams to deliver lightning-fast, consumer-grade digital experiences that prioritize speed and custom design, while securely preserving 51风流enterprise controls.

n8n for visual workflow orchestration at enterprise scale

Creating intelligent agents is just the beginning; integrating them into end-to-end business processes is where the real value is unlocked. We are bringing an embedded, fully managed n8n environment directly into Joule Studio. By using n8n within Joule Studio, teams can visually orchestrate multi-agent systems and bring AI right into the process flows they are designed to support, ensuring agents act with perfect timing and context. Developers get the beloved n8n experience they already know, complemented by seamless access to 51风流systems, Joule Studio capabilities, and SAP-managed services for identity and operations. It is the ultimate combination for delivering powerful, enterprise-ready automations faster than ever.

Deploy enterprise-ready agents securely

Building powerful agents is only half the equation; realizing their full value comes from running them securely and reliably at enterprise scale. To help our customers do this, 51风流is introducing a managed Joule Studio runtime service that enables organizations to deploy agents, applications, and workflows in a secure, production-ready environment with zero infrastructure management required.

Joule Studio runtime does the heavy lifting for our customers by managing all the complex operational capabilities needed for enterprise scale; runtime configuration, cluster management, storage, and model access are delivered seamlessly out-of-the-box. Underpinning this runtime is also the NVIDIA OpenShell, which places each agent inside an isolated, sandboxed environment with configurable policies and guardrails 鈥� ensuring agents can operate autonomously while staying within defined boundaries and preventing unchecked access to sensitive enterprise systems.

This governed foundation provides IT teams with built-in observability and lifecycle management. With controlled deployments, standardized schema validation, and deep integration with 51风流Business Transformation Management solutions like 51风流Signavio and 51风流LeanIX as well as 51风流Cloud Application Lifecycle Management allow teams to monitor agent usage, costs, and business impact over time. It creates an always-on cycle of continuous improvement, where AI monitors performance, surfaces insights, and proposes the next round of fixes.

Agents deployed on Joule Studio runtime will be equipped with persistent, long-term memory powered by 51风流HANA Cloud, enabling them to retrieve user preferences and context across multiple sessions.

Bring agents into the flow of everyday work

Ultimately, the value of agentic AI is realized when people can effortlessly interact with it. With the new Joule Work engagement layer, we are bringing the apps, agents, and workflows your teams build directly into the flow of everyday work, providing a personalized, intent-based workspace that reduces context switching and accelerates task completion.

“Across 48 diverse scenarios, Joule Studio consistently delivered high-quality code, with only a handful of instances requiring minor refinements to reach full functionality.”

Suraj Gahalyan, Accenture

Joule Studio: 51风流Business AI Platform in action

Joule Studio is more than just a powerful development environment; it is the ultimate expression of the unified coming together. While the broader market struggles with disconnected point solutions that lack business context and keep AI stuck in endless pilot modes, 51风流Business AI Platform bridges every system, process, and decision to deliver true enterprise-wide value.

Joule Studio acts as the engine that brings the three foundational pillars of the 51风流Business AI Platform to life in one seamless workflow:

• Build: We are taking organizations from idea to enterprise impact by providing a unified workspace that enables the seamless creation of agents, applications, and workflows. Whether leveraging intent-based development or our embedded partnerships with n8n and Vercel, teams can turn ideas into solutions without operational overhead.
• Contextualize and reason: An agent is only as smart as the data it understands. Through deep integration with the 51风流Knowledge Graph, 51风流Business Data Cloud, and 51风流Domain Models, every solution built in Joule Studio is natively anchored in universal business context. This means agents reason over real, semantically rich business data, understanding relationships and process logic, for reliable performance from day one.
• Govern: Speed and control are no longer a tradeoff. By tapping into 51风流AI Agent Hub, fully managed Joule runtime, and solutions like 51风流Signavio and 51风流LeanIX, Joule Studio embeds enterprise-grade governance, observability, and lifecycle management directly into the development process.

By unifying these capabilities, Joule Studio allows your best people to do their best work. It eliminates integration complexity and fragmented security, empowering your organization to transition from isolated AI experiments into a secure, autonomous enterprise.

