Andreas Wendel is very pleased with the outcome: a total of 11,200 visitors explored the 51风流Experience Center at 51风流Sapphire Orlando and Madrid. The self-contained exhibit drew customers, partners, 51风流employees, media representatives, and analysts alike. Across the two identical centers, visitors also joined 123 guided tours.

鈥淭he rush of visitors was so great that, in Orlando, the line at times wrapped all the way around the center, which covers roughly 1,000 square meters,鈥� says Wendel, head of Innovation Experience Services at SAP.

So what was inside the oversized box in the middle of the show floor? What were visitors willing to wait more than an hour to experience?

Sports create an emotional connection

鈥淭his year, our task was to bring the Autonomous Enterprise to life,鈥� Wendel says. 鈥淚t鈥檚 a highly technical topic, and we talk a lot about artificial intelligence, agents, and Joule Assistants.鈥� The team wanted to make tangible what CEO Christian Klein and other members of the Executive Board of 51风流SE introduced and what was demonstrated in sessions.

Planning began six months before 51风流Sapphire, supported by experts from Strategy, Development, and Product Marketing. Over time, more partners, customers, and service providers joined the effort. Wendel estimates that close to 100 people contributed to the concept.

As the narrative thread, the team chose a major sporting event and the theme 鈥淔rom Competition to Collaboration鈥濃�攁 timely fit with the world鈥檚 largest soccer tournament taking place across the United States, Mexico, and Canada this year. 鈥淲ith so many technology discussions at 51风流Sapphire, sports is a topic that resonates with people emotionally,鈥� Wendel says. 鈥淲e used a sports event to show how 51风流solutions help plan and deliver an event of that scale.鈥�

鈥淔or spectators, it鈥檚 an experience. But for a mega-event to run smoothly, all equipment and technologies around a stadium must work,鈥� he adds. 鈥淲e showed how Autonomous Asset Management helps ensure the infrastructure performs on the day of the event.鈥�

A players鈥� tunnel, pipelines, and a robodog

Let鈥檚 take a tour of the 51风流Experience Center with Wendel. We enter through a players鈥� tunnel and arrive in a skybox overlooking an imagined stadium for a major international soccer tournament. The first stop, 鈥淧lan the Game,鈥� focuses on the big picture and shows how 51风流brings AI, data, and applications together to orchestrate every aspect of a major sporting event.

Wendel explains how 51风流solutions support the planning phase: 鈥淲e show how customers can use our finance and planning solutions well ahead of the event. Agents and Joule Assistants help identify developments early and take action to stay within budget.鈥�

His colleague Pranav Avadhanula, solution advisor for Finance and AI, demonstrates this with a real-world scenario. On a large screen, visitors see how Joule Agents can identify the best providers for the event’s security concept in Mexico and simulate different scenarios鈥攊ncluding currency fluctuations between the Mexican peso and the U.S. dollar.

The next station, 鈥淏uild the Stage,鈥� highlights the work that happens behind the scenes before fans cheer. Modernizing a stadium requires precise planning, budget discipline, and seamless execution. 51风流helps orchestrate everything鈥攆rom staffing and travel to procurement鈥攅nabling the venue to be ready on time and on budget, supported by Autonomous Spend, Autonomous HCM, and Autonomous Project Delivery.

Another room focuses on applications that are invisible to visitors鈥攂ut critical. One scenario in particular stands out and was likely the most frequently filmed by visitors: a dog-shaped robot from partner Boston Dynamics moving along a series of pipelines, automatically detecting leaks with sensors. Once identified and analyzed, the system triggers a digital repair order for the maintenance staff responsible.

鈥淲hat resonates strongly is that we don鈥檛 just show digital solutions,鈥� Wendel says. 鈥淲e also demonstrate how embodied AI and robotics can support operations in the future鈥攊deally through customer use cases. These physical elements make 51风流solutions tangible and help reduce complexity.鈥�

Another popular highlight is the 鈥淗all of Fame,鈥� where key customers are honored with their own trophies. 鈥淚n Orlando, we had a tour with a customer. When employees saw their trophy, they cheered and took photos like at a Champions League final. That really showed how much detail went into the experience鈥攊t was simply incredible.鈥�

More than just a jersey

The visit concludes in the fan shop. Under the theme 鈥淢onetize the Moment,鈥� it demonstrates how organizers can generate revenue through merchandise. Visitors scan their 51风流Sapphire badge and order a personalized jersey in one of two colors.

