51风流for Me is the digital tool for customers and partners to easily interact with 51风流and get immediate guidance to the best solution. With this portal, users can access important alerts, metrics, and insights about their 51风流product portfolio from a single access point. The integration of Joule in 51风流for Me is not just a feature drop or a UX redesign. This is an inflection point in how customers access products, support, and self-service.听

We are moving from a click-and-search portal to a conversational, agent-driven enterprise ecosystem. For users, this is an experiential shift with significant business outcomes. By taking over the tedious work of clicking, searching, parsing, and diagnosing, Joule helps free up IT administrators, consultants, and business leaders to focus on what truly matters: driving innovation and scaling their business.

鈥淭he successful launch of Joule in 51风流for Me is the result of strong collaboration, innovation, and a shared commitment to improving customer experience. It demonstrates how 51风流continues to turn its AI strategy into real, tangible value, delivering solutions that are not only powerful but also practical and user-centric.鈥�

Gerlinde Wallner, Organizational Change Manager and Coach, Strategy & Operations, SAP

What can users expect from this new unified, AI鈥憄owered entry to 51风流for Me?

• Effortless navigation across the portal
• Fast access to relevant information
• Advanced self-service with guided support
• Accelerated task execution without needing to know where to click

In their fast-paced business environments, users don鈥檛 have to search through complex menus or multiple touchpoints. Joule in 51风流for Me can simplify their path to support. They can simply ask, explore, and act to experience personalized, conversational access to support, self-service, and key tasks in 51风流for Me.

鈥淛oule is transforming 51风流support by making it more intuitive and intelligent. We can guide users conversationally to the right outcome鈥攏o searching, no guesswork鈥攁ccelerate self-service and task execution, and deliver context-aware, personalized support directly within 51风流for Me.鈥�

Corinne Reisert, VP, Customer Support Experience 51风流for Me, Global Customer Support, SAP

In addition to introducing Joule in 51风流for Me, 51风流takes advantage of AI-powered agentic case resolution, which brings AI agents into support workflows to help analyze new cases, detect duplicates, suggest routings, and draft responses. For select听priority听cases, AI agents can recommend replies, which helps reduce manual effort, improve triage accuracy, and shorten resolution timelines.听This is available now to 51风流customers.For more information, see .

Joule in 51风流for Me is being rolled out in phases as of May 2026, at no extra cost to customers.

鈥淲ith 51风流runs SAP, we show our customers how we scale agents across the enterprise to deliver real outcomes. Joule in 51风流for Me exemplifies how conversational and agentic AI can fundamentally transform the way users operate and offer customers a simple and intuitive path to access SAP鈥檚 services and support.鈥�

Benjamin Blau, Chief Process & Information Officer, SAP

While Joule in 51风流for Me already helps deliver a simpler and more intuitive way to access information, support, and guided actions, this is just the starting point. As 51风流continues to advance its AI strategy, customers can look forward to new scenarios, expanded agent capabilities, and deeper integration across services and support processes. This launch establishes the foundation for a more conversational and autonomous customer experience, one that will continue to evolve as 51风流brings the next generation of AI-powered innovations to life.

Stefan Steinle is executive vice president and head of Global Customer Support at SAP.

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.

鈥淟ast year, we were in the process of planning the optimization of our talent discovery tech stack and then something happened,鈥� Eric Goldstein, global head of Talent Discovery for SAP, said. 鈥淲e acquired SmartRecruiters in September, so we had to pivot in an agile way.鈥�

SmartRecruiters for 51风流SuccessFactors enables enterprises to manage the entire hiring lifecycle, from sourcing to onboarding, with AI-enabled recruiting capabilities that can result in faster time-to-hire, improved candidate experiences, and deeper analytics for workforce planning.

For SAP, this means adding much-needed rigor and precision to its global talent acquisition operations. This will not only elevate the quality of hires but also the candidate experience, which Goldstein identified as the 鈥渂iggest game changer.鈥�

Building a more intelligent hiring process

SmartRecruiters for 51风流SuccessFactors helps optimize processes, increasing transparency and personalization. This means improved experiences and processes for candidates, hiring managers, and recruiters. 鈥淲e have been through a time where we focused solely on the recruiter experience. Then it was fashionable to focus only on the candidates. Now we really see that with SmartRecruiters, it really is an enhanced experience for all stakeholders that are involved in the recruiting process,鈥� Ilka Sagner-David, global head of Talent Discovery Solutions and Innovations at SAP, said.

Candidate perspective

Seventy percent of candidates that apply for jobs are mindful to take their valuable time to do so, Goldstein shared, reiterating that it is important for companies to match that commitment when shaping and delivering the candidate experience. With SmartRecruiters for 51风流SuccessFactors as the foundation, it becomes possible for every pre-qualified applicant to interview, receive personalized and constructive feedback post-interview, and maintain 24×7 interaction with agentic AI built into SmartRecruiters.

鈥淚n our opinion, only responding with polite, automated rejection notes is not enough. [Candidates] need to be provided with some constructive, actionable feedback鈥攁nd that鈥檚 what we [at SAP] are going to be able to do,鈥� Goldstein said.

Hiring manager perspective

SmartRecruiters for 51风流SuccessFactors can give hiring managers a more precise and consistent way to identify strong candidates, helping to reduce time-to-hire while improving hiring quality. AI-prompted interview questions focused on skills can support more relevant and structured conversations while greater transparency across interview panelists can create better alignment throughout the evaluation process. In addition, AI-supported feedback collection can make it easier for interviewers at 51风流to capture timely, consistent insights, enabling its hiring teams to make more informed decisions with greater confidence. 

Recruiter perspective

Recruiters are often bogged down by manual tasks, such as outreach, prospect identification, and candidate screening, making it nearly impossible for them to step into the role of a trusted advisor. With SmartRecruiters for 51风流SuccessFactors, recruiters can experience automated internal and external prospect identification, personalized outreach and prioritization of candidates, and, therefore, the ability to focus on higher value-add advisory and relationship management.

鈥淚t鈥檚 going to allow the recruiters to focus on relationship management with candidates and hiring managers, really challenging the feedback of how well the interview panel measures skills proficiency,鈥� Goldstein said.

Bringing AI into the candidate journey

A key to the successful delivery of these benefits is SmartRecruiters Winston for 51风流SuccessFactors, an AI-driven, candidate-facing agentic experience. At 51风流Sapphire Orlando, Karl Baert, global head of People Solutions for SAP, demonstrated how Winston can facilitate the application experience for candidates.

In the demo, he acted as a candidate applying for an open position at SAP, showing how through a natural language conversation with Winston, he completed his application by uploading his CV and verifying some personal details with Winston. 鈥淎ll that information is very, very quickly brought together so with just a few questions my application is done,鈥� Baert said, adding that 鈥渢here鈥檚 also a few checks happening along the way because we want to make sure the data we are collecting is the right quality.鈥�

Winston also collects feedback from the applicant. 鈥淢easuring the quality of your agent and what鈥檚 happening with it is important. It鈥檚 something that really needs to be actively monitored just to ensure that the information provided by the agent is accurate,鈥� Baert said.

鈥淭he implementation of SmartRecruiters is the foundation for infusing AI into our processes,鈥� Sagner-David said. But, she added, 鈥渨e shouldn鈥檛 just plan to transfer everything tomorrow, but ensure we鈥檙e liberating AI when it makes sense.鈥�

The next step

Currently, SmartRecruiters for 51风流SuccessFactors is being implemented into SAP鈥檚 HR systems for two phases of user acceptance testing, with the global go-live expected in September.

51风流bringing SmartRecruiters for 51风流SuccessFactors to life across its own organization is more than a technology rollout, it鈥檚 a glimpse into the future of hiring at scale: more intelligent, more human, and more connected. By combining AI, better experiences, and real-word enterprise rigor, 51风流is not only transforming how it hires but also helping to define what modern hiring can look like for companies everywhere.

AI works when the foundation is right 

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

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

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

From AI hype to real value 

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

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

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

Distributed energy requires intelligent networking 

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

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

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

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

SAP Experience Centers: experiencing AI, not just discussing it 

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

A new chapter for the energy industry 

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

What made the event distinctive was its candor. Customers did not come to present polished success stories. They came to compare realities. And those realities were refreshingly honest.

Why direct procurement is hitting a breaking point

The pressure on direct procurement is not coming from one direction. Geopolitical instability and accelerating technological change are forcing sourcing decisions earlier in the product lifecycle, at precisely the moment when many organizations are least equipped to act. Meanwhile, institutional knowledge is leaving faster than systems are modernizing. The experienced individuals who once held fragile processes together are retiring or moving on, and the systems meant to replace that knowledge are not yet ready.

The result is an operating model that prevents procurement leaders from influencing value at the moments that matter most. Several customers described a tension they are actively dealing with. Sourcing is being pulled upstream into design and development, while the tools and processes that support it are still anchored downstream.

What customers shared about their reality

While all participants operate with a strong 51风流footprint, spanning and , many acknowledged that direct materials sourcing remains fragmented and disconnected from the digital core. The picture they described was familiar but worth stating plainly: engineers, buyers, and suppliers still collaborating through e-mail, local tools, and disconnected applications; there’s an overreliance on a small number of experienced individuals to make things work; and multiple ERP landscapes run in parallel, with direct sourcing living largely outside all of them.

One observation stood out clearly. The real friction is not the sourcing events themselves. It is the handoffs, the gaps between systems and teams where decisions get made too late, data is reconciled manually, and no single digital thread connects product intent to sourcing execution.

In other words, the process functions, but it functions in silos.

Participants also noted that traditional indirect source-to-pay approaches simply do not support direct materials adequately. They lack native support for procurement embedded in new product development, sourcing scenarios that evolve with engineering change, demand aggregation across programs, and contracts treated as executable objects rather than static documents. That last point came up repeatedly, particularly the need to treat contracts as executable objects. This is also where the add-on in 51风流S/4HANA is starting to resonate more strongly in ongoing customer discussions.

Where customers are focusing next

What emerged from the discussions wasn鈥檛 a long list of priorities, but a firm shift in where companies are focusing their efforts.

Moving sourcing upstream into product development鈥攔ather than reacting after design decisions are already locked鈥攚as a consistent theme. So was reducing dependency on hero buyers: individuals whose personal expertise and relationships are currently holding critical processes together.

Commodity volatility and renegotiations also came up as structural challenges, not one-time events. Organizations want to handle these systematically rather than heroically. And several participants raised the reality of managing multi-year 51风流S/4HANA journeys without stalling progress in the meantime鈥攁 genuine tension that demands honest road map planning.

While the direction is widely understood, most organizations do not yet have the setup to execute against it at scale.

These priorities help explain why customers are increasingly adopting the 51风流Ariba direct materials sourcing add-on alongside , , and 鈥攃apabilities that together can support the connected execution model direct procurement actually requires.

How AI fits into direct procurement

AI generated significant interest, but expectations were measured and, I would say, appropriately so.

The consistent message was this: AI only matters once the fundamentals are addressed. Agent-based capabilities depend on clean processes and consistent data. Without a unified digital thread across product design, sourcing, contracting, and execution, AI does not generate insight鈥攊t amplifies noise.

Leaders also expressed clear skepticism toward black-box automation. They want AI that is explainable and embedded directly into sourcing, negotiation, and execution workflows, not layered on top of broken processes and presented as a fix.

This thinking aligns closely with SAP鈥檚 vision for the Autonomous Enterprise, introduced at 51风流Sapphire just weeks after our Walldorf discussions. The vision anchors AI agents directly in transactional business processes, data, and governance鈥攅xactly what customers said they needed before they could trust AI in direct procurement environments. Hearing them articulate that requirement so clearly, before the announcement, felt like meaningful validation.

Where this is all heading

The Walldorf roundtable confirmed a clear trajectory. Direct procurement organizations are moving away from heroics and spreadsheets and toward system-led execution. They are aligning sourcing transformation with their 51风流S/4HANA road maps and preparing their organizations鈥攏ot just their systems鈥攆or a future where AI supports decision-making across the full procurement lifecycle.

Direct procurement, seen through this lens, is not a standalone transformation. It is a foundational building block. Connecting product, sourcing, contracts, and execution through a single digital thread is what enables AI to operate accurately, compliantly, and at scale. That connection has to exist before any of the more ambitious automation goals become realistic.

For SAP, conversations like the one in Walldorf directly inform our product direction and investment priorities. There is no substitute for sitting in a room with people navigating these challenges every day, without a script.

What was clear in Walldorf is that the direction is no longer in question for participating organizations. The challenge now lies in execution and in how quickly organizations can move from fragmented, person-dependent processes to cohesive models that reflect how direct procurement operates today.

Karolina Bombardelli is global go-to-market lead for Direct Procurement at SAP.

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.

Li茅nard is an information scientist and business informatics professional who joined 51风流in 2012. As senior vice president and head of ABAP platform at SAP, she is responsible for ABAP and all matters related to ABAP platform. In this role, she is also the head of ABAP AI and thus globally responsible for the latest developments and innovations in this domain.