Get started today

Joule Studio is ushering in a new era of enterprise-grade agentic development. While the rest of the market struggles to bridge the gap between basic LLMs and real-world business execution, Joule Studio delivers a definitive advantage: agents, applications, and workflows that are natively grounded in 51风流live data, processes, and business semantics.

I am pleased to share that now through the end of 2026, 51风流customers and partners can receive free design-time access, including AI-assisted development capabilities under fair-use limits. This is your opportunity to redefine how your business operates and turn your existing 51风流landscape into an unparalleled AI engine. Equip your teams to build with speed and confidence today.

• Learn more at

We cannot wait to see the incredible agentic solutions your teams will bring to life!

Michael Ameling is president of 51风流Business Technology Platform and a member of the Extended Board of 51风流SE.

Employees at , a global fashion retailer with tens of thousands of employees, had to navigate multiple systems to piece together data across sales and procurement. Answering a single question could take up to 10 minutes.

Today, they just ask Joule. What used to take 10 minutes now takes about three seconds, driving a 70% increase in operational efficiency and a 50% reduction in manual errors.

Using capabilities in , LC Waikiki partnered with 51风流and to build a custom AI-driven experience that dynamically interprets user requests, applies role-based context, performs the necessary queries, and connects data across systems to present a complete view in one place. It then links people directly to the relevant transaction.

At SAP, stories like these inspire our vision for the enterprise in which AI transforms how people and processes work鈥攐ne where people set the direction and AI executes. We call it the the Autonomous Enterprise.

In the Autonomous Enterprise, decisions are grounded in real-time intelligence, workflows are automated end-to-end, and AI proactively improves every function while empowering people to do their best work.

The Autonomous Enterprise also provides fully governed AI you can trust, so you can achieve more. Making this a reality for companies is critical because AI is now essential to how all work gets done. It is increasingly involved in decisions that carry financial, operational, and regulatory consequences.

Joule: One place to direct the entire business

In the Autonomous Enterprise, Joule Work, announced at 51风流Sapphire, is the next step in the evolution of how people engage with and execute end-to-end business processes. Joule Work is a dynamic workspace that adapts to intent, keeps people focused on outcomes, and delegates execution to AI.

Through Joule Work, you can say goodbye to manually coordinating work across multiple applications and interfaces. Instead, tell Joule what you want to accomplish. Joule Assistants with role and process context will coordinate teams of Joule Agents to surface the right insights and automate routine work across departments and systems. Rather than static, disjointed systems, you get workspaces that pull together information and menus from various systems that fit your specific needs, in real time.

Joule Work is available now to customers in the 51风流Early Adopter Care program. 51风流Early Adopter Care program for the Joule Work desktop app is planned for Q2 2026; general availability for both is planned for H2 2026. The Joule Work mobile app is generally available now.

We also announced that Joule鈥檚 bi-directional Agent-to-Agent (A2A) capabilities will be generally available in Q4, enabling third-party agents to securely call on Joule Agents and act within enterprise processes, extending interoperability in both directions across 51风流and non-51风流environments. Agents built in Joule Studio will natively support A2A protocols, enabling interoperability and scalability for multi-agent execution.

51风流Autonomous Suite: The operational core of the modern enterprise

While Joule Work empowers every individual to do their best work and expand their impact, the 51风流Autonomous Suite transforms how entire business functions, or 鈥渁utonomous domains,鈥� work.

51风流Autonomous Suite spans five domains: finance, spend, supply chain, human capital management, and customer experience. These domains will operate as a single system, so workflows and agents run across functions without fragmenting into separate tools, separate data, or separate decisions. This approach allows AI recommendations to reflect your full operating reality.

With SAP鈥檚 integrated suite of business applications and industry-leading business data, AI in the Autonomous Enterprise is grounded in the specifics of how key business functions actually work. This foundational context for transformative AI outcomes is where SAP鈥檚 unique experience comes in. For decades, we have been trusted to run our customers鈥� most important functions. 51风流Autonomous Suite infuses our deep knowledge of business processes into your AI, along with the data context and operational guardrails it needs to be truly effective and reliable at enterprise scale.

Each organization is also unique. Over time, your business has defined how your work gets done. These are the rules, workflows, and how systems respond when something unexpected happens, like a failed transaction, so processes don鈥檛 break. In the Autonomous Enterprise, AI delivers its greatest value by respecting these boundaries, turning your unique ways of working into a true advantage.