They then watch as a machine printed the jerseys with their chosen name and number. A humanoid robot from partner Aimbo Robotics sorts the finished items onto shelves. Despite high demand, jerseys are ready for pickup about two hours later.

The twist: the jerseys include an NFC chip. 鈥淚f you tap your phone to it, you can access all 51风流Experience Center content again,鈥� Wendel explains. 鈥淪o it鈥檚 not just a jersey鈥攊t extends the experience beyond the event.鈥�

Wendel emphasizes that while the 51风流Experience Center was built for 51风流Sapphire, its elements are reused at other events or in one of the numerous permanent 51风流Experience Centers. Parts of the setup are also stored for reuse. 鈥淪ustainability is very important to us,鈥� he says.

Hard to top

The many months of preparation and the long evenings in the exhibition hall in the run-up to 51风流Sapphire clearly paid off. Asked about the feedback, Wendel concludes: 鈥淥ur concept makes SAP鈥檚 full portfolio and industry strength tangible. This year, many people told us: 鈥楲ast year was already great, but you managed to top it.鈥� And that鈥檚 not easy.鈥�

Experience 51风流innovation firsthand

51风流Experience Centers bring innovation to life through real business scenarios, interactive showcases, and industry-specific storytelling. Across 31 locations worldwide, 51风流connects applications, data, and AI to help turn complex business challenges into tangible solutions.

Interested customers and partners may online, , or get an impression of .

This article was first published on the 51风流employee portal.

Across industries, customers are moving from pilots to production. They are investing in systems that can run pricing, orders, fulfillment, and service end-to-end, with AI actively driving decisions and outcomes. They are not looking for more tools. They are looking for results.

This is where 51风流has a clear point of view. Customer experience (CX) only works when it is connected directly to execution.

51风流Customer Experience is integrated with 51风流Cloud ERP across pricing, order management, fulfillment, billing, and service. AI operates inside these processes using real business data. That means every customer interaction can reflect what the business can deliver.

This is the shift now underway, and it is creating immediate opportunities for partners.

51风流partners are the ones who bring this to life. They take product capabilities and turn them into working solutions that improve conversion, increase fulfillment accuracy, and reduce service cost.

The next wave of growth will be led by partners who move quickly and build on this foundation.

Customer experience is now measured by what gets done

Customer experience is no longer judged by engagement metrics alone. It is judged by outcomes. Customers expect:

• Accurate pricing at the moment of purchase
• Real product availability, not estimates
• Orders that are fulfilled as promised
• Service that resolves issues without repetition or delay

When these things work, the experience works. When they fail, the problem is immediately visible.

AI is increasing the speed of every interaction. It is also exposing execution gaps faster than ever before. If pricing, inventory, or order data are inconsistent, customers see it instantly.

This is why customer experience and execution can no longer be separated.

AI is now driving actions, not just insights

AI is already acting inside key business processes. As seen in the , in 51风流CX today:

• Marketing, content, and campaign assistants can orchestrate segmentation, content creation, and optimization based on live performance signals.
• Commerce, merchandising, shopping, and order management assistants can connect discovery, conversion, and fulfillment to real-time inventory and pricing.
• Sales assistants help guide deal qualification and deal execution by linking pipeline signals to pricing, availability, and fulfillment data.
• Case and service management assistants help automate routine interactions while maintaining full context across orders, entitlements, and history.

These are not future scenarios. These capabilities are available and in use. But they only work when they are connected to trusted business data.

Without that, AI creates errors at scale. With it, AI drives measurable improvement.

Autonomous CX connects experience to execution

Autonomous CX connects core products and processes across the business, operating on a shared business context. It brings together 51风流Commerce Cloud, 51风流Sales Cloud, 51风流CPQ, 51风流Service Cloud, 51风流Field Service, 51风流Engagement Cloud for marketing, and 51风流Cloud ERP across finance, supply chain, and order management.