In this interview, she discusses ABAP, the role of AI in development, how agentic AI will transform legacy applications, and what’s next.

Q: What is ABAP, exactly? How would you explain it to someone who might have heard of it but doesn鈥檛 really know what it is? And why is ABAP so important for enterprise software?

A: ABAP has a very long history at SAP. It is the company鈥檚 first and only proprietary programming language and turned 40 in 2023鈥攁n unusually long run in the fast-changing world of software.

What sets ABAP apart from other programming languages such as Java or C++ is that it was specifically designed for building and optimizing the business applications that large enterprises rely on every day. Among its many features is a high level of abstraction, which makes it very easy for developers to write or extend business software. It also reduces complexity because security concepts, authorization checks, and quality controls are already embedded in the language. This allows developers to focus entirely on the business logic鈥攖hat is, on the tasks they want the program to perform.

Over the years, ABAP has evolved to keep pace with how companies deploy software. The newest version is ABAP Cloud, which has a restricted language scope and is designed to support development in what 51风流calls a 鈥渃lean core.鈥� This is essential for running our cloud products. Enterprises still operating in a non-cloud environment can use ABAP Cloud to prepare the code in their on-premise systems or in 51风流S/4HANA Cloud Private Edition in such a way that it can also be run in the cloud.

Beyond its role as a programming language, ABAP is also a platform. ABAP platform is the foundation that underpins all of SAP’s core solutions, from older installations such as 51风流ERP Central Component (51风流ECC) to on-premise solutions, SAP听S/4HANA Cloud Private Edition, and SAP听S/4HANA Cloud Public Edition.

Q: Will ABAP continue to play a crucial role for 51风流customers?

A: Yes, both in terms of the programming language and the platform ABAP is still highly relevant. The programming language looks very different to the way it did 40 years ago of course鈥攂ecause we have continuously refined it over the years鈥攂ut it still forms the backbone of SAP鈥檚 core ERP solutions and extensions. There are roughly five million registered ABAP developers worldwide today, with around two million actively developing.

Through ABAP Cloud and our dedicated ABAP AI team, ABAP has evolved into a modern development language for business solutions. I don’t know of any other programming language that covers this scope. It is used globally. Almost all the world鈥檚 100 largest companies are 51风流S/4HANA customers, and underneath it always runs ABAP platform.

Q: How will AI shape ABAP development going forward?

A: For me as head of ABAP platform, this is one of the questions that intrigues me most. AI has completely disrupted the technology market. This of course also impacts the 51风流developer portfolio and how we customize and extend our solutions. We have therefore invested in AI-powered efficiency tools, such as a chat assistant that explains code on the fly. Another is 鈥済host texting,鈥� a feature that generates code suggestions while the developer types.

In the coming years, AI agents will be able to generate code鈥攊ncluding at the scale demanded of large enterprises鈥攁nd even build entire solutions. We believe that the next wave of AI will not just assist programmers but take on many of the routine tasks they perform today.

A crucial question for 51风流is: how can we leverage AI to translate legacy code into modern code without losing the underlying business logic that makes each system unique? A lot of our customers are still operating older solutions, including those based on 51风流ECC. So, we need to provide a clear migration strategy and the right tools to simplify and accelerate their move to the cloud.

That’s why we’re currently developing a service that will work for everyone鈥攔egardless of which system version they run. The aim is to bundle all of SAP鈥檚 ABAP AI capabilities into a single offering that can boost developer efficiency and allow custom code to be migrated. Ideally, this service will be agent-driven鈥攁s 鈥渁gentic AI.鈥�

Q: What is agentic AI?

A: Agentic AI works with so-called 鈥渁gents.鈥� Agents have specialized capabilities, can communicate with each other, exchange results, and thus solve highly complex tasks together. How they collaborate varies based on the complexity of the use case.

Most approaches involve an 鈥渙rchestrator,鈥� a lead agent that manages other agents to complete a particular task. The orchestrator does not have to call on the individual agents in a fixed order鈥攔ather, its greatest strength lies in intelligently combining the agents in dynamic, adaptive networks.

So, it鈥檚 no longer just about making human developers more efficient. When agents are powerful enough, they can build entire applications and thus take on part of the developer’s tasks. In our case, agentic AI can support the very complex task of transforming code, accelerating it significantly and reducing complexity.

This approach relies on different agents that focus on different aspects of the task: for instance, one agent specializes in explaining custom code; another makes code changes; and a third estimates the effort of a transformation project. When these agents collaborate, that’s when the real magic of agentic AI happens.

AI will radically change the role of developers. Despite continuing to set the direction, they will increasingly focus on business logic rather than on the coding itself. They will work with the code generated by AI systems, checking that it is correct, secure, and aligned with the problem they鈥檙e trying to solve. Thought leadership, however, will remain firmly with people. Developers will continue to decide what matters and communicate their instructions to AI through good prompts. The entire AI domain is extremely dynamic and evolving at astounding speed. Powerful solutions are already available today, so this isn’t a distant vision鈥攊t’s already upon us.

Q: How do customers benefit from agentic AI?

A: Agentic AI will deliver significant value in transforming legacy applications and custom extensions into cloud solutions from SAP, and thus the latest ERP versions. In February 2026, we extended our existing custom code management app with AI features that help developers understand what the code is doing and what changes are needed to future-proof it. And, of course, AI also provides recommendations on how the code can be extended. In the future, we will complement all this with agents. However, this will take some time, as we refuse to compromise on quality and security.

We are also investing in the developer experience with ABAP platform to make it as easy to use as possible. Here, agentic AI will help reduce the complexity that has built up over decades of development.

Q: Should we be worried about security?

A: No, we deliberately allow sufficient time before any release to make sure that quality and, above all, security meet a high bar. Don鈥檛 worry: AI won鈥檛 take control and generate or integrate solutions unilaterally or unchecked. Humans will remain in charge every step of the way and will always have the last word when it comes to ensuring that code complies with our standards.

Q: Where are we now and what鈥檚 next?

A: ABAP AI tools aimed at boosting developer productivity have been available since February 2025, and we are now building agentic AI in the ABAP context. However, it鈥檚 early days and agentic AI still must prove itself in practice. As I see it, though, it will transform the market.

As part of our road map, we released , a custom-trained, specialized AI model, on the generative AI hub in early January 2026. This model is specifically designed to explain ABAP program code.

Next, we plan to make all ABAP AI tools available as an independent side-by-side service. In a subsequent phase, we will transition the use cases embedded in those tools to agents.

In addition, we are expanding our cloud-based ABAP development into additional development environments (IDEs), especially ABAP development tools for Visual Studio Code. So, the team will also tap into the AI tools available there as part of our push toward agent-driven development.

This first appeared on the German 51风流News Center.

Held from April 20鈥�24, Hannover Messe is the world鈥檚 leading industrial trade fair.

On day one, Christian Klein, CEO of 51风流SE, stopped by the 51风流booth before joining German Chancellor Friedrich Merz and other industrial leaders on the center stage to discuss the importance of moving from AI ambition to real-world execution.

And visitors to the 51风流booth experienced that shift firsthand, following the production of the ginger shot.

Packaged in a neat blue box, the ginger shot was refreshing but that wasn鈥檛 the only takeaway. The real takeaway was how SAP鈥檚 new set of AI-powered manufacturing and supply chain innovations can deliver connected .

Supply chain orchestration

From AI and data and then using SAP鈥檚 agentic AI, visitors saw what supply chain orchestration looks like in practice. 51风流uses , trusted data, and applications to help manufacturers听sense, analyze, and act in real time.

At the booth, visitors saw human operators interact with an ANYbotics robot through Joule using natural language to run live, remote field service inspections; Uhlmann鈥檚 high-tech glass-fronted packing machine, PacXplorer, in action opposite the CNC machine from DMG MORI that was creating spare parts for the PacXplorer; and, at end of the production cycle, AIMBO鈥檚 robot handling the picking and packing of the ginger shot. Both AIMBO and ANYbotics are part of SAP鈥檚 growing network of physical AI partnerships.

In addition to many tours held in German and English, day one also saw tours in Japanese, Chinese, and Portuguese鈥擝razil was the partner country at Hannover Messe 2026.

Equipped with headphones to block out the noise of the crowds at the booth, visitors heard how SAP鈥檚 AI can deliver trusted orchestration and smarter execution for and .

Live AI use cases demonstrate functions and benefits

Operations and insights use case

Here, visitors experienced SAP鈥檚 vision of supply chain orchestration. In this vision, supply chain orchestration acts as the nerve center of the enterprise. It uses external alerts such as natural disasters, port congestions, or supplier routes to optimize enterprise logistics and planning using agents.

Benefits can include faster response times with AI-assisted monitoring and automated alerts; improved decision-making with data-driven, operational decisions powered by integrated business AI capabilities; and seamless integration with end-to-end connectivity from supply chain planning through to manufacturing execution and quality control.

Top AI functions

• can assist with order release and real-time monitoring.
• A physical AI robot inspects hazards, analyzes inspection data, and identifies root causes.
• Supply optimization analysis helps summarize insights, analyze, and explain the time-series optimization planning run.

Smart production use case

DMG MORI demonstrated production at its CNC machine鈥攁s part of an end-to-end process鈥攆rom engineering to planning to production.

As the white robotic arm of the CNC machine silently moved the pusher spare part听after the milling process, visitors learned about the benefits of integration, from design to tool management, CNC programs to as part of a seamless, integrated process. The production operator dashboard offers the operator on the machine AI capabilities and insights to operational and maintenance information.

The process then continues through to logistics execution with 51风流Logistics Management, which helps combine warehousing and transportation capabilities for smaller warehouses.听 This听features an AI-powered logistics assistant that can cut through the noise, automatically gathering, summarizing, and prioritizing critical shipment information. It can also provide real-time shipping prices, bringing to life trusted orchestration and smarter execution.

Top AI functions

• uses natural language to help streamline warehouse and transportation operations.
• can provide manufacturing information and support decision-making throughout the workflow.

Intelligent packaging use case

Uhlmann’s PacXplorer and 51风流highlighted a fully integrated, high-speed packaging line from 51风流S/4HANA, to 51风流Digital Manufacturing, down to Uhlmann鈥檚 automation layer to produce the packaged ginger shot. The ginger shots were moved away from the line by a mobile autonomous robot from Symovo. This use case showed visitors how 51风流supports regulated industries such as pharma and life sciences. 听

Highlighted benefits include increased operational speed with higher throughput thanks to decreased order processing time, built-in regulatory compliance, reduced manual intervention, inventory transparency, and data integrity across the entire production chain.

Top AI functions

• Condition monitoring-led services can enhance asset uptime and service efficiency by combining AI-driven insights and seamless collaboration across the service ecosystem.
• AI-empowered flow analysis enables quick process modeling and engineering optimization.
• Intelligent exception handling is embedded in agent-driven processes.
• Joule’s integrated AI agents can support decision-making throughout the workflow.
• Joule can help power order and line insights.

Humanoid use case

At the final stop before getting their ginger shots, visitors watched an intelligent humanoid robot perform physical tasks at the end of the packaging line, bridging the gap between digital planning and physical execution, highlighting SAP鈥檚 Project Embodied AI.

Benefits of humanoids include increased operational speed with higher throughput due to a decreased order processing time; increased business uptime and cost efficiency especially in areas dangerous or difficult for humans; inventory transparency with real-time data integrity across the warehouse; and physical-digital alignment eliminating misalignment between planning and execution.

Top AI functions

• Joule and Joule Studio can enable robots to understand the physical world, make autonomous decisions, and learn from their environment for smarter operations.

More than a quick refuel

At the end of their visit, visitors got so much more than a quick refuel to slake their thirst. Following the creation of the ginger shot from recipe development and planning to production with mixing, filling, and packing, visitors came away with a clear understanding of how 51风流is connecting insight to execution with trusted orchestration and smarter execution. And, it is this trusted orchestration and smarter execution that is building the resilience every manufacturer needs in today鈥檚 world.

Founded in 1899, NEC Corporation is one of Japan鈥檚 leading technology companies, operating globally across IT services, telecommunications, and digital infrastructure. Over the decades, the company has continuously adapted to new waves of technological change, but today鈥檚 shift is different. Artificial intelligence is not just another innovation cycle; it is redefining how organizations operate at their core.

For NEC, this means rethinking not only technology, but also how work gets done, how decisions are made, and how value is created.

In a recent conversation with Thomas Pfiester, head of Customer Engagement & Adoption and member of the Extended Board of 51风流SE, NEC CIO Toshihiko Nakata shared how the company is approaching this challenge and why becoming an AI-native enterprise requires more than technology.

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NEC鈥檚 journey toward becoming an AI-native enterprise did not begin with AI; it began with a fundamental shift in how the company operates. By rethinking systems, processes, data, and organization as one, NEC laid the groundwork for continuous transformation.

Over time, this meant building a strong digital foundation, standardizing processes, embracing a clean core strategy, increasing transparency, and enabling more connected, data-driven decision-making across the business.