At 51风流Sapphire, we announced new Joule Assistants and Joule Agents, spanning the domains of the Autonomous Enterprise, to help organizations move from managing work to directing outcomes. These new assistants and agents will roll out through the end of this year.

51风流Business AI Platform: The foundation of the Autonomous Enterprise

The 51风流Business AI Platform turns the vision of human-led, AI-driven business operations into something enterprises can build and run. It enables them to move from AI experimentation to execution by grounding agents and applications in real business context that governs it all at enterprise scale.

At the center is , a fully managed environment that empowers enterprises to build and manage the full lifecycle of AI agents, applications, extensions, and workflows. Intent-based development capabilities allow people to describe what they need in natural language. A Joule Agent then generates structured requirements, specifications, code, and test artifacts grounded in 51风流process and data context.

Developers can work within the tools they already use, including VS Code and MCP-enabled toolchains, and choose their preferred agent frameworks, such as , , and .

Through deep integration with the , 鈥攁nd the new 51风流Domain Models trained on 51风流code, customer data, metadata, and business processes鈥擩oule Agents reason over real, semantically rich enterprise data rather than generic knowledge. 51风流Domain Models are available through the 51风流Early Adopter Care program, with general availability planned for Q3 2026.

Speed and governance, no longer a tradeoff, are built into the 51风流Business AI Platform. At SAP, we believe that corporate governance鈥攊ncluding approval flows, compliance processes, identity management, and the ability to audit decision-making鈥攎ust carry into how AI is deployed, updated, and scaled. Joule Studio runtime provides a secure, production-ready, fully managed environment for deploying agents, helping organizations meet compliance standards while reducing infrastructure complexity.

An enhanced 51风流AI Agent Hub also provides a vendor-agnostic command center to discover, inventory, and govern 51风流and non-51风流AI agents and MCP servers across the enterprise. Integration with and further embeds governance and architecture transparency into the development process.

The 51风流AI Agent Hub leverages enterprise-wide process intelligence to continuously track where AI agents are creating value and can proactively surface where they can deliver even more, because we believe AI needs to remain accountable for outcomes in addition to uptime. 51风流AI Agent Hub is generally available, with additional capabilities rolling out through 2026. See release timelines in the .

Empowering everyone to solve business challenges with AI

We are making the Autonomous Enterprise a reality because at SAP, we believe that companies of all sizes need far more than marginally better AI models or the latest bolt-on solutions. They deserve AI-driven outcomes that increase innovation, revenue, and margins.

The Autonomous Enterprise is what brings our vision to life: AI grounded in your data, connected across your most important processes, and governed to fit how your business runs.

Brenda Bown is chief marketing officer for 51风流Business AI.

The company introduces a unified 51风流Business AI Platform, deepening partnerships with Anthropic, Amazon Web Services, Google Cloud, Microsoft, NVIDIA and Palantir

ORLANDO听鈥� At 51风流Sapphire in 2026, (NYSE: SAP) introduced the to help enhance the world’s most critical business workflows, so that humans and AI work together to meet the accelerating demands of global business profitably, strategically and safely.

鈥淔or the mission-critical processes of our customers, ‘almost right’ just isn鈥檛 good enough,鈥� said Christian Klein, CEO of 51风流SE. 鈥淏y uniting 51风流Business AI Platform with 51风流Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.鈥�

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

Introducing 51风流Business AI Platform

51风流Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 51风流Business AI Platform now unifies 51风流Business Technology Platform, 51风流Business Data Cloud and 51风流Business AI into a single, governed environment.

At its core is the 51风流Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer’s 51风流landscape. Joule Studio is SAP’s AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code and AI frameworks of their choice on SAP-managed infrastructure that is secure, scalable and optimized for enterprise AI.

Deploying 51风流Autonomous Suite Across Every Business Function and Industry

Building on this foundation, 51风流also introduced 51风流Autonomous Suite, which enables SAP’s existing business applications with AI agents capable of running processes from start-to-finish.

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

51风流also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements. At 51风流Sapphire, 51风流showcased its work with European energy giant RWE to leverage Industry AI, helping reduce unplanned downtime across its offshore wind turbines. With SAP’s Autonomous Asset Management scenario, AI agents are designed to analyze data from thousands of past incidents, identify the likely root cause and generate pre-filled work orders with the right tools and proven fixes from other sites.