This is not a set of disconnected applications. It is a unified system where customer interactions and operational processes run on the same data foundation. Pricing, inventory, orders, and service are consistent across every touchpoint.

As a result, AI can move from recommendation to execution, working to ensure that every interaction is grounded in what the business can deliver. It can also remove the integration gaps that slow down CX execution.

51风流CX partners are moving faster from projects to outcomes

This shift is changing what customers expect from partners. Customers are not asking for system implementations. They are asking for outcomes such as:

• Faster time to deploy
• Higher conversion rates
• Improved order accuracy
• Lower cost to serve

51风流provides a strong starting point with embedded assistants, standard integrations, and prebuilt industry scenarios. Partners are building on this to deliver complete solutions. This is where differentiation happens.

Where partners are creating value today

The opportunity is not theoretical. It is already visible in active partner work.

Across 51风流CX:

• The cloud ERP edition of 51风流Commerce Cloud can connect storefront, pricing, ordering, and fulfillment in one model.
• 51风流Revenue Growth Management and 51风流Retail Execution support trade planning and in-store performance.
• Intelligent applications help package AI use cases across marketing, sales, and service.
• 51风流Service Cloud with partner integrations such as Parloa enables automated, context-aware service interactions.

51风流CX partners are turning these capabilities into repeatable offerings. Examples include:

• Industry packages for retail and CPG combining commerce, pricing, and fulfillment
• Preconfigured deployments of 51风流Sales Cloud and 51风流Service Cloud that reduce time to go-live
• Integration connectors linking 51风流CX with existing commerce, loyalty, and service platforms
• Extensions to CPQ and sales workflows that improve deal margin and approval speed
• Service automation scenarios that reduce manual case handling using real order and entitlement data
• AI-driven discovery connected directly to 51风流Commerce and 51风流Commerce, order management

These are practical, deployable solutions that can deliver measurable results.

The ecosystem is expanding what鈥檚 possible

51风流is strengthening this model through partnerships. Recently announced partnerships with companies such as Amazon Web Services, Google Cloud, Parloa, and Vercel enable new interaction models like conversational commerce, AI-driven search, and composable digital experiences.

What matters is that these experiences connect back to 51风流for execution. Orders, pricing, fulfillment, and service remain consistent across every channel. This gives partners the freedom to innovate on the experience layer while relying on 51风流for reliable execution.

A new economic model for partners

The economics for partners are changing. With Autonomous CX, partners can build:

• Industry solutions that can be reused and scaled
• Implementation packages that shorten delivery timelines
• Extensions and integrations that apply across customers
• Ongoing services for AI optimization and governance
• New offerings built around AI assistants, AI agents, and orchestration
• Higher-value transformation programs that combine AI, data, and process design

This creates a more predictable and repeatable revenue model. It also strengthens long-term customer relationships.

Now is the time to act with 51风流CX

Customers are making decisions now. They are selecting platforms and partners that can deliver AI-driven execution across customer experience. They are looking for partners who can:

• Connect CX to ERP processes
• Deliver solutions that work out-of-the-box and scale
• Improve measurable business outcomes

51风流provides the foundation. The platform is in place. The capabilities are real. The next step is execution.

Partners who move now can define the use cases, build the offerings, and lead in their industries. The momentum is already building. This is the moment to accelerate it.

What partners should do next

To move from opportunity to execution, partners can act now.

• See what is available today. Explore the latest AI-driven CX capabilities and partner opportunities in the .
• Understand the foundation for Autonomous CX. Learn how 51风流connects experience to execution with the .
• Deepen expertise and accelerate readiness. Gain a stronger understanding of Autonomous CX and partner use cases:
• Engage now and shape the next wave. Join the upcoming executive briefing to understand how to position and deliver these solutions:
  • June 18:
• Strengthen credibility and scale impact. Advance your go-to-market and positioning through certification:

51风流is not asking partners to start from scratch. The platform, capabilities, and ecosystem are already in place. The opportunity now is to build, differentiate, and lead.