With this in place, NEC moved early to modernize its core systems with . The ambition went beyond cloud migration. It was about creating a more flexible and resilient environment that can evolve with changing business needs while addressing the complexity that had built up over time.

鈥淏y moving to RISE with SAP, we鈥檝e laid the foundation to modernize our corporate infrastructure and speed up our use of AI agents like Joule,鈥� Nakata-san says.

Simplifying that landscape became a strategic priority. Through its clean core approach, NEC is reducing complexity and creating conditions for faster innovation, turning its core into a platform for continuous improvement rather than maintenance.

Building on this foundation, NEC is now accelerating its next phase: scaling AI across the enterprise. Rather than treating AI as isolated use cases, the company is embedding it into everyday work, supporting employees, streamlining processes, and enabling new ways of operating. In collaboration with SAP, NEC is bringing AI closer to where decisions are made, integrating capabilities such as 51风流Business AI and Joule directly into its business processes.

Looking ahead, NEC sees AI as a defining force for the next phase of enterprise transformation. At the same time, Nakata-san emphasizes that realizing that potential requires more than technology. It requires the ability to continuously adapt, and that鈥檚 the cornerstone of NEC success.

Panagiotis Moutas is part of Executive Communications, Customer Engagement & Adoption, at SAP.

Across many enterprises, HR, time, and payroll systems have evolved through years of growth, acquisitions, and regional customization. The result is a patchwork of disconnected tools, duplicated data, and manual handoffs that quietly slow decision-making and increase operational risk. These systems may still 鈥渨ork,鈥� but they carry a hidden cost on productivity, accuracy, and confidence, as expectations on HR continue to rise and AI becomes central to how work gets done.

Fragmentation is the hidden bottleneck behind 鈥渟low鈥� decisions

The impact of fragmentation isn鈥檛 always visible, but it shows up clearly in how decisions get made.

When decisions stall, leaders often point to approvals, governance, or external constraints. In reality, much of the friction happens earlier, when teams reconcile data across systems before decisions can even begin.

According to the research, organizations with unified HR foundations gained faster access to trusted workforce information, generating insights 60% faster and creating new position listings 53% faster. Rather than adding tools, these organizations removed friction by eliminating manual validation, shadow spreadsheets, and repeated checks to confirm data accuracy.

As organizations look to AI to accelerate workforce planning, surface risks, and guide decisions, this foundation becomes even more critical. AI is only as effective as the data it can access and trust. In disconnected environments, AI inherits the same inconsistencies, delays, and gaps, limiting its ability to generate reliable insights and recommendations.

Consider a simple workforce planning decision like headcount approval. In a fragmented environment, HR pulls data from one system, finance validates it in another, and managers reconcile discrepancies in spreadsheets. What should take hours stretches into days鈥攏ot because the decision is complex, but because the data is.

With real-time, consistent workforce information, leaders can act faster and with greater confidence in their decisions. More importantly, unified data allows AI to move beyond reactive reporting to deliver proactive, decision-ready intelligence.

Most payroll errors aren鈥檛 human鈥攖hey鈥檙e structural

Disconnected systems don鈥檛 just slow work; they also increase errors.

When employee data, time records, and payroll information live in different places, every handoff becomes an opportunity for mistakes. Manual reconciliation and corrective actions become routine, especially during high-pressure cycles like payroll close.

Organizations with unified platforms see a clear shift. Payroll error rates drop by 64% and payroll cycles are completed 44% faster by eliminating data gaps and automating validation across connected processes.

This is where AI begins to shift from reactive to preventative. With unified data, AI can identify anomalies before payroll runs, flag potential compliance risks, and continuously learn from patterns across the organization. Instead of fixing errors after the fact, HR and payroll teams can prevent them altogether.

That structural shift changes the nature of work for HR and payroll teams. Payroll teams saw a 21% productivity increase, while HR teams improved productivity by 14%, as time previously spent tracking down discrepancies, correcting entries, and responding to escalations was redirected toward oversight, compliance, and continuous improvement.

Fragmentation quietly erodes trust and limits AI adoption

When systems are fragmented, trust erodes quietly. Employees lose confidence when pay errors occur or self-service tools don鈥檛 reflect their reality. Managers hesitate to act when dashboards conflict. HR teams become intermediaries between systems rather than strategic partners to the business.

Integrated HR, time, and payroll systems reverse this dynamic. Employees gain easier access to self-service tools, with 28% more employees able to directly access HR and time entry platforms. Managers benefit from real-time visibility into approvals and team data. And HR teams regain credibility as the source of accurate, timely workforce information.

Over time, this trust compounds. When people trust the system, they use it. Increased usage improves data quality, and better data strengthens decision-making.

This foundation becomes even more important as organizations scale AI across HR. Employees and managers are far more likely to rely on AI-driven recommendations鈥攚hether for career growth, scheduling, or compensation鈥攚hen they trust the underlying data. Without that trust, even the most advanced AI capabilities remain underutilized.

Fragmentation doesn鈥檛 just slow execution鈥攊t narrows what leaders believe is possible, forcing decisions to be shaped by system constraints rather than business needs.

The cost of standing still

The cost of fragmentation isn鈥檛 just operational; it鈥檚 financial, and it compounds over time.

Across organizations studied, the average annual quantified benefit totaled US$649,400 per 1,000 employees supported, driven by productivity gains, reduced errors, faster cycles, and better business decisions. Over three years,organizations achieved a 284% return on investment, with a payback period of approximately 15 months.

Beyond these quantified gains, there is a growing competitive gap. Organizations operating on unified platforms are not only more efficient, but they are also better positioned to embed AI across the entire employee lifecycle, from hiring and onboarding to development and workforce planning. Those still operating with disconnected systems risk falling behind鈥攏ot just operationally, but strategically.

The real risk isn鈥檛 innovation

Innovation draws attention because it鈥檚 new, visible, and often disruptive. Fragmentation, by contrast, builds quietly in the background until it starts to limit how the organization operates. But as organizations ask HR to deliver more鈥攂etter insights, faster planning, stronger compliance, and improved employee experiences鈥攖he limits of disconnected systems become harder to ignore.

Modern HR outcomes don鈥檛 come from layering new tools on top of outdated foundations. They come from reducing complexity, unifying data, and creating consistency across the most essential people processes. This is where platforms like 51风流SuccessFactors are evolving鈥攏ot just to unify core HR, time, and payroll, but to embed AI directly into the flow of work. By combining a trusted data foundation with AI-driven insights and automation, organizations can move from reactive operations to predictive, insight-led workforce management.

The question isn鈥檛 whether organizations can afford to modernize HR. It鈥檚 whether they can afford to limit the impact of AI by building on fragmented foundations.

AI doesn鈥檛 transform HR on its own; it amplifies what鈥檚 already there. And without a unified, trusted core, even the most advanced AI will struggle to deliver on its promise.

Learn how leading organizations are reducing fragmentation and building a strong foundation for AI by unifying core HR, time, and payroll with .

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Lara Albert is chief marketing officer for 51风流SuccessFactors.

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Artificial intelligence is creating new opportunities for social innovation鈥攂ut many young entrepreneurs are still navigating how to use it effectively.

According to a global study conducted by The Possibilists, a global alliance for youth innovation and partner of ChangemakerXchange, more than 60% of young impact entrepreneurs believe AI can benefit their work, society, and the broader economy. At the same time, 70% of these innovators say they lack support in navigating AI tools. Through a long鈥憇tanding collaboration, 51风流and ChangemakerXchange bring together young social entrepreneurs with 51风流volunteers and professionals to exchange knowledge, explore practical use cases, and build confidence in applying AI responsibly. Matthias Scheffelmeier, co-founder of ChangemakerXchange, and Alexia von Salomon, learning designer at Education Innovation Labs and a changemaker in the European cohort, discuss which skills are essential in an AI-driven future and how AI can help improve efficiency and scale social impact.

Learn more.

鈥淩eoassunto provides dedicated support for reintegration,鈥� Proietti Pantosti said. 鈥淥ur goal is to significantly reduce the rate of reoffending among first-time convicts.鈥� As processes for reintegration are complex and time consuming, he had the idea to set up an offline, server-based AI tool to help inmates with job applications as well as an AI agent to automate the complex tax paperwork for companies that offer jobs for inmates. But he and his organization didn鈥檛 have the skills or funds to create an AI prototype to realize his concept.

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A community of changemakers

This is when came in, a global support community for young social entrepreneurs and a long-standing partner of SAP. In 2025, this organization established a for social entrepreneurs and NGOs to experiment with AI capabilities and implement AI tools and features to fix one challenge common to all social enterprises: a lack of helping hands in combination with a large volume of small, sometimes repetitive tasks.

According to Matthias Scheffelmeier, co-founder of ChangemakerXchange, young changemakers are tackling the most pressing issues of our time but are often stretched and under-resourced. 鈥淲e believe helping them mindfully and ethically adopt AI tools allows them to focus on their key expertise and therefore scale their impact in the world,鈥� he said. 鈥淭o address this, the ChangemakerXchange AI program provides customized support, in-person gatherings, and a public toolkit to help young entrepreneurs navigate AI.鈥�

As the longest-standing corporate partner, 51风流has supported social enterprise ChangemakerXchange for more than eight years. Beyond just financial support from the company, 51风流employees joined local cohorts of social enterprises, shared knowledge on AI, and brainstormed how individual ideas could be brought to life.

ChangemakerXchange initiated the Possibilists, a global alliance for youth innovation. on the needs and challenges young change makers face with AI. The study showed that while 65% use AI almost daily, 70% lack knowledge on how to navigate AI tools proactively for their purpose.

From environment to politics

Entrepreneurs in the European cohort of the ChangemakerXchange AI program cover environmental, social, and political projects.

One of them, Romania-based social enterprise Station Europe, aims to make democracy accessible, especially for young people from rural areas. 鈥淲e empower young people to engage in participatory democracy, embrace creative activism, identify and address disinformation campaigns, and design policy recommendations that reflect their communities鈥� needs,鈥� said Alin Gramescu, president & co-founder of Station Europe. To support these goals, the organization launched a collaborative platform in 2024 called that allows young people to explore new formats of political participation, taking them right into the heart of the policymaking process. Participants in hands-on workshops learn how to start from an actual issue or need and create a policy recommendation鈥攚ith AI clustering and processing workshop findings. This results in recommendations for government authorities based on the input of thousands of young people.

鈥淎I will help connect policymakers and young people. Within one year, we condensed more than 1,400 papers from over 80 workshops,鈥� Gramescu said. 鈥淥pening the platform to additional countries will exponentially increase the volume of data we will be dealing with.鈥� When asked for the value ChangemakerXchange added for his organization, he said 鈥淚 knew what I wanted to build to manage this content, but I needed the step-by-step technical guidance to make it happen.鈥�

Education as foundation for progress

Education is often described as the cornerstone of progress, and for Alexia von Salomon, concept & learning designer at Education Innovation Lab, this belief is her daily motivation.

鈥淔or me, education is the foundation for social innovation,鈥� von Salomon said. As a leader in educational transformation, she sees a lack of relevant future skills conveyed at schools in Germany and aims as high as transforming Germany鈥檚 education system.

Besides conducting workshops at schools, she creates learning experiences for teachers and pupils, like the learning platform 鈥渄igital sparks for the future.鈥� To scale reach, Education Innovation Lab focuses on self-guided learning platforms and train-the-trainer sessions for school teachers.

von Salomon uses AI to co-create and validate new concepts. 鈥淭his helped me to be more creative and think outside the box,鈥� she said. 鈥淯sing AI for early testing how minors would interact with learning content and tools reduces the iterations we need before actually conducting tests in schools.鈥�

She said that being part of the ChangemakerXchange program not only gave her the opportunity to get to know the right people in the tech industry, but to shift her perspective on AI and increase her use of AI tools. Her personal goal is to shape a future where learning is not just about knowledge, but about empowerment and transformation. 鈥淔rom my perspective, key skills for minors in a future influenced by AI will be creativity and critical thinking鈥攖o use the opportunity AI offers without suffering from the potential negative impacts,鈥� she said.

Serving business and society

More than 1,500 social entrepreneurs in over 130 countries are part of ChangemakerXchange鈥檚 global community. 鈥淭rue innovation happens when changemakers challenge the status quo and create solutions that serve both business and society,鈥� Scheffelmeier emphasized. For him, social enterprises are not just businesses, but catalysts for inclusive growth and sustainable impact. 鈥淏y combining technology with the vision of social innovators, we can scale solutions that address global challenges and build a future where profit and purpose go hand in hand,鈥� he said.

To succeed, manufacturers need more than incremental improvements or siloed optimizations. They need to orchestrate their operations end to end with connected processes and trusted data, so they can respond faster to change, operate more efficiently, remain compliant, and continue to grow鈥攅ven as disruption is constant.