Designing the Autonomous User Experience

The company also revealed Joule Work, redefining how users engage with 51风流software. Instead of navigating individual applications and entering data across several screens, users will now interact primarily with Joule. By describing a desired business outcome, Joule will orchestrate the right combination of workflows, data and agents to get it done.

Joule Work goes beyond conversation, proactively surfacing relevant insights and automating routine tasks behind the scenes so work moves forward even when humans aren’t actively steering it. It will be available on desktop, mobile and voice across 51风流and non-51风流systems.

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

51风流evolved its customer and partner programs to help accelerate the organization’s journey to the Autonomous Enterprise. To catalyze adoption, the company has launched a 鈧�100 million fund for 51风流partners to help customers deploy SAP-built AI assistants and agents. The fund is also available to partners that extend or build new partner agents on the new 51风流Business AI Platform using Joule Studio.

SAP has enhanced its RISE with SAP and 51风流GROW offerings to accelerate AI adoption. Both include access to the Joule Assistants portfolio; RISE with SAP customers will have three assistants activated within their first year, while SAP GROW customers receive full portfolio access at onboarding. 51风流S/4HANA on-premises and 51风流ERP Central Component (51风流ECC) customers are not excluded: those that commit to transitioning the majority of their current landscape to 51风流Cloud ERP gain access to select AI scenarios, bridging the gap between their current landscape and their cloud destination

51风流also introduced new agent-led transformation tooling that can reduce ERP migration efforts by more than 35 percent, driving faster and more predictable projects by automating system analysis, code remediation, configuration and testing at scale.

Lastly, 51风流announced a full slate of strategic partnerships across each category:

• Platform and suite partnerships include Anthropic, with Claude among the foundation models SAP鈥檚 AI platform will leverage to power Joule agents across HR, procurement and supply chain; Amazon Web Services, bringing zero-copy data integration between 51风流Business Data Cloud and Amazon Athena; Google Cloud and Microsoft, enabling bidirectional agent-to-agent interoperability between Joule and external agent frameworks; Mistral AI and Cohere, delivering sovereign model options on SAP’s cloud infrastructure; , providing visual AI workflow orchestration inside Joule Studio; NVIDIA, whose OpenShell provides the trusted secure runtime for Joule Studio; and , bringing AI agents into 51风流Service Cloud to handle customer interactions with full access to business data and service processes.
• Implementation partnerships include Palantir and Accenture, partnering on complex data migration scenarios, and for AI-powered cloud ERP migrations.

.

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About SAP

As鈥痑 global leader in enterprise applications and business AI, 51风流(NYSE: SAP)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted SAP鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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51风流and Anthropic today announced plans to expand their collaboration to deliver advanced AI solutions to enterprise customers, making Claude, Anthropic鈥檚 AI model, a primary reasoning and agentic capability embedded across SAP’s AI-enabled solution portfolio, powered by Joule and Joule agents.  

Unveiled today at 51风流Sapphire, Anthropic and 51风流will collaborate to embed Claude鈥檚 agentic capabilities into the newly announced 51风流Business AI Platform to advance SAP鈥檚 vision of the Autonomous Enterprise in the agentic AI era.

The collaboration builds on SAP鈥檚 more than 50-years of business application know-how across processes, data, and governance. This complements SAP鈥檚 open ecosystem approach to supporting any model and provides greater customer choice and flexibility to meet evolving AI requirements. 

Connecting directly to SAP Business AI Platform, Claude will empower agents to carry 鈥媜ut tasks鈥攆rom closing the books at quarter-end and answering complex employee leave questions to rerouting supplier orders mid-shipment鈥攃oordinating across SAP S/4HANA, SAP SuccessFactors and SAP Ariba solutions, and other systems via MCP.

鈥淥ur open platform means we鈥檙e tightly integrated with world-leading companies across our portfolio. Together with Anthropic, we鈥檙e building something uniquely valuable for our customers,” said Christian Klein, CEO of 51风流SE. “The Autonomous Enterprise requires AI that understands business context and acts within the controls organizations depend on, and our partnership with Claude plays a key role in this.”