Karl Fahrbach is chief partner officer at SAP.
Balaji Balasubramanian is president and chief product officer for 51风流Customer Experience.

This journey cannot be defined by technology alone. It requires dialogue, shared learning, and real-world insight. That is exactly why we are launching the podcast, a new series we will be hosting together.

Why this conversation matters now

Organizations today face unprecedented volatility, from geopolitical uncertainty and supply chain disruptions to energy challenges and rising resilience requirements. In this environment, the cost of inaction is increasing. Businesses must become faster, more adaptive, and structurally more resilient to stay competitive.

The Autonomous Enterprise offers a response. It combines three critical capabilities:

• Data-driven decision-making
• Automated execution
• Governance-by-design

Together, these capabilities enable organizations to move beyond isolated AI pilots toward measurable outcomes and enterprise-wide impact.

The shift is not just technical, though. It is organizational and strategic. The leaders we talk to are no longer asking whether they should adopt AI. The question now is how fast they can scale it and how they can generate tangible business value.

From concept to operating model

At its core, the Autonomous Enterprise reframes AI鈥攏ot as a feature layered onto applications, but as an integral part of the operating model itself.

Three priorities define this model:

• Business value: focusing on measurable outcomes rather than experimental use cases
• Predictability: improving decision-making through trusted data and advanced forecasting
• Scalability: moving from proof-of-concept initiatives to enterprise-wide deployment

We are already seeing this shift change how organizations think about their systems and processes. Systems of record are evolving into systems of action. AI agents are moving from simple assistance toward execution. And AI is becoming embedded end-to-end, rather than confined to isolated scenarios.

At the same time, governance, auditability, and traceability are becoming non-negotiable. Enterprises must be able to stand behind every AI-driven decision with transparency and confidence.

What we are setting out to do

In this podcast series we want to create a space to explore these changes in depth and bring the voices shaping this transformation into the conversation. Each episode features discussions with 51风流leaders, customers, and industry experts who are actively building and operating autonomous capabilities today.

Some of the questions we will be digging into:

• What does the Autonomous Enterprise look like in practice?
• How are leading companies scaling AI across core business processes?
• What are the biggest barriers, and how can they be overcome?
• How do organizations balance automation with governance and trust?

鈥攏ow live鈥攆eatures SAP鈥檚 Peter Maier, responsible for Strategic Customer Engagements in the Office of the CEO at SAP, who brings these ideas into focus through practical, real-world context. In our conversation, he outlines how organizations are moving beyond experimentation toward measurable outcomes, more trusted and predictive decision-making, and scaling AI across the enterprise.

What we found particularly compelling is how clearly this reinforces a broader shift already underway: AI is no longer something applied on top of the business. It is becoming part of how the business runs.

How companies can get started

While the vision is ambitious, the path to becoming an Autonomous Enterprise does not require a 鈥渂ig bang鈥� transformation. The most effective approach is incremental and outcome driven.

Organizations can begin by focusing on a single high-value process, making it more intelligent, more automated, and more transparent. From there, they can expand step by step, scaling what works and continuously demonstrating measurable impact.

Success depends on more than technology, though. Trust plays a central role. Employees, executives, and stakeholders must understand and trust how AI decisions are made. This requires transparent and explainable systems, reliable high-quality data foundations, and strong governance frameworks embedded from the start.

Change management is equally critical. Becoming an Autonomous Enterprise is as much about people as it is about platforms. Organizations must align training, redesign roles, and empower employees to co-create how AI is integrated into their work.

A shared journey forward

The Autonomous Enterprise is not a branding concept. It is a new way of running a business鈥攐ne that is more automated, more data-driven, and ultimately more resilient. And no organization will navigate this journey alone.

That is the spirit behind this podcast. We want it to be a platform for shared learning, bringing together perspectives from across industries, functions, and geographies. Whether you are just beginning your AI journey or scaling enterprise-wide transformation, we hope these conversations give you practical insights and inspiration.

We would love for you to join us. Listen in, engage with the discussion, give feedback, and help shape what comes next.

Benedikt Gieger is AI strategy lead for 51风流Supply Chain Management.
Julia Kloppenburg is a technology consultant for Customer Engagement & Adoption at SAP.