At Hannover Messe 2026, the world鈥檚 leading stage for industrial transformation, 51风流will introduce a new set of AI鈥憄owered manufacturing and supply chain innovations. These innovations help companies ensure business continuity by orchestrating people, processes, and technology across their extended enterprise, turning volatility into an opportunity for resilience, efficiency, and customer impact.

From AI insight to AI in execution

For years, manufacturers have invested in analytics and dashboards to improve visibility. But visibility alone does not prevent disruption. What鈥檚 required now is AI embedded directly into core business processes, where intelligence can analyze alerts, reason over business impact, and provide real-time solutions to resolve issues. With agentic AI, companies are now able to go a step further: automating the right actions for the best outcomes, with humans remaining in the loop wherever critical decisions are required.

51风流is operationalizing AI at industrial scale by embedding AI agents directly into supply chain and manufacturing workflows and contextualizing them with trusted enterprise and network data. Built on harmonized industrial, transactional, and network data, these agents can move beyond analysis to real鈥憈ime prediction and execution, working to deliver resilience, regulatory readiness, and measurable customer impact from day one. Creating tangible ROI is what matters most鈥攚hether by reducing unplanned downtimes, scrap, and rework, or by increasing quality and ultimately production output.

Orchestrating the supply chain end to end with AI

At the center of SAP鈥檚 focus at Hannover Messe is .

51风流helps manufacturers connect processes and data not only across internal teams, but also across company boundaries鈥攚ith suppliers, logistics partners, and service providers. By using AI agents to connect design, planning, procurement, manufacturing, logistics, service, and asset management鈥攁nd by integrating seamlessly with ERP and line-of-business systems鈥�51风流helps break down silos that slow decision-making and increase operational risk.

This new agentic orchestration is powered and governed by a portfolio of intelligent applications that act, not just analyze, enabling faster, more coordinated responses without sacrificing quality, control, or growth.

New AI agents redefining planning, service, and operations

At Hannover Messe 2026, 51风流will showcase AI agents that help manufacturers and operators reduce time to value, stabilize operations, and improve service levels amid ongoing disruption. As a precursor to broader announcements planned for 51风流Sapphire, these agents demonstrate how agentic AI delivers practical benefits across all supply chain domains. Here are a few examples:

Manufacturing

• Production Master Data Agent helps automate and optimize the creation and maintenance of production master data. By leveraging the bill of materials, the agent can generate production routings鈥攊ncluding operations and work centers鈥攁nd help ensure components are correctly assigned across the production process. This helps reduce manual effort, accelerate production setup, and keep production data accurate as requirements change. General availability is planned for Q2 2026.
• Production Planning and Operations Agent enables planners to release production orders using natural language while automatically validating material availability, capacity, and scheduling constraints. Joule provides recommendations鈥攕uch as alternative components or rescheduling options鈥攖hat planners can review and approve, reducing manual work and keeping production aligned with real鈥憌orld conditions. General availability is planned for Q2 2026.

Assets & services

• Field Service Dispatcher Agent can improve service responsiveness and asset uptime by dispatching the right technician based on skills, location, asset condition, and priority鈥攄riving faster resolution and better workforce utilization. General availability is planned for Q2 2026.
• Alert Processing Agent can enrich operational alerts using past incidents, resolutions, and contextual signals and recommend clear, data鈥慸riven actions to help teams resolve issues faster and improve operational reliability. General availability is planned for Q3 2026.
• Asset Health Agent analyzes time鈥憇eries health indicators to assess and summarize the current and projected health of individual and multiple technical objects. By forecasting when assets are likely to become critical and alerting users in real time, the agent supports condition鈥慴ased maintenance and helps minimize downtime while ensuring asset availability. General availability is planned for Q3 2026.

AI agents advancing logistics execution

• Material Reservation Agent helps ensure materials are available when and where needed by automating reservation creation and maintenance based on business rules鈥攔educing delays, improving inventory accuracy, and optimizing working capital. General availability is planned for Q2 2026.
• Outbound Task Orchestration Agent can protect customer service levels by detecting and resolving picking and packing issues in real time, orchestrating corrective actions to support on鈥憈ime, accurate delivery. General availability is planned for Q2 2026.

Aligning workforce, logistics, and assets in real time

Operational resilience also depends on synchronizing people with all other resources as conditions change.

With , skills, certifications, availability, and labor rules are aligned with real-time operational demand so workforce plans can adjust automatically as production changes.

In logistics, , together with the new solution, helps organizations reduce transportation costs, accelerate warehouse execution, and improve delivery performance. Using conversational interaction with Joule, order managers can prioritize fulfillment while automatically accounting for availability and scheduling constraints.

Asset and quality operations also benefit from embedded intelligence. AI-assisted anomaly detection and alert processing in helps teams identify risks earlier, prioritize actions, and reduce unplanned downtime. In parallel, 51风流Document AI can automate the , improving throughput, data quality, and compliance at scale.

Regulatory readiness and what鈥檚 next

As regulatory requirements tighten, 51风流is expanding support for Digital Product Passports as part of , aligned with the EU鈥檚 Ecodesign for Sustainable Products Regulation (ESPR). These capabilities help manufacturers create ESPR鈥憆eady product records capturing environmental impact, material composition, repairability, and recyclability data. General availability is planned for Q2 2026.

Expanded 51风流Business Network capabilities also deliver built鈥慽n e鈥慽nvoicing compliance and data-residency support, enabling secure partner collaboration, synchronized logistics, and improved delivery performance across global networks.

See it live at Hannover Messe 2026

Taken together, these innovations reflect a shift from reactive management to intelligent execution鈥攚here AI is embedded directly into the processes that keep manufacturing and supply chains running today while laying the foundation for the next wave of innovation that will be unveiled at 51风流Sapphire.

Visit 51风流at booth F08 in Hall 15 at Hannover Messe 2026, April 20鈥�24, to see how AI-infused orchestration, embedded AI agents, and end鈥憈o鈥慹nd supply chain applications are redefining manufacturing.

Dominik Metzger is president and chief product officer for 51风流Supply Chain Management.

With the听听1H鈥�2026 release,听we鈥檙e听deepening those connections across the HR lifecycle. This release focuses on听four听core priorities:听connected,听suite-wide听AI; unified experiences that adapt to how organizations work;听processes designed for clarity, accuracy, and compliance; and stronger foundations for skills and long-term growth.听Together, these innovations help organizations听anticipate听needs earlier, reduce friction in daily work, and move forward with greater confidence.听

Connected AI that works across HCM

AI in HR delivers the greatest impact when it works continuously across the entire workforce lifecycle鈥攏ot as isolated features, but as connected capabilities that share context and insight.

The 1H鈥�2026 release expands听suite-wide听agentic AI听across 51风流SuccessFactors solutions, helping听employees听get clearer answers, act sooner, and keep听work moving听across roles and responsibilities.听A connected network of听听now supports areas such as recruiting, workforce administration, payroll, learning, performance, and talent development鈥攚orking together behind the scenes to help听anticipate听next steps and surface relevant guidance.

This release also introduces a growing听workforce knowledge network, bringing trusted external expertise and research directly into the flow of work through Joule.听Teams can now access expert-backed global employment guidance and听research-driven听insights without leaving their workflows鈥攕upporting听faster, more听confident decisions.

To听further听support learning in the flow of work,听intelligent Q&A in听听now helps employees find information more easily. AI听can deliver instant,听context-aware听responses drawn directly from an organization鈥檚 learning content,听along with relevant links and resources,听so employees can get answers quickly without searching through courses or documentation.听

Unified experiences that adapt to how work gets done听

As HR听tasks听become more embedded in听day-to-day work, experiences need to feel intuitive, connected, and responsive听wherever work happens. In the 1H 2026 release,听51风流SuccessFactors solutions continue to unify experiences across the suite, giving employees, managers, and HR teams what they need听in听the moment.听

• Connected recruiting and onboarding:听Native integration between听 solutions, , and听听can bring AI-enabled听recruiting, core HR, and onboarding together into a single, continuous experience, helping hiring teams move faster while听maintaining听consistency from candidate through new hire.听

• Tailored experiences,听built faster:听The new听extensibility wizard听can provide guided, step-by-step support for creating custom extensions on听听(51风流BTP) directly within听SAP听SuccessFactors solutions, making it easier to adapt experiences to unique business needs while preserving governance.听
• Simpler, clearer employee moments:听A redesigned, configurable 401(k) experience听in听听for U.S.听employees helps simplify enrollment and management by clearly explaining employer contributions and guiding deferrals and beneficiary setup, helping employees make informed decisions with confidence.听

Processes designed for clarity, accuracy, and compliance听

In the 1H鈥�2026 release, 51风流SuccessFactors introduces new capabilities that help organizations bring greater clarity and rigor to pay practices.

With听pay听transparency insights听in the , organizations can analyze compensation patterns and potential pay gaps, supporting transparent, data-driven pay practices in-line with evolving regulatory expectations,听including in the EU.听

Skills governance听for sustainable growth听

Preparing for听what鈥檚听next requires trusted, consistent skills data that organizations can rely on across HR, talent, and workforce planning.

In the 1H鈥�2026 release,听we are听strengthening听the听听with enhanced听skills governance, providing a centralized interface to help manage skills, apply governance standards, and ensure alignment across 51风流SuccessFactors solutions and partner applications. This helps organizations improve听skills听data quality, maintain consistency at scale, and make more confident,听skills-based听decisions.听

A connected foundation for the future 

This听release听reinforces听SAP鈥檚 continued focus on an intelligent, connected HCM听foundation鈥攐ne designed to evolve with your organization and support confident decisions at every stage of work. By bringing together data, AI, and experiences across the HR lifecycle, these听enhancements help organizations reduce friction today while听laying听the groundwork for听tomorrow.

To explore what鈥檚 included in this release, check out the or watch the overview .

Bianka Woelke is group vice president and head of Application Product Management for 51风流SuccessFactors.

But new research from 51风流and Wakefield* suggests a different reality is emerging. AI isn鈥檛 making early talent irrelevant. Instead, it鈥檚 accelerating how quickly they become productive, reshaping the earliest stages of work, and raising expectations far earlier in the employee lifecycle.

According to the findings, 88% of CHROs say AI is making early-career talent role-ready faster. This acceleration raises the stakes on both sides. While organizations benefit from faster productivity and earlier impact, early鈥慶areer employees are entering roles with heightened expectations and fewer traditional learning buffers鈥攆orcing leaders to rethink how success is defined and supported from day one.

AI as an accelerator of readiness

Entry-level roles have long relied on repetitive, lower-stakes tasks that helped new employees learn how work gets done. Today, AI automates much of that foundational execution.

This shift is increasingly common: 79% of surveyed CHROs report that their early-career talent receives enterprise AI tools within their first month on the job. Additionally, 87% expect new hires to be comfortable with AI on day one or learn the tools immediately after joining.

With AI absorbing traditional tasks, early-career talent is stepping into meaningful work sooner鈥攁nd CHROs are already seeing the impact, with 56% reporting improved confidence and 55% citing increased productivity among those using AI.

This acceleration reflects themes we first explored in the 2025 51风流SuccessFactors Future of Work Predictions , where we examined how AI might reshape entry鈥憀evel roles. As foundational tasks continue to be absorbed by AI, the question becomes not whether early鈥慶areer roles will exist, but how organizations can redesign them to build capability in new ways.

When productivity accelerates, expectations follow

As early talent ramps faster, the expectations placed on them are rising just as quickly. Several structural factors are contributing to this shift: organizations are hiring fewer early-career talent, and those who do join are expected to take on more complex work earlier in their tenure. Our upcoming research from our makes this clear, as one research participant summarized, 鈥淓ntry level roles used to be focused on mundane tasks鈥攚hat should they do now? They bring an incredibly unique perspective; we want to hire early talent to challenge our norms and help us find better ways of working.鈥�

But with AI removing the mundane work, it may also remove many of the gradual, hands-on learning moments that once helped new hires build experience over time.

With these rising expectations, it鈥檚 easy to see how the cognitive load of entry level roles could increase substantially. CHROs report heightened performance pressure and increased mental effort as new hires try to keep pace with AI-accelerated work. Some researchers refer to this dynamic as 鈥�,鈥� the cognitive strain that comes from managing rapid, AI-driven workflow.

Together, these shifts create several risks for both employees and organizations:

• Shadow AI use rises: 56%of CHROs say early-career talent turns to unsanctioned AI tools when formal guidance is unclear. This behavior may reflect entry-level hires trying to keep pace rather than intentionally breaking policy.
• Inconsistent enablement creates talent risk: 44% of CHROs say uneven access to AI tools increases attrition risk, especially for early talent who may feel unable to live up to new performance expectations without tools to automate routine tasks.
• Foundational skills may erode: Even as AI boosts productivity, 38%of leaders worry early-career talent are not building long-term skills like communication, critical thinking, judgment, and collaboration. That concern is echoed in qualitative feedback from HR leaders as well. As one noted, 鈥淲e鈥檝e observed gaps in professionalism in business settings for entry鈥憀evel talent, from collaboration and stakeholder management [to] ownership and accountability.鈥�

Rethinking the first step into work

As traditional early鈥慶areer learning pathways narrow, organizations must now redesign how those learning moments happen. Our research points to several areas where HR leaders can intentionally strengthen the early-career ramp:

1. Build foundational skill development intentionally.

As repetitive tasks disappear, organizations have the opportunity to deliberately create new ways for early talent to build communication, collaboration, critical thinking, and decision-making skills. This can include structured, project-based experiences, clearer decision-making frameworks, and more frequent coaching that focuses on judgement and prioritization, not just task completion.