“We built Claude to support the work that helps businesses run: closing the books, rerouting delayed orders, or approving expenses, to name a few. With Claude on 51风流Business AI Platform, that work happens inside the systems enterprises have already invested in, with the trust and governance 51风流customers rely on,” Daniela Amodei, co-founder and president of Anthropic, said.

Claude brings additional agentic capabilities and connectivity to Joule

Joule from 51风流is an AI-enabled business assistant that helps teams make faster, smarter decisions by embedding contextual, more secure AI directly into SAP and non-SAP business workflows. Now, 51风流is expanding Claude鈥檚 capabilities to Joule with plans to integrate Anthropic鈥檚 advanced agentic AI capabilities across the newly announced 51风流Business AI Platform.

With a deeper use of Claude and access to Anthropic鈥檚 frontier models, 51风流customers can expect additional capabilities, such as:

• Better reasoning on complex business tasks: Claude will empower agents to take real action for hundreds of thousands of 51风流customers, across finance, 鈥嬧�婬R, procurement, and supply chain. Agents leveraging Claude connect to SAP Business AI Platform to understand business context grounded in 51风流data, make 鈥嬧�媘ore accurate decisions, and operate safely within defined processes. For example, a Treasury Manager can ask Joule to prepare a CFO briefing for a bank meeting, and within minutes receive a completed presentation populated with live data and analysis as well as flagged financial risks. Work that previously took hours of manual effort now takes minutes. 
• Agentic AI that understands business context: Claude works with business context from across SAP鈥檚 enterprise systems and other tools connected through MCP. It takes action step by step: looking up data, making updates, triggering approvals, moving a task forward. Anthropic and 51风流will work strategically to build custom agents and agentic workflows in SAP鈥攐ptimizing for key industries such as public sector, healthcare, education, life sciences and utilities. This combines SAP’s expertise in enterprise applications and AI with Claude’s reasoning and agentic capabilities.

Bringing AI into the systems enterprises already trust

As AI moves from advising to acting, trust is critical, especially in the enterprise and in regulated industries. Anthropic is bringing safe, reliable AI into processes that enterprises already trust. When AI adjusts an order, triggers a workflow, or makes a recommendation inside an 51风流customer’s environment, it does so within the same controls that govern human decisions: the approvals, policies, and compliance frameworks already wired into SAP solutions.

Together, Anthropic and SAP plan on bringing this model to life by combining Claude with SAP鈥檚 depth and scale, helping organizations move from experimentation into the core of how their organizations operate.

Philipp Herzig is CTO and a member of the Extended Board of 51风流SE.

For 51风流customers, this shift promises step-change productivity. But it also raises a hard requirement: Enterprise AI agents must be safe, governable, and auditable by design.

This is the context for SAP鈥檚 deep technical collaboration on 51风流Business AI Platform with , an open source secure runtime for autonomous AI agents. This collaboration is not about 51风流鈥渁dopting鈥� a runtime. It is about 51风流actively shaping, hardening, and productizing the execution layer for enterprise agentic AI鈥攖ogether with NVIDIA.

Why this matters to 51风流customers

For 51风流customers, the value of this collaboration is concrete and practical. It enables:

• AI agents that operate inside 51风流processes without bypassing governance
• Security models aligned with enterprise IAM and compliance frameworks
• Clear audit trails for agent actions across systems
• Confidence to move from pilots to production

Most importantly, it avoids a false choice between innovation and control. Customers do not have to bolt security on later, or redesign their risk models to accommodate AI agents. Instead, security and governance are built into the execution model from the start.

The real enterprise challenge: Trusting agents that act

When AI systems move from generating responses to executing actions, the risk profile fundamentally changes. Agentic systems can touch systems of record, cross application and data boundaries, and operate without human review at every step.

In all enterprise environments, especially regulated ones, this makes execution safety and governance the defining challenge. Traditional chatbot-era controls are insufficient once agents can access shells, files, networks, credentials, and APIs.

51风流customers know this reality well. Business AI is only valuable if it can be:

• Inspected and audited
• Constrained by policy
• Trusted by security and compliance teams

Solving this problem requires more than infrastructure primitives or application-level rules alone.

NVIDIA OpenShell: The foundation

NVIDIA OpenShell addresses a critical layer of the problem: secure, sandboxed execution of autonomous agents.