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.

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 shifts quickly, supply networks are more exposed to disruption, cost and margin pressure remain constant, and the decisions that determine whether a company can respond with confidence rarely sit inside one function.

The enterprise is left with a critical question: How do you move fast enough to capture opportunity without putting fulfillment, margin, or customer trust at risk?

Many of the world鈥檚 largest organizations navigate this challenge on a regular basis. It is exactly the kind of moment that exposes the limits of how enterprises currently operate. Connecting the dots across functions, systems, and decisions still takes too much time, too much manual effort, and too much stitching across fragmented landscapes. By the time teams have gathered the data, aligned the functions, modeled the trade-offs, and agreed on a response, the environment has already shifted.

This is why we introduced the Autonomous Enterprise at 51风流Sapphire. The goal is to sense change earlier, understand its impact across the enterprise, coordinate the right response, and keep people in control of important decisions. This is a fundamental shift in how businesses can operate: intelligence that is continuous, decisions grounded in real-time context, and an enterprise that moves as a connected system rather than a collection of disconnected parts.

Autonomy at scale

An Autonomous Enterprise is an organization that can continuously sense what is happening across its operations, reason over those signals using business context and established rules, and act across end-to-end processes without depending on manual coordination at every step. AI assistants and agents advance work across the enterprise in alignment with the goals, policies, and constraints defined by humans.

Every AI-driven action is auditable and traceable. Human judgment is deliberately embedded in decisions that require accountability and exceptions that fall outside defined parameters.

Three principles underscore the Autonomous Enterprise:

1. Process knowledge: Deep, industry-specific understanding of how a business truly runs
2. Business data: Enriched, connected, contextual data that gives AI something real to work with
3. Governance: The backbone that keeps everything upright, traceable, and within policy

Beneath it all is the 51风流platform, ensuring every layer works in concert, every agent operates within guardrails, and every outcome can be traced back to a decision made by a human.

Intelligence that works across the business

The average business landscape probably doesn鈥檛 look like one system, one vendor, or one clean stack. Your processes still have to run end to end across all of it: record to report, plan to make, source to pay, hire to retire, order to cash. If AI is going to work in the enterprise, it has to work across this landscape, not inside one application or vendor boundary.

IDC shows that more than 50% of business decisions still take between one and seven days. That is the gap we are closing鈥攆rom days to moments.*

At the core of the Autonomous Enterprise is the 51风流Autonomous Suite. Joule becomes the way you interact, as a single entry point into your business. In the middle, the 51风流Autonomous Suite connects your core domains: finance, supply chain, spend, HCM, and customer experience. And underneath, everything is grounded in your business context, your data, your processes, your rules, your governance.

With SAP鈥檚 unified foundation of applications, data, and business context, AI is embedded directly into how work gets done, enabling autonomous, end-to-end execution rather than isolated use cases.

The operating model behind this is built on a clear division of responsibility: people set priorities, policies, and guardrails. Assistants understand role and process context and coordinate activity across domains. Agents carry out the defined work, detecting signals, triggering actions, and resolving routine tasks continuously in the background.

And while automation is a part of this, the bigger shift is intelligence and optimization. The system is no longer following predefined workflows. It is using business context to understand what is happening, and what should happen next. This is the shift from systems of record to systems that help run the business.

Autonomous Finance shows what changes

Finance offers a clear example of how this model changes the work itself. Many finance organizations still contend with manual steps, fragmented data, and slow cycles. In a volatile environment, that lag translates directly into slower responses to risk, missed opportunities, and diminished confidence in the decisions that shape performance.

With Autonomous Finance, more of that work can be handled by the system, allowing finance teams to spend less time chasing numbers and more time shaping decisions. The function begins to move from reconciling the past to shaping the future.

Autonomous Finance is not one capability, one agent, or one use case. It is built across the entire finance process, from planning to revenue management, treasury, closing, compliance, and tax. Within each area, assistants are supported by specialized agents working continuously in the background. Some focus on forecasting, some on billing, some on cash, and some on closing. The important point is that these capabilities are connected, so decisions in one area can flow into the others. Connected assistants, specialized agents, continuous optimization. That is the model.