2. Design entry-level roles around higher-value work.

Early-career employees are capable of contributing more strategically when roles are designed with the right balance of scope and support. Redesigning entry鈥憀evel positions to include clear ownership鈥攕upported by explicit expectations, mentoring, and well鈥慸efined guidance for decisions and escalation鈥攈elps early鈥慶areer talent build confidence while managing risk.

3. Establish AI governance from day one.

Without clear guidance, early talent may struggle to understand how to use AI responsibly. Introducing AI expectations during onboarding, reinforcing role-specific best practices, and normalizing manager-led conversations about AI use can reduce shadow AI and build trust in new technologies early on.

4. Ensure equitable AI access across teams and managers.

As expectations rise, uneven access to AI tools can quietly increase workload pressure and stress for early-career employees. Providing consistent access, training, and enablement helps ensure new hires are equipped to meet accelerated demands without increasing burnout or attrition.

The bottom line

AI isn鈥檛 eliminating early-career talent from the workforce; it鈥檚 reshaping the path they take to become effective and increasing the value of the work they contribute. While entry-level roles may be fewer, expectations for impact are higher, placing greater importance on pairing AI fluency with strong human skills. For new graduates, developing both will not only help them land a job but also enable them to contribute quickly and build lasting capabilities.

When early鈥慶areer talent becomes productive sooner, companies can move faster, innovate earlier, and operate more efficiently, but only if that speed is matched with structure, coaching, and intentional development. Organizations that navigate this transition successfully will ensure early talent doesn鈥檛 just ramp up faster, but also builds the judgment, collaboration, and critical鈥憈hinking skills that AI can鈥檛 replace.

To stay on top of more upcoming research on the impact of AI on entry-level roles, visit our .

Lara Albert is chief marketing officer for 51风流SuccessFactors.

*The 51风流AI Talent Survey was conducted by Wakefield Research (www.wakefieldresearch.com) among 100 US CHROs (or CPO equivalent) at organizations with a minimum annual revenue of $500m where employees are using AI-enabled tools in their day-to-day responsibilities, between February 19th and March 2nd, 2026, using an email invitation and an online survey.

The 11th cycle of the Hasso Plattner Founders鈥� Award saw an evolution of the award itself. With a refined structure and this year鈥檚 strong thematic focus on AI, the award now recognizes achievements in two categories: Emerging Ideas, honoring visionary concepts that explore new architectural directions and long-term opportunities for customers and the business, and Scaling Innovation, celebrating innovations already delivering proven impact at scale.

The jury received a total of 254 submissions from all over the globe, from which 41 finalists representing nine different countries were chosen. Six teams made it to the final round, highlighting the breadth of innovation across teams worldwide.

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The winning teams were formally recognized and celebrated during a red carpet award ceremony on March 26 at 51风流headquarters in Walldorf, Germany. Executive Board Members Christian Klein and Sebastian Steinhaeuser introduced the finalists and announced the winners in the Emerging Ideas and Scaling Innovation categories, respectively. 

Emerging Ideas winner: 51风流Cognitive Twin Enterprise

The Emerging Ideas category honors bold thinking and visionary concepts that explore the future of enterprise software. This year鈥檚 winner, 51风流Cognitive Twin Enterprise (51风流CTE), embodies this forward-looking spirit by presenting a new way of how organizations plan, simulate, and execute in an increasingly complex and fast-changing world.  

51风流CTE introduces the idea of an ever-learning, AI-powered intelligence layer built on a continuously updated model of the entire organization. It unifies data, simulation, and AI on SAP鈥檚 foundation to help deliver guided autonomy across functions, supporting the shift from keyboard-centric SaaS to governed decision-making and agent-led execution. 

Acting as a constant observer of the business landscape, 51风流CTE evaluates an organization鈥檚 position against anticipated trends and potential changes. It runs what-if simulations and provides governed recommendations on 51风流applications and data across finance, spend, supply chain, HR, and customer experience, with selective, low-risk auto-execution and human-in-the-loop control for high-risk steps. By doing so, it can transform ERP into an AI-native system of foresight and elevates workforce intelligence. 

The solution helps organizations move from reacting after events occur to proactively and continuously testing scenarios, anticipating risks, and evaluating options. This provides the information they need to make critical decisions, allowing them to anticipate what鈥檚 next, shape it, and execute in a single, connected environment.  

鈥淲inning the Hasso Plattner Founders’ Award validated 51风流Cognitive Twin Enterprise鈥檚 vision,鈥� Natalia Aksakova, Strategy & Portfolio at Global Finance and Administration, says on behalf of the team. 鈥淚t reinforced that we are on the right path and gives us the momentum to bring the next era of ERP to life faster, with the ambition to help define how organizations operate in the years ahead.鈥� 

Scaling Innovation winner: 51风流Document AI

The winner in the Scaling Innovation category demonstrates how breakthrough innovation becomes truly transformative when it is embedded into everyday business processes and adopted at global scale. The 51风流Document AI solution can fundamentally change how organizations process and understand the vast volume of documents that power daily operations.

Across industries, enterprises continue to grapple with the rapid growth of unstructured data. Invoices, purchase orders, contracts, shipping documents, and many other business records still require significant manual handling in many organizations, creating bottlenecks, delays, and avoidable errors. The 51风流Document AI team addressed this challenge by bringing intelligent document processing directly into core business applications, enabling customers to automate document workflows seamlessly and securely.

What sets this achievement apart is not only the technological innovation but the scale of real-world adoption. The solution has become deeply embedded across SAP鈥檚 portfolio and is used by tens of thousands of customers worldwide to process billions of documents. By integrating advanced AI capabilities directly into existing workflows, the team has made automation accessible without the need for complex integrations or specialized expertise. This approach enables organizations to accelerate business processes, reduce manual effort, and improve the quality and speed of decision-making.

The award recognizes the team鈥檚 ability to translate research excellence and engineering innovation into measurable business impact. Their work demonstrates how embedded AI can move beyond experimentation to become a trusted and reliable component of everyday enterprise operations. By operationalizing AI responsibly and at scale, the team has helped strengthen SAP鈥檚 position as a leader in enterprise automation and intelligent applications.

Equally important is the long-term perspective behind the innovation. The continued evolution of document understanding capabilities, combined with growing adoption across SAP鈥檚 platform, illustrates how scalable AI can serve as a foundation for future innovation. The recognition celebrates not only the impact already achieved but also the momentum created for the next generation of intelligent enterprise processes.

鈥淲inning this award is a tremendous honor for our team,鈥� Tobias Weller, chief product owner and team lead, says. 鈥淚t validates years of hard work, close collaboration, and a shared belief in the transformative potential of AI to accelerate essential business processes and capture true business value for our customers.鈥�

Celebrating innovation across the AI spectrum

The Hasso Plattner Founders鈥� Award has long celebrated the people and ideas that drive 51风流forward. By recognizing both scaled impact and visionary thinking, the award highlights how innovation thrives at every stage of the journey鈥攆rom early exploration to global adoption. It underscores the belief that long-term success depends on both delivering value today and continuously reimagining what is possible.

At the ceremony in Walldorf, employees around the world came together or joined virtually to celebrate the winning teams and the many contributors who helped bring their ideas to life. Their work reflects the creativity, dedication, and passion that define SAP鈥檚 culture of innovation. As the company continues to advance its AI-driven strategy, this year鈥檚 winners demonstrate how teams across the organization are turning ambition into reality鈥攈elping customers run better, adapt faster, and prepare for the future.

The winning teams will be given the opportunity to pitch their project to the Executive Board in 2026. The projects will be recognized in the permanent Founders鈥� Exhibits in Walldorf and Palo Alto. In addition, the members of the winning teams will receive a personalized trophy.

ANYbotics, a Swiss robotics company, has stepped into this space with a vision to shape a safer future for industrial inspection, one where robots operate as autonomous members of the inspection team, running inspection operations integrated into plant maintenance workflows.听

This vision is embodied in the company鈥檚 鈥淎NYmal鈥�: a four-legged inspection robot designed specifically for heavy industry.

Unlike general-purpose robotics platforms, ANYmal is engineered to operate in 鈥渂ig, dirty, dusty, and dangerous鈥� environments, says Nicole Zingg, director of Technology Partnerships at ANYbotics. Places where stairs, corrosion, heat, and unreliable connectivity are the norm, not the exception.

But hardware, Zingg says, is only one part of the puzzle that makes ANYmal indispensable to customers.

Inspection robotics is about data

鈥淲e build a hardware platform,鈥� Zingg explains, 鈥渂ut inspection robotics is really about data that is consistent and trustworthy.鈥�

ANYmal autonomously navigates industrial sites to collect data that goes beyond what a human can collect alone. Beyond just visual inspection, its sensors also collect multi-modal data, including thermal imaging, ultrasonic leak detection, gas concentration detection, acoustic anomaly detection, and more. The observations are fed into what ANYbotics calls 鈥渋nspection intelligence,鈥� which transforms the collected data into actionable operational insights. The result is higher uptime, longer asset lifecycles, and, most importantly, safer working conditions for humans.

ANYmal can make a huge impact on operations. One offshore wind customer, Zingg says, has used ANYmal to manage all inspections and has eliminated the need to send personnel to a remote platform for months. When human intervention was eventually required, ANYmal鈥檚 data from prior inspections made all the difference. The customer already knew exactly what was wrong, which expert to send, and what equipment to bring鈥攁voiding costly and risky trial-and-error site visits.

Yet for ANYbotics, delivering insights is not enough if those insights are not integrated in the software systems customers use.

鈥�51风流is where ANYbotics needs to be native鈥�

Through extensive user research, ANYbotics discovered that many plant operators, maintenance managers, and field service teams already run their daily operations in SAP. Work orders, asset histories, performance trends, and decisions all flow through 51风流systems. 鈥淚f customers are using SAP, 51风流is where ANYbotics needs to be native,鈥� Zingg says.

Meanwhile, SAP鈥檚 Project Embodied AI was looking for robotics companies to partner with. The project focuses on extending the impact of 51风流Business AI into physical operations by enabling robots to autonomously perform complex tasks with an understanding of the broader business context.

It was clearly a perfect fit and has delivered advantages for both companies.

On the system side, a continuous, unbroken digital thread connects ANYbotics insights from industrial inspections to data in 51风流systems, helping inform key business and operational decisions across the organization.

For end users, embedding ANYmal directly into familiar 51风流workflows can also help ease adoption, since introducing robotics into already stretched industrial workforces can trigger anxiety. Concerns about job security, workflow disruption, and complexity are common, but embedding ANYmal directly into familiar 51风流workflows can help reduce that friction, Zingg explains.

Treating robots as part of the workforce

The first major integration point was听. Rather than sending only human technicians, customers can now dispatch work orders directly to ANYmal as they would to any other field team member. The robot then autonomously executes inspection tasks, gathers data, and reports the results directly back into a company鈥檚 51风流system.

From there, the integration expanded into asset-related scenarios and is now moving toward broader enablement via 51风流Business Technology Platform (51风流BTP), with the goal of allowing robot-generated data to land wherever customers need it in their 51风流landscape.

The ambition is not to force humans to adapt to robots, but for robots to adapt to human workflows. 鈥淎NYmal has to put data in the 51风流system, just like human team members,鈥� Zingg notes. ANYmal becomes another worker in the same operational system of record.

Project Embodied AI in practice

This combination of ANYbotics robotic technology with 51风流bridges the gap between physical operations and enterprise applications and tangibly reflects the goal of Project Embodied AI.

On the 51风流side, AI agents operate on ANYmal鈥檚 robotic systems to execute physical tasks, such as safety inspections.

On the ANYbotics side, ANYmal is a physical object that moves through space, perceives its environment, and acts within real-world constraints. ANYmal uses 51风流historic and time-series data to inform decisions while at the same time remaining fully autonomous even in environments with no connectivity.

It鈥檚 important to note, Zingg stresses, that ANYbotics has control over ANYmal鈥檚 behavior and inspection execution, while 51风流has control over the business context such as work orders, asset data, or operational priorities. It is the 51风流business context that informs how ANYmal鈥檚 insights are consumed and acted upon while ANYbotics controls ANYmal鈥檚 physical interactions.

Scaling safely and responsibly

Today, more than 200 ANYmal robots are already in productive use worldwide, with inspection deployments in heavy-industry environments that would otherwise require constant human exposure.