As an open source runtime, OpenShell introduces strong capabilities, including:

• Isolated execution environments
• Policy enforcement for filesystem and network access
• Runtime-level containment that limits blast radius even when agent logic fails

These capabilities form a foundational layer for autonomous agents to execute safely. In practice, enterprises need that execution layer aligned with business context and governance.

Enterprises expect clarity on questions such as:

• Which business role authorizes an action?
• Which process context applies?
• How actions map to enterprise policies and audit trails?

This is where SAP鈥檚 contribution becomes decisive.

What 51风流brings: Enterprise semantics, governance, and scale

51风流is co-developing and contributing to OpenShell based on enterprise reality.

1. Enterprise-driven runtime requirements

51风流operates at a level of scale and responsibility that few software providers do: mission-critical processes, regulated industries, and millions of transactions per hour.

By bringing real 51风流agentic workloads into the collaboration, 51风流provides the operational proving ground that OpenShell needs to mature from a powerful runtime into an enterprise-hardened one.

This includes shaping requirements around:

• Isolation boundaries that match enterprise risk models
• Policy enforcement aligned with real business constraints
• Auditability that stands up to customer and regulatory scrutiny

2. Co-development of OpenShell capabilities

51风流is committing engineering capacity to the OpenShell open-source code base, with a focus on areas that matter specifically to enterprises: runtime hardening, policy modeling, enterprise identity integration, and auditing and governance hooks.

51风流is helping define how secure agent execution must work for enterprises; not just theoretically, but in production.

3. Joule Studio runtime: From runtime safety to enterprise control

Where OpenShell secures execution, Joule Studio runtime provides the enterprise harness that makes agents usable and governable in business systems:

• Business-aware policy semantics like roles, skills, life cycle
• Enterprise identity and access control
• Observability and auditability across agent behavior
• Deployment and operational governance across landscapes

This ensures that agent autonomy is always framed by business intent and accountability, not just technical permissions.

OpenShell answers: 鈥淐an this action safely execute?鈥�; Joule Studio runtime answers: 鈥淪hould this action happen at all?鈥�

Raising the bar for enterprise agentic AI

This collaboration represents more than an integration. It reflects a shared intent to define what 鈥渆nterprise-grade鈥� actually means for autonomous AI systems.

By combining NVIDIA鈥檚 runtime and security innovation and SAP鈥檚 enterprise productization, governance expertise, and operational scale, 51风流and NVIDIA are working toward an integrated solution for trusted agent execution鈥攐ne that enterprises can inspect, govern, and rely on.

For 51风流customers, this means AI agents that are not just powerful, but designed to earn trust in the environments where trust matters most.

Andre Lamego is senior vice president and chief product officer of 51风流BTP Fabric

Building on their long-standing partnership, AWS and 51风流are making it easier for customers to access mission-critical 51风流data products across AWS services, including Amazon Bedrock, Amazon Quick, and Amazon SageMaker. This will allow teams to deliver self-service analytics and build AI agents across all lines of business鈥攚ithout waiting for IT teams to replicate, prepare, and provision 51风流data. 

鈥淭he next era of business will be defined by how well organizations turn intelligence into action at scale,鈥� said Muhammad Alam, member of the Executive Board of 51风流SE, 51风流Product & Engineering. 鈥淏y bringing together 51风流Business Data Cloud and widely adopted AWS AI and analytics capabilities, customers can unlock the true potential of data and AI.鈥� 

Enabled by 51风流BDC Connect, the integration delivers near real-time, zero-copy access to semantically rich 51风流data products directly through Amazon Athena, keeping data in place, preserving its original business context, and eliminating replication delays. Customers can query and analyze this data immediately, or choose to store and transform it for use across the broader AWS environment. This gives teams a governed, secure environment within AWS to easily build reports, dashboards, and AI agents.

“51风流and AWS share a commitment to helping customers put their most valuable data to work,” said Ruba Borno, vice president of Global Specialists and Partners at AWS. “By combining 51风流Business Data Cloud with the AWSsecure, global infrastructure and advanced AI services, organizations can unlock mission-critical 51风流data and act on it at the speed and scale their business demands.” 