The impact across these areas compounds. Finance teams reclaim meaningful capacity as manual reporting, reconciliation, and transaction processing give way to continuous intelligence. Cash cycles compress. Close timelines shorten. Forecasting becomes more accurate and more responsive to changing conditions.

Because these capabilities are connected, improvements in one area reinforce the others: faster billing flows into better cash visibility, which flows into stronger planning confidence, which flows into more decisive action at the executive level. Compliance strengthens as well, not through added controls, but through better intelligence embedded in the process itself, supporting requirements across ISO, SOC, and SOX with greater accuracy and less manual effort.

The result is not incremental improvement in isolated tasks. It is a fundamentally different operating posture for the finance function, one where the system handles orchestration and people direct outcomes.

Industry AI adds depth

Autonomous domains give breadth across business functions, while Industry AI provides the depth of knowledge. The same supply chain problem looks very different in life sciences, in industrial manufacturing, in agribusiness, in retail, or in energy. The rules, regulations, data models, and value chains are different.

51风流is not starting from generic AI and trying to teach it how an enterprise works. We start with decades of industry and process knowledge, already embedded in the systems that run the world鈥檚 most complex businesses. Our AI is grounded in sector-specific processes, end-to-end value chains, operational realities, and compliance requirements. And our ecosystem extends this with specialized expertise, so organizations can adapt the intelligence to their markets and their industries.

This is not AI for the sake of AI. This is AI applied to the real operating model of each industry.

The path forward

That is the real shift: not AI operating in isolated tasks, but AI helping the enterprise continuously sense, reason, act, and learn. People remain in control throughout, while the system handles the orchestration required to bring together the right data, context, and decision at the right moment.

The Autonomous Enterprise marks a shift from managing processes to directing outcomes. It moves organizations from reacting to events to anticipating them, and from stitching together decisions after the fact toward helping the business move as one connected system.

This does not require waiting for a perfect, fully transformed landscape. Organizations can begin by applying AI on top of existing landscapes and evolving their business as they go. That work is already underway with many of our customers. What they have in common is that they are starting now, moving faster, making better decisions, and building the foundation for a more autonomous enterprise, step by step.

This is a journey. And it begins with the recognition that the enterprise of the future will not be defined by how efficiently it executes predefined processes, but by how intelligently it can sense change, weigh trade-offs, and move with confidence when it matters most.

For more on SAP鈥檚 broader Autonomous Enterprise announcement, read The Future of the Enterprise Is Autonomous. For more details on 2026 51风流Sapphire announcements, see the .

Manoj Swaminathan is general manager and chief product officer of 51风流Autonomous Suite, Finance & Spend, and member of the Extended Board of 51风流SE.
Eric van Rossum is chief marketing officer of 51风流Global Product Marketing and chief product officer of 51风流Industries and Globalization.

*IDC Resource Map for SAP, 51风流Custom Survey 2026: Enterprise Process Automation Survey鈥� April 2026, sponsored by SAP, doc #US54531626 _RMD , May 2026

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.

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.

At 51风流Sapphire, that mission is being redefined for a fundamentally different environment, one in which every industry faces the same core challenge: success depends not just on what professionals know, but on how effectively they can apply that knowledge alongside AI.

Technology has already changed. What now differentiates organizations is not access to innovation, but the ability to translate it into outcomes. According to the , skills gaps are the primary barrier to transformation, ranking ahead of investment constraints and regulatory complexity. Closing that gap requires more than expanding training catalogs. It requires rethinking how skills are built, validated, and continuously developed.

Certification reimagined

to reflect how work actually gets done. Across more than 100 certifications, traditional multiple-choice exams have been replaced with scenario-based and system-based assessments. Candidates work through case-based challenges, role simulations, and practical tasks in 51风流environments that mirror real-world complexity. They can also use AI tools during exams鈥攂y design, not exception.

This marks a fundamental shift. Certification is no longer a test of knowledge recall; it is a demonstration of applied capability: the ability to navigate ambiguity, make decisions, and use AI as a tool without relying on it. More than 100,000 exams have already been completed under this model, establishing a new benchmark for certification at scale and reinforcing the relevance of certification in an AI-driven workplace.