Safety remains central to ANYbotics. Each deployment includes extensive testing and an on-site field engineer who helps ANYmal learn and validate its environment and trains customer teams on safe operational procedures. While ANYmal is built to work independently, humans remain firmly in the loop.

A glimpse into the future

As industries face labor shortages and aging workforces, undocumented expertise can all too often be lost. With autonomous inspection robots such as ANYmal, this knowledge is captured and turned into programs that can run day in and day out across multiple sites. The captured data flows into 51风流to become organizational intelligence that survives any workforce turnover.  

ANYbotics鈥� partnership with 51风流shows that this combination of robotics and enterprise software is moving swiftly from the experimental stage to real-world implementation.

In the future, industrial inspection will be powered by AI, not as disembodied dashboards or isolated machines, but as an integrated intelligent system where physical robots and digital workflows in 51风流systems operate as one.

In that future, robots like ANYmal are no longer novelties. They are coworkers, albeit mechanical four-legged ones, quietly extending human capability into places humans were never meant to go. These robots, together with SAP, are shaping for a future where dirty, dangerous, and dusty industrial inspections are being transformed into business insights.

Top image courtesy of ANYbotics

SafetyGuard was created as part of a program at UTUM鈥檚 Digital Product School鈥攚here teams of selected students work on real-world challenges鈥攊n just 12 weeks by a student team, 鈥淢IDAS,鈥� and 51风流Research & Innovation. This project illustrates just how effective cross-location collaboration with the ecosystem can be in rapidly creating prototypes as a foundation for product development at SAP.

Embodied AI: a joint focus of innovation

The objective of this particular prototyping project was to identify use cases in which robotics and AI could be seamlessly integrated into business processes. Based on its research and on user studies, team MIDAS pinpointed the reliable detection and documentation of safety risks as one such use case.

Safety inspections are essential in many industries, but they are often time-consuming and error-prone. SafetyGuard could change that: leveraging embodied AI, it makes inspections faster, more efficient, and more reliable, without increasing the workload for employees.

Embodied AI鈥攖he integration of artificial intelligence into physical robot systems鈥攚ill be a focal point of investment and development work at 51风流going forward.

SafetyGuard combines two technologies: modular robotics and AI-powered autonomy. In this prototype, robots, such as drones and humanoid systems capable of inspecting work environments without human intervention, are equipped with a specialized AI model that is trained, for example, to detect where protective equipment is missing and to automatically document safety-related incidents. What鈥檚 more, the robots can multitask. While they are carrying out inspections, they can transport materials and monitor machinery鈥攁n approach that combines efficiency gains with increased safety levels.

鈥淪afetyGuard demonstrates just how effective our ecosystem approach is. In this project, an 51风流team in Potsdam and a group of students in Munich joined forces and very quickly built a prototype that will have a real impact on product development,鈥� Tobias Riasanow, head of Ecosystem Development at 51风流Labs Germany, says. 鈥淚t鈥檚 the perfect example of what 51风流understands by 鈥榚cosystem development.鈥欌��

The project is also strategic to 51风流in that SafetyGuard addresses real-life industry requirements and complements SAP鈥檚 solutions for environment, health, and safety management. The prototyping approach that led to SafetyGuard could therefore become part of the 51风流portfolio in the future to help further reduce the time it takes to get from an idea to a product.

Programs with impact

To date, 13 prototypes have been developed for 51风流under programs run by UTUM, all in close collaboration with product teams at 51风流and directly related to their respective road maps. The programs offered by UTUM include:

• Innovation Sprint: Here, students have just one week to work on prototypes for solving specific user challenges. The most recent sprint, The Future of Retail with 51风流Joule, produced five such prototypes, including solutions for intelligent inventory optimization, virtual shelf monitoring, and retail assistance systems.
• Digital Product School: This 12-week program for students is designed as a platform for developing executable software prototypes. One prototype created out of this program was Carbon Data Exchange, which is now part of SAP Sustainability Control Tower. Another is an application that makes it easier for developers to access the extensive documentation for SAP Field Service Management. Instead of wasting valuable time searching, they can simply type their questions into a chatbot and receive helpful answers, including code examples and direct links to the documentation they need.
• Multistakeholder projects: Additional prototypes have been created in longer-term programs such as Digital Hub Mobility and Circular Republic. Programs like these bring together experts from companies, startups, and research institutions over several months and allow 51风流to test innovations in real-world customer and partner environments at an early stage in their development.

Co-innovation gets results鈥攆aster

The collaboration between 51风流and UTUM shows how quickly ideas can lead to tangible results when students, researchers, and 51风流teams work together to apply scientific approaches to real-life industrial challenges. SafetyGuard is an example of how embodied AI innovations can be created and how different groups of experts can benefit from one another.

鈥淪afetyGuard demonstrates the extensibility of SAP鈥檚 approach to embodied AI. SAP鈥檚 embodied AI layer integrates the business context and triggers actions across the suite. SafetyGuard鈥檚 AI-native, manufacturer-agnostic design is scalable across different use cases and enables multitasking, allowing, for example, robots to process safety incidents while performing other tasks such as industrial asset inspections. SafetyGuard is a proof point for 51风流for the added value of using cognitive robotics in safety scenarios.鈥�

Adelya鈥疐atykhova and Dr.鈥乽kasz鈥疧strowski, Initiators and Supervisors of the student challenge

This first appeared on the German 51风流News Center.

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Team Liquid, the world鈥檚 largest esports organization, is turning to Joule to transform how it manages the vast amounts of data generated in competitive gaming.

I鈥檓 pleased to announce that next鈥慻en 51风流Ariba is now available, marking the next phase in SAP鈥檚 journey to reimagine source鈥憈o鈥憄ay for the age of AI. This milestone represents the transition from announcement to execution, bringing a fundamentally rebuilt platform into customers鈥� hands.

This milestone comes alongside strong industry recognition. 51风流has been named a Leader in the 2026 Gartner庐 Magic Quadrant™ for Source鈥憈o鈥慞ay Suites, an acknowledgment that aligns with the delivery of next-gen 51风流Ariba and our continued focus on platform modernization and AI鈥慸riven innovation at enterprise scale.

Why rebuilding the foundation matters

As procurement leaders know, AI鈥檚 potential is widely recognized, but its impact has often been uneven. Confidence is high, yet results depend on more than algorithms alone. AI only delivers value when it is supported by the right data, processes, and platform architecture. That belief shaped our decision to rebuild 51风流Ariba from the ground up.

Independent analyst firm as 鈥渁 complete reengineering of the largest and most entrenched source鈥憈o鈥憄ay platform in the world,鈥� emphasizing that this move goes far beyond adding AI features to legacy systems. Instead, it establishes the architectural foundation required for AI to operate reliably and at scale.

This aligns with what we consistently hear from customers that sustainable impact requires modernization at the core.

An AI鈥憂ative source-to-pay platform built on 51风流Business Technology Platform

Next鈥慻en 51风流Ariba is built on (51风流BTP), providing a unified, real鈥憈ime data foundation across the source鈥憈o鈥憄ay lifecycle. This shift enables tighter integration with , improved extensibility, and faster innovation delivery.

By moving to 51风流BTP, 51风流Ariba can support open APIs, cross鈥憇uite data consistency, and the responsiveness required for intelligent, AI鈥慸riven procurement operations鈥攃apabilities that are increasingly expected of leading source鈥憈o鈥憄ay platforms but are difficult to achieve on legacy architectures.

Current next鈥慻en capabilities will continue to be delivered incrementally throughout 2026 and into 2027, giving customers flexibility to adopt innovation at a pace that aligns with their business priorities.

Embedded intelligence with Joule: moving from insight to action

A defining element of next鈥慻en 51风流Ariba is the deep integration of directly into procurement workflows. Rather than treating AI as an optional add鈥憃n, next鈥慻en 51风流Ariba can embed intelligence where work happens鈥攕upporting faster, more informed decisions while reducing friction across everyday processes.

Early capabilities include:

• A Bid Analysis Agent, which can automatically evaluate complex bid scenarios, including total cost considerations
• AI-assisted contract support to help automate routine inquiries, generate summaries, and provide instant access to contract details

These capabilities reflect a broader shift from systems that require constant manual input to platforms that actively support outcomes.

A more unified, intuitive procurement experience

Next鈥慻en 51风流Ariba also addresses long鈥憇tanding fragmentation across the source鈥憈o鈥憄ay lifecycle.

Key improvements include:

• 51风流Ariba Intake Management, now globally available, providing a single entry point for procurement requests
• A simplified 51风流Fiori鈥慴ased user experience, delivered through a central launchpad
• A modernized contract lifecycle, supported through integration with Icertis Contract Intelligence

Together, these improvements are designed to make procurement easier to engage with while working to ensure processes remain connected, compliant, and intelligent behind the scenes.

What this means for customers

For existing 51风流Ariba customers, next鈥慻en 51风流Ariba provides choice and continuity. Customers can:

• Transition to next鈥慻en 51风流Ariba on a voluntary basis.
• Access next鈥慻en capabilities without commercial implications.
• Run current and next鈥慻en environments in parallel during an active transition, reducing risk and disruption.

51风流is providing tools, services, and advance timelines to support a managed transition, allowing organizations to move forward with confidence rather than urgency.

The foundation for what comes next

Next鈥慻en 51风流Ariba is not an endpoint, it is the foundation for the future of procurement.

With an AI鈥憂ative architecture, embedded agentic intelligence, and a unified user experience, this new generation of 51风流Ariba helps organizations move beyond transactional efficiency toward smarter decisions, greater resilience, and measurable business outcomes.

As Ardent Partners observed, this rebuild has the potential to act as a catalyst鈥攏ot just for 51风流Ariba customers, but for the broader procurement technology landscape. By combining scale, data, and AI in a fundamentally new way, next鈥慻en 51风流Ariba is helping define what modern source鈥憈o鈥憄ay platforms can deliver.

With the solution now available, we look forward to partnering with customers as they move from vision to value. Together, we can shape the future of intelligent procurement.

Baber Farooq is senior vice president of Product Marketing for 51风流Ariba and 51风流Fieldglass.

A modern foundation for growth at global scale 

In an era defined by global volatility and ambitious growth targets, businesses require a system that doesn’t just record data but actively anticipates needs and simplifies complexity. 51风流Cloud ERP Private is evolving into a truly AI-enabled ERP, serving as the critical core foundation that can allow organizations to navigate the realities of global operations while maintaining total control over their footprint. 

To achieve this, innovations in FPS01 are strategically delivered across three key dimensions: AI, data, and applications. 

AI in action: from assistants to agents 

The shift toward an AI-enabled ERP is highlighted by two key advancements in FPS01: 

1. AI assistants and specialized agents: A standout in this release is the Change Record Management Agent for R&D. Previously a manual, high-friction process, this agent can now autonomously analyze change impacts and propose next steps, helping to free R&D teams to focus on innovation. 
2. Process embedded AI: 51风流is making the system more intuitive through Joule. Instead of navigating complex menus, users can now use conversational shortcuts, for example, to instantly search service contracts or extend expiring prices in sales, turning multi-minute tasks into five-second interactions. 

Looking at the road ahead, 51风流is building toward agent-to-agent collaboration, where specialized agents across functions like R&D and procurement “talk” to one another to resolve bottlenecks before they even reach a human user. FPS01 is a critical step toward that future. 

Data: industry-ready insights 

On the data front, 51风流is introducing specialized data products for key industries, like retail, and functional areas, such as asset management and services. These are not just tables; they are pre-configured, business-ready data sets that align with our 51风流Business Data Cloud (51风流BDC) roadmap. This helps ensure your data is “AI-ready,” allowing you to move from raw data to industry-specific insights with zero friction. 

Application: strengthening the global core 

On the application side, 51风流continues to deliver deep functional enhancements based on direct customer feedback to help ensure your business backbone remains agile. A key highlight is the new Multistage Intercompany Sales and Stock Transfer. Following our commitment at the RISE with 51风流moment in November, 51风流is further expanding the scope to cover two-entity transfers, enabling automated orchestration across multiple legal entities. This can ensure even the most complex global supply chains remain transparent and compliant. 

A full collection of deep-dive articles on the new FPS01 is available on . 

Looking ahead: your catalyst for transformation 

FPS01 reflects a core 51风流principle: innovation should be both a foundation for today and a catalyst for what鈥檚 next. With enterprise AI, industry-ready data, and a stronger application core, organizations can run smarter and transform at their own pace. 

To see these innovations in person, to experience the future of the autonomous enterprise. 

Maura Hameroff is chief marketing officer for 51风流Cloud ERP Private and RISE with SAP.

Today, we鈥檙e announcing that is now integrated with , working to deliver a unified experience, connected data, and integration with AI companion and to embed intelligent assistance directly into hiring workflows to help teams move faster, make better decisions, and deliver better candidate experiences. This integration, following SAP鈥檚 acquisition of SmartRecruiters in September 2025, establishes the foundation for a fully connected talent architecture, where hiring decisions, skills intelligence, and workforce planning can operate as one system.