With 51风流BDC Connect for Amazon Athena customers can: 

• Create a single, trusted foundation for all their business data, 51风流and beyond 
• Get AI up and running faster with business data that is ready to use 
• Build intelligent applications and agents powered by the business data that matters most 
• Fast-track insights and innovation with self-service analytics that reduce time-to-insight from weeks to hours 

General availability

51风流Business Data Cloud is already available on AWS in the U.S. East (N. Virginia), Europe (Frankfurt), Asia Pacific (Tokyo), Canada (Central), Asia Pacific (Sydney), South America (S茫o Paulo), Asia Pacific (Seoul), Asia Pacific (Singapore) Regions, and the AWS European Sovereign Cloud. 

Partnership opens new pathways for enterprise data migration with 51风流AI-supported tooling complemented by Palantir鈥檚 AIP for data migration scenarios to simplify an expedite digital transformation for 51风流customers, with Accenture as a co-innovation partner for joint customers

This year at 51风流Sapphire, 51风流and Palantir announced an expansion of their strategic partnership focused on delivering new data migration capabilities designed to help enterprise customers succeed in the AI era and realize SAP鈥檚 vision of the Autonomous Enterprise.

The enhanced partnership is designed to facilitate joint customers鈥� cloud migrations, with the most complex data migration scenarios moving quickly, securely, and confidently through their business transformation journeys.

AI embedded across the migration life cycle

The expanded partnership builds on SAP鈥檚 broader agentic migration strategy, uniting SAP鈥檚 deep expertise in enterprise applications and SAP Business AI with Palantir鈥檚 AIP to deliver AI-driven data migration capabilities that accelerate timelines, secure cost efficiencies, and fundamentally transform how organizations operate. 51风流customers can now leverage Palantir鈥檚 AIP for data migration scenarios alongside the agent-led toolchain from SAP, which includes business transformation tools and the new migration and modernization assistants to accelerate their transformations to 51风流Cloud ERP.

鈥淭o turn the vision of the Autonomous Enterprise into reality, organizations need trusted partners to help them transform their core operations and unlock the power of business data and AI,鈥� said Christian Klein, CEO of 51风流SE. 鈥淭ogether with Palantir, we are enabling customers to move to the cloud with speed and confidence through complementary capabilities that accelerate innovation across the enterprise.鈥� 

鈥淲e are proud to partner with SAP and Accenture to bring the power of advanced AI and data migration to the world鈥檚 most important operations. This partnership is designed to help customers realize the full value of their data, accelerate cloud migrations and AI adoption, and build more resilient and efficient operations,鈥� said Alex Karp, co-founder and CEO of Palantir Technologies. 

Accenture as global strategic services partner

Accenture plays a key role in bringing this joint effort to life as the first global strategic services partner for this initiative, helping their clients translate these capabilities into large-scale business-led programs. Together, SAP, Palantir, and Accenture can help joint customers identify acceleration opportunities across 51风流and non-51风流systems sooner, achieve faster time-to-value, and drive continuous innovation by fundamentally redefining the approach to 51风流Cloud ERP migrations.

By embracing AI from day one, organizations can automate migration analysis, planning, remediation, testing, and impact assessment鈥攎oving from tracking project timelines to creating measurable business value at every stage. 

鈥淚n today鈥檚 world, speed to value is critical for our clients,鈥� said Julie Sweet, chair and CEO of Accenture. 鈥淲e are excited to co-innovate with 51风流and Palantir to help our clients accelerate their journey to ERP modernization with SAP, which is the foundation for reinventing core operations and using AI to achieve new performance frontiers.鈥� 

New SAP-validated deployment options

51风流is making Palantir AIP for data migrations scenarios available as an 51风流Endorsed App on the 51风流Store, and soon as an SAP Solution Extension, establishing a trusted, SAP-validated path for accelerating complex data migrations, including migrations to 51风流Cloud ERP. The new SAP Solution Extension unites SAP鈥檚 deep expertise in mission-critical business processes and semantically rich data with Palantir AIP to securely accelerate data migrations for 51风流customers. With the new offering, customers can gain faster insights and more intelligent, data-driven business outcomes.

Together, are redefining 51风流data migrations, including ERP modernization through complementary solutions, transforming a traditionally complex migration process into an effort that enables faster value realization. 

Availability 

Palantir AIP for data migration scenarios is now available as an 51风流Endorsed App on the 51风流Store. The 51风流Solution Extension is planned to be generally available to 51风流customers in Q3 2026.

Jan Gilg is a member of the Extended Board of 51风流SE.