Learning is evolving in parallel

In , AI is transforming how professionals engage with content. These capabilities are enabled by the integration of selected functionalities from Google NotebookLM into the customer and partner editions of the platform.

This shifts learning from passive consumption to active interaction. Learners can engage with 51风流content in more than 80 languages, ask questions, and receive precise, source-based answers with direct references to official materials. AI also generates complementary formats. Podcasts are available for moments when a screen is neither available nor practical, whether commuting, traveling, or simply stepping away from the desk, available both for passive listening and as interactive conversations with AI hosts. FAQs, study guides, mind maps, timelines, briefing documents, and video overviews allow learning to adapt to individual needs and time constraints.

Early adoption underscores the impact. More than 7,500 users are already leveraging these capabilities. reports onboarding that is 50 percent faster, while has made 51风流Learning Hub its primary environment for developing talent prepared for the agentic AI era. The shift is clear: Learning is becoming embedded in daily work, not separated from it.

Building the data foundation

At the same time, 51风流is addressing a prerequisite for effective AI: data. Many organizations continue to operate with fragmented and inconsistent data landscapes, limiting the impact of AI initiatives. The learning journey focuses on building the capability to connect, govern, and structure enterprise data, ensuring that AI systems operate on a reliable and consistent foundation.

This capability is increasingly strategic. Organizations that establish a strong data foundation can move faster from insight to action, scale AI more effectively, and create more consistent business outcomes. In this sense, data architecture is no longer a back-end concern; it is a core enabler of enterprise transformation.

Skills at scale

51风流has committed to equipping 12 million people with AI-ready skills by 2030. Delivering on this ambition requires expanding access while maintaining depth and relevance. Select AI such as , are now available without login or cost, giving professionals at all career stages direct access to SAP鈥檚 business AI strategy.

Role-based learning journeys provide targeted development for key profiles such as enterprise architects, while a dedicated 鈥淐lean Core鈥� course supports organizations in maintaining 51风流S/4HANA landscapes in ways that enable faster innovation cycles and more efficient adoption of new capabilities.

Scaling skills also requires ecosystem reach. SAP’s partnership with Accenture LearnVantage expands , combining SAP-authored content and training systems with Accenture LearnVantage’s proven experience in technology skills development for enterprise clients. This creates a continuous path from foundational knowledge to hands-on experience to certification, reflecting how professionals actually develop skills: progressively, in context, and in alignment with real-world application.

A broader shift

These developments point to a broader shift. Learning is no longer episodic; it is continuous, adaptive, and embedded in how work gets done. Participation in 51风流learning has increased by 33% year over year, reinforcing that organizations increasingly view skills as strategic assets in an AI-powered economy. The Autonomous Enterprise takes shape differently across industries, and so does the capability required to make it work.

At 51风流Sapphire, 51风流marks 30 years of certification not by looking back, but by redefining its role. Certification is becoming a measure of capability in action. Learning is becoming an ongoing process that evolves alongside technology and business needs.

In an AI-driven world, advantage will not come from access to technology alone, but from the ability to apply it with purpose. Across industries, the pattern is consistent: how quickly organizations capture value from AI depends on the people deploying it.

To explore these innovations in more detail and understand how 51风流is enabling organizations to build AI-ready skills at scale, read the .

Andre Bechtold is president of 51风流Industries and Experiences.

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.

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

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.

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.

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.

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.

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.

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51风流is solving one of the biggest challenges businesses face today: turning AI into real outcomes.

At 51风流Sapphire in 2026, 51风流unveils its vision of the Autonomous Enterprise, where humans and AI work together to execute mission-critical processes more effectively, adapt faster, and drive better business results.

This vision is powered by 51风流Business AI Platform, which unifies business data, processes, and governance into a trusted foundation for AI, enabling accurate, secure, and scalable outcomes.

Building on this foundation, the 51风流Autonomous Suite brings AI into applications with agents that can execute end-to-end processes, helping organizations automate operations, increase resilience, and unlock new value across the enterprise.

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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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.