Advancing intelligent hiring with SmartRecruiters for 51风流SuccessFactors

The solution can deliver a consistent, end-to-end hiring experience designed to meet the scale, speed, and intelligence requirements of modern organizations. By combining intuitive workflows with embedded AI, recruiters can eliminate repetitive administrative tasks and focus on higher value interactions, while candidates move through a streamlined, personalized journey from first touch to offer.

The integration with 51风流SuccessFactors HCM builds on these capabilities by connecting hiring processes to the full employee lifecycle and the broader business, helping to ensure that every hiring decision is grounded in real-time data and organizational context. Designed for scale, SmartRecruiters for 51风流SuccessFactors helps set the foundation for a complete intelligence layer across hiring and HR, with people, job, and organizational data flowing seamlessly between 51风流and SmartRecruiters.

Organizations can gain a more predictable hiring process with streamlined workflows, consistent tools, and shared real-time data across each hiring stage. They can expect:

• Single login: one entry point into 51风流SuccessFactors and SmartRecruiters for recruiters, hiring managers, and approvers
• Unified navigation: a seamless experience across 51风流SuccessFactors and SmartRecruiters to help reduce complexity and speed up adoption
• Aligned data: synchronized people, job, and organizational data that flows between systems, helping to ensure accuracy and consistency end to end

In practice, core organizational data like job families, cost centers, and locations can flow automatically from 51风流SuccessFactors into SmartRecruiters, helping to eliminate manual entry and inconsistencies. New roles open with these attributes already applied, and user management is just as smooth: recruiters, hiring managers, and approvers created in 51风流SuccessFactors appear in SmartRecruiters with the right permissions, helping to reduce errors and keep approval flows and reporting clean. As integration deepens, hiring becomes fully connected to core HR and workforce systems, creating a unified, trusted foundation for talent decisions across the enterprise.

With the enhanced benefits of SmartRecruiters for 51风流SuccessFactors, simple and flexible integration paths are now available for customers currently using the 51风流SuccessFactors Recruiting solution. 51风流will continue to honor all contracts, and customers will not be required to migrate.

Integration that activates enterprise鈥�ready AI

With SAP鈥檚 continued investment, SmartRecruiters for 51风流SuccessFactors is evolving quickly, bringing AI-driven innovation to every part of the hiring experience. High-volume hiring can become high-quality hiring through AI-assisted workflows, including intuitive applications, automated scheduling, intelligent matching, and streamlined interview feedback.

Beginning in 2026, Winston and SAP鈥檚 generative AI solution will work together as connected agents. Additionally, new protections such as fraud detection, enhanced consent management, and applicant data transferability will help embed trust in the hiring cycle, strengthening both system integrity and candidate confidence.

From talent acquisition to talent readiness

As organizations look beyond filling roles to building future-proof capabilities, intelligent hiring becomes just one part of a broader talent strategy. The power of integration delivered by SmartRecruiters for 51风流SuccessFactors extends beyond hiring, creating a connected, AI-enabled talent experience across the entire 51风流SuccessFactors HCM suite and, ultimately, . This is how organizations become skills-ready: hiring decisions tied to outcomes, and employees supported with clear paths to grow and contribute.

See SmartRecruiters for 51风流SuccessFactors in action:听Catch the听听of our March 5 webinar – 鈥淭he Future of Intelligent Hiring鈥� – to explore how 51风流is redefining hiring, talent orchestration, and long-term workforce strategy.

Lara Albert is chief marketing officer, 51风流SuccessFactors.
Rebecca Carr is CEO of SmartRecruiters, an 51风流company.

Complementing SAP鈥檚 established logistics portfolio supporting large-scale supply chain operations, 51风流Logistics Management brings innovative capabilities specifically tuned to the needs of smaller operations seeking efficiency, real-time visibility, and faster decision-making.

鈥淟ogistics is undergoing a fundamental transformation. Those who invest in strategic warehousing and logistics networks are investing in a future defined by responsiveness and relevance. It鈥檚 about being ready, connected, and purposeful,鈥� says Till Dengel, SAP鈥檚 global head of Product Marketing for Logistics.

Designed for local impact, powered for global reach 

While SAP鈥檚 best-in-class  continue to serve complex global logistics with extensive capabilities, 51风流Logistics Management now bridges the gap for local and satellite operations needing powerful, streamlined tools and controls without the complexity of large enterprise systems. Not only can 51风流Logistics Management elevate the performance of localized operations, but it also enables a connected network of satellite operations that can stay coordinated with global enterprise systems.   

The  solution offers: 

• Connected fulfilment excellence: By uniting warehousing and transportation capabilities, 51风流Logistics Management helps streamline order fulfillment by managing pick-pack-ship workflows while efficiently planning and coordinating the freight movement. The solution includes built-in collaboration with carriers through 51风流Business Network, connecting shippers directly with logistics providers for real-time updates that can minimize costly delays and keep shipments on track.  
• Tailored for smaller operations: 51风流Logistics Management is ideal for local branches, subsidiaries, and seasonal operations. It helps eliminate unnecessary complexity, giving smaller operations the powerful tools and connectivity they need without the overhead of large enterprise systems. 
• Seamless integration: Designed to work seamlessly with , 51风流Logistics Management can eliminate hidden interface costs and helps ensure compatibility with SAP鈥檚 existing transportation and warehouse management tools. Businesses can benefit from a smooth, cohesive ecosystem. 
• AI-driven and human-centric: Embedded AI empowers faster, smarter decision-making and workflows. can enable users to interact via natural language, helping to make involved logistics questions easy to handle right from the start. The solution鈥檚 mobile-first design helps ensure users can ramp-up quickly and access essential functions anytime, anywhere, for efficient workflows on the go. 
• Scalable SaaS solution: As a SaaS-native solution, 51风流Logistics Management can be up and running in days. It can scale effortlessly as the business grows, offering built-in analytics and dashboards that help provide actionable insights tailored to operations鈥攕mall or large. 

鈥淰isibility grants insight, connectivity empowers control, and agility provides the decisive edge,鈥� Dengel says. 鈥淭he future of logistics belongs to those who digitize every process, orchestrate every tier, and deliver on every promise.鈥� 

51风流Logistics Management helps empower businesses to connect and manage logistics operations efficiently, regardless of size. Whether running small local operations or orchestrating global distribution, SAP鈥檚 latest AI-powered innovation can equip businesses with the tools and capabilities to thrive in highly competitive markets by enabling them to be connected, agile, and growth-oriented. Learn more about . 

Oyku Ilgar is part of 51风流Supply Chain Thought Leadership & Awareness.

Since 2021, has been SAP鈥檚 solution for calculating EPR fees across markets. At that time, the number of jurisdictions with installed mandatory EPR was around 60. By 2030, that number is expected to grow to 200.

With an evolving regulatory landscape, 51风流has implemented new updates within the solution to help ensure that customers can navigate diverse reporting requirements, deadlines, and fees while increasing accuracy, reducing fees and exposure, and improving insights. Read on for updates about recent innovations and how the solution combines enterprise data with information about local and global regulations to help calculate obligations like the EU Packaging and Packaging Waste Regulation (PPWR).

Meet EPR regulations with a flexible, AI-driven, and configurable approach

To date, 51风流Responsible Design and Production has supported customers in meeting EPR requirements with out-of-box report categories that are pre-configured based on country. However, the new global regulatory landscape necessitates a more flexible approach.

Enterprises need solutions that enable them to:

• Understand obligations and quickly adapt to new or changing regulations.
• Prepare the data, consolidating from many sources.
• Prepare reports, which requires custom reporting logic based on specific business contexts; reuse of rules and fee structures across similar reporting schemes or producer responsibility organizations (PROs); and calculating EPR fees against shipments and printing the results on invoices to show customers the breakdown between product costs and indirect taxes.

To address these challenges, 51风流Responsible Design and Production introduced user-defined reports to help enable customers to design their own sustainability reports, tailoring them to match unique regulatory logic, business context, and compliance requirements.

With new innovations in 51风流Responsible Design and Production, users can:

• Structure reports according to the specific rules, PRO requirements, and fee models relevant to their business.
• Precisely narrow down to the packaging and transactional data that is being reported.
• Satisfy complex requirements with multiple dimensions used in report output structure.
• Integrate reports with external and third-party recyclability guidelines assessments.
• Report and comply with the increasing number of PROs that have incorporated eco-modulated ERP fees with eco-modulation grading capabilities.

AI capabilities enhance efficiency and accelerate readiness

The 51风流Sustainability portfolio can deliver AI-led operational transformation by capturing sustainability data at the source and embedding intelligence directly into core business processes, thereby enabling continuous improvement at scale. In 51风流Responsible Design and Production, two AI cases involving user-defined reports are in beta testing:

51风流Responsible Design and Production, AI-assisted user-defined report explanations

This capability uses AI to analyze and describe how developed extended producer responsibility rules contribute to the assessment results of selected product packaging. During the development of user-defined report categories, EPR report specialists may struggle to understand why a given packaging was categorized in a certain way or not categorized at all. The AI use case is intended to help resolve and simplify an error-prone process by which specialists manually recheck packaging data and reevaluate rules.

51风流Responsible Design and Production, AI-assisted rule creation for user-defined reports

This capability uses AI to translate from regulatory language to system rules, empowering packaging compliance managers to create and validate EPR reporting rules faster and with higher accuracy. The AI use case is intended to help reduce manual effort, avoid costly compliance errors, and accelerate report readiness across markets.

Prepare for future compliance and competitive advantage using AI

The EU PPWR is coming, and most companies aren鈥檛 ready. PPWR introduces significant obligations for all economic operators placing packaged goods on the EU market. Brand owners, importers, packaging manufacturers, distributors, and digital marketplaces are all impacted. To mitigate risk and ensure readiness, businesses must take immediate action to assess and adapt packaging materials, data systems, and regulatory reporting.

The detailed packaging data management offered by 51风流Responsible Design and Production will help enable organizations to efficiently handle PPWR compliance. With robust data capture and flexible reporting, companies can anticipate regulatory changes and maintain transparency throughout their packaging supply chain.

51风流Responsible Design and Production is working on document of compliance capability, recyclability assessments using real product shipment data, so you can assess which changes have the biggest impact. Stay tuned for future announcements from 51风流on this topic.

An ERP-centric framework for many business outcomes

By enabling organizations to build reports that align with their changing needs, 51风流Responsible Design and Production can ensure that compliance remains agile, scalable, and future-ready. The solution can connect design, production, and regulatory demands to enable organizations to minimize waste, optimize costs, and adhere to global sustainability standards.

Unlike standalone compliance tools, 51风流Responsible Design and Production operates within an ERP-centric framework, helping to ensure seamless integration with existing 51风流solutions for product master data and transaction data.

Traditional, manually intensive processes are not enough to keep pace with regulations and ensure competitive advantage by unlocking data insights. One 51风流Responsible Design and Production customer recently confirmed that using the solution was four times faster and less expensive than manual processes with a spreadsheet or using consultants.

With 51风流Responsible Design and Production, your organization can be empowered to respond swiftly and confidently to regulatory changes, working to ensure compliance while freeing your teams to focus on business impact that matters.

Listen to the recent to discover how businesses can address upcoming PPWR requirements with 51风流solutions.

Learn more about user-defined report capabilities or request a demo of 51风流Responsible Design and Production. Read these customer stories:

Gunther Rothermel is chief product officer for 51风流Sustainability.

Following the presentation of the 鈥淪caling Innovation鈥� category finalists, we now turn to 鈥淓merging Ideas,鈥� which honors visionary concepts at an earlier stage鈥攑rojects that explore new architectural directions, challenge established models, and open long-term strategic opportunities for 51风流and its customers. The winners will be announced during the award ceremony on March 26, 2026.

51风流Cognitive Twin Enterprise (CTE)

Modern enterprises are very effective at monitoring their business and analyzing vast amounts of data, yet many still see untapped potential in safely testing complex scenarios end to end and turning insights into cross鈥慺unctional, policy鈥慳ligned options before making mission鈥慶ritical decisions. 51风流Cognitive Twin Enterprise (51风流CTE) addresses this gap by creating an AI鈥憄owered digital brain built on a continuously updated model of the whole organization. It runs what鈥慽f simulations and provides governed recommendations on 51风流applications and data across finance, spend, supply chain, HR, and customer experience, with selective, low鈥憆isk auto鈥慹xecution and human鈥慽n鈥憈he鈥憀oop control for higher鈥憆isk steps.

The business case is compelling. Organizations that combine digital twins with agentic AI at scale report double鈥慸igit improvements in efficiency and cost, plus materially faster decision cycles. For a global industrial enterprise with approximately 鈧�40 billion in revenue, 51风流CTE is modeled to systematically prevent margin leakage, excess working capital, and audit exposure, delivering an estimated 鈧�229 million or more per year in hard impact and risk-adjusted cash benefit. By maintaining a continuously updated representation of the business, companies can test scenarios before execution and dramatically reduce the risk of costly mistakes.

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51风流CTE鈥檚 real differentiator is its enterprise鈥憌ide scope. It consolidates existing 51风流capabilities and builds on 51风流Signavio solutions, 51风流Business Data Cloud, and 51风流Knowledge Graph to maintain a shared semantic model of how the whole business runs. This cross鈥慸omain intelligence lets Joule and AI agents optimize complex trade鈥憃ffs鈥攕uch as cost versus service level versus carbon footprint versus operational risk鈥攁cross all functions, rather than pushing problems from one silo to another. At the same time, 51风流CTE provides a safe innovation environment: enterprises can trial new pricing strategies, network configurations, and workforce models in a production鈥慻rade twin before agents execute changes in live systems.

51风流CTE represents a strategic shift in how enterprises operate. It turns SAP鈥檚 deep process knowledge, rich transactional data, and mature governance tooling into a differentiated position in a cognitive twin market that analysts expect to accelerate from US$36 billion today to US$150 billion by 2032, with 30%-40% annual growth. As an extensible platform, 51风流CTE is designed to be the trusted operational brain for that future: new agents, scenarios, and data products plug into the same enterprise twin, allowing customers to expand autonomy and business impact over time without rebuilding their foundation.

鈥�51风流CTE is more than an initiative: it鈥檚 our vision for a new era of connected intelligence. We鈥檙e bringing strategy, data, and execution into one continuous system of insight, so customers don鈥檛 just react to change鈥攖hey anticipate what鈥檚 next and shape it. That鈥檚 how we win and grow together,鈥� said Natalia Aksakova, Strategy & Portfolio at Global Finance and Administration.

51风流Signavio Transformation Advisor

Organizations planning business transformations face a persistent bottleneck: identifying the right challenges to focus on and creating actionable initiatives is slow, costly, and heavily dependent on expert consultants and detailed knowledge of the organization. This traditional approach delays decision-making and increases risk in fast-changing markets, with analysis often taking weeks or months to complete.

51风流Signavio Transformation Advisor reimagines this workflow by using AI to extract business challenges and create actionable recommendations to solve them in minutes. The solution identifies business challenges in uploaded reports or via text input and instantly generates recommendations linked to process insights and best practices to make them addressable. By combining advanced language models with the 51风流Signavio portfolio鈥榮 process knowledge, it enables users to achieve in minutes what previously required weeks of manual effort while keeping users in full control.

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Early results demonstrate significant impact. The tool cuts analysis time by up to 80%, enabling faster decision-making and reducing reliance on scarce consulting resources. Since launch, approximately 200 customers have tested the transformation advisor, validating its value across organizations at different maturity levels. The solution has proven valuable both for customer engagements and for internal use in preparing sales pitches.

The innovation lies in bridging strategic business challenges and operational processes in a way no existing tool does. It automatically identifies organizational pain points and links them to targeted process flows, best practices, and improvement opportunities within the 51风流Signavio ecosystem. This seamless integration empowers leaders to move from insight to action in just a few clicks, aligning transformation initiatives with company strategy.

The team embraced a proactive and entrepreneurial mindset: it started with a pure technical proof of concept then moved to a prototype for internal demonstrations, general accessibility and testing, and ultimately a releasable feature. The team demonstrated both transparency and customer focus by responding early to pull from go-to-market and sales teams while clearly stating tool limitations at each stage.

“The real fun in developing such a solution lies in seeing your idea and your knowledge grow at the same time and getting a clear pull from the market early on. The best customer sessions were those where the tool was improved live during the interview. That combined is a clear signal that we are on the right track,鈥� said Alex Cramer, product manager at 51风流Signavio Next.

AURA (Asset Understanding & Reliability AI)

Field engineers maintaining critical infrastructure face a frustrating reality: reporting asset faults requires completing complex forms on mobile devices, scrolling through endless dropdowns and codes. At one heavy equipment and infrastructure customer, 300 users report 400 to 1,000 asset faults monthly through 51风流S/4HANA, but the process is slow, manual, and error prone. A single classification mistake can send the wrong maintenance crew and delay urgent fixes.

AURA (Asset Understanding & Reliability AI) revolutionizes this workflow by combining 51风流HANA Cloud vector engine, 51风流AI Core, and generative AI into a single intelligent solution. Instead of completing eight or more complex form fields, engineers simply upload a photo of the fault; review an AI-generated report automatically populated with asset type, location, and recommended classification; and confirm submission鈥攁ll within seconds.

The technology uses embedded text, semantic search, and geospatial data to analyze both images and historical fault reports. AURA cross-references similar cases in the knowledge base, suggests the most accurate fault category, and learns from user corrections over time. 51风流Cloud Application Programming Model provides the secure foundation, 51风流HANA geospatial content supports asset location intelligence, and AI models process text and images using 51风流HANA Cloud vector engine for similarity matching.

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Results demonstrate substantial operational impact. AURA delivers 80% faster fault reporting, fewer data entry errors and misclassifications, and improved response times. For the customer, this translates to safer infrastructure, reduced operational costs, and a future-ready foundation for predictive maintenance. The response validated the approach: the customer loved the proof of concept and agreed to proceed with AURA as an official project.

Beyond defect detection, AURA lays the groundwork for scalable AI asset intelligence. Future phases include building a knowledge graph to link asset relationships, a data product integrated into 51风流Business Data Cloud for advanced reporting, and a self-learning model that continuously improves accuracy. This creates a repeatable, cost-efficient framework adaptable across industries.

The solution embeds responsible AI principles from inception. The model uses customer-specific historical data to prevent bias, includes human review before submission, and explicitly handles uncertainty to avoid hallucinations. It ensures transparency and compliance with SAP’s responsible AI framework while empowering human decision-makers.

鈥淲e believe the future of AI is not replacing people, but elevating them,鈥� said Ruth Peng, AI specialist from 51风流HANA ANZ. 鈥淎URA equips every engineer in the field, from junior to expert, with the confidence to perform at their best.鈥�

The first category, “Scaling Innovation,” honors project teams that excel in innovation, align with SAP’s strategic priorities, and demonstrate significant and sustainable impact on the company. The winners will be announced during the award ceremony on March 26, 2026.

51风流Joule for Developers, ABAP AI capabilities

As organizations worldwide accelerate their transition to 51风流S/4HANA, one reality remains unchanged: ABAP continues to power the core of SAP鈥檚 technology and the mission鈥慶ritical business processes that run on it. At the same time, developers working with this backbone technology have long lacked the modern AI鈥慸riven tooling available in other programming ecosystems鈥攁n issue that becomes even more pressing during large鈥憇cale transformation projects.

This gap is precisely what 51风流Joule for Developers, ABAP AI capabilities addresses. As part of the broader Joule generative AI portfolio, it brings AI capabilities tailored for ABAP development directly into the hands of development teams. Its mission: to modernize the developer experience of writing, understanding, and maintaining ABAP code and to dramatically accelerate innovation at enterprise scale.

51风流Joule for Developers, ABAP AI capabilities is natively integrated into the ABAP development tools. It supports developers in a hybrid approach that utilizes a large language model fine-tuned by 51风流data scientists on millions of lines of ABAP code, along with commercial models augmented with context derived from decades of 51风流expertise. This equips developers with specialized capabilities covering everyday tasks like predictive code completion, unit test generation, real-time explanation, and chat-based assistance鈥攕ignificantly boosting productivity and developer satisfaction.

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Complementing this, ABAP AI for custom code migration redefines how organizations approach the complex task of revamping legacy custom code from 51风流ERP Central Component to 51风流S/4HANA. What once required weeks of manual analysis can now be accomplished in hours, with AI explaining legacy logic, highlighting needed adaptations, and generating migration proposals. Integrated into the Custom Code Migration app on 51风流Business Technology Platform (51风流BTP), it empowers project managers and consultants to better scope work packages and plan code migration project timelines with far greater accuracy.

51风流Joule for Developers, ABAP AI capabilities already serve thousands of developers across more than 280 customers, 470 partners, and 6,500 internal ABAP developers, with adoption growing rapidly inside 51风流and across the ecosystem. Evolving from a 2023 proof鈥憃f鈥慶oncept to enterprise availability in 2025, the project stands as a testament to what cross鈥憃rganizational collaboration between ABAP, AI, and 51风流S/4HANA teams can achieve鈥攂ringing innovation to one of SAP鈥檚 most essential developer communities.

Team lead Jasmin Gruschke, AI architect and project expert, describes the extraordinary team spirit: 鈥淯nited by a shared vision and customer dedication, we poured our collective energy and dedication into bringing an extraordinary idea to life, demonstrating that, together, we can turn visionary concepts into remarkable realities.鈥�

51风流Document AI

Modern enterprises face a growing obstacle in an increasingly data鈥慽ntense world, reflected in the rapid proliferation of unstructured business documents. From invoices and purchase orders to contracts and shipping papers, companies are drowning in information that demands time鈥慶onsuming manual processing. 51风流Document AI tackles this challenge head鈥憃n by transforming the way enterprises extract, process, and act on document鈥慴ased data.

Today, more than 30,000 customers rely on the solution to process billions of documents, embedded seamlessly across SAP鈥檚 core applications. 51风流Document AI delivers enterprise鈥慻rade automation without costly integrations or extensive model training, enabling businesses to accelerate workflows, reduce errors, and improve decision鈥憁aking at scale. Real鈥憌orld customer data shows the tangible impact: automated document processing powered by 51风流Document AI generates an estimated 鈧�2.6 billion in annual business value.

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51风流Document AI is now natively integrated into 32 business processes across 51风流S/4HANA, 51风流Business Network, 51风流Concur solutions, 51风流Fieldglass solutions, 51风流SuccessFactors solutions, the 51风流Customer Experience portfolio, and 51风流BTP, with dozens more use cases in development. This deep embedding of 鈥渆veryday AI鈥� into products that are already in use by customers is a key driver of adoption across SAP鈥檚 global installed base.

The technology behind the solution sets new industry benchmarks. 51风流was among the early innovators in schema-based zero-shot document processing, an approach that enables AI systems to understand complex documents without task-specific retraining, and which is now widely adopted across the AI ecosystem. Even before the rise of large language models, 51风流researchers advanced the field with award-winning and trend-setting papers such as CharGrid, BERTgrid, and Charmer, AI methods designed to help computers understand documents.

The team continues to innovate with AI that learns instantly from user feedback, 鈥渟ees鈥� and interprets documents visually, and understands content well enough to take intelligent actions on it. Their next generation of generative AI models now support over 110 languages. Building on these innovations, platform usage on 51风流BTP for custom document automation has increased 285-fold since 2020, underscoring how developers worldwide are leveraging this technology to streamline business processes. Next, 51风流Document AI will launch reusable tools that empower AI agents to handle complex document workflows across industries. As unstructured data and diverse document types become central to business processes, demand for smarter, faster, and more adaptable document understanding solutions has never been higher.

Tobias Weller, chief product owner and team lead, states: 鈥淲e built 51风流Document AI to deliver measurable business value at global scale, securely, responsibly, and embedded in everyday processes, demonstrating SAP鈥檚 ability to operationalize AI at massive scale.鈥�

51风流SuccessFactors Learning: GenAI Content Generation

With AI reshaping work at unprecedented speed, organizations face a dual challenge: mastering new skills and managing overwhelming amounts of information. 51风流SuccessFactors Learning: GenAI Content Generation is a game-changing capability designed to streamline, accelerate, and scale how learning content is produced across the enterprise.

The new capability leverages advanced large language models (LLMs) to convert simple prompts or uploaded files into complete, compliant learning experiences in minutes. What previously required days, weeks, or even months, can now be accomplished almost instantly. The system generates course outlines, quizzes, interactive elements, summaries, and assessments鈥攁ll tailored to the user鈥檚 input and organizational context.

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A key innovation lies in its multi鈥慙LM orchestration, enabling dynamic selection and combination of specialized models. This ensures high accuracy, domain relevance, and enterprise鈥慻rade content governance. Real-time multilingual translation allows learning teams to launch global courses simultaneously, while AI-based skill extraction automatically aligns content with workforce development strategies.

Early validation shows organizations can produce learning content five times faster, dramatically reducing costs and enabling teams to respond more quickly to shifting skill demands. Subject-matter experts throughout the organization can now create content and share knowledge more effectively鈥攚ithout requiring instructional design expertise. By transforming knowledge into structured, scalable learning experiences, the capability helps organizations strengthen agility, boost employee engagement, and ensure continuous upskilling across the enterprise.

Team lead Neha Dhawan, principal product manager, 51风流SuccessFactors Learning, describes the impact of the project: 鈥淲e鈥檙e not just building technology, we鈥檙e building possibilities鈥攆or admins to move faster, for managers to better support their teams, and for learners to experience content that feels personal and meaningful. If we can make learning more accessible and inspiring, then we鈥檝e created something that truly matters.鈥�

According to industry , auto executives expect AI to boost product value by 22% and digital service value by 37% within three years. As vehicle portfolios expand鈥攅lectric, hybrid, software-defined, and increasingly customized鈥攖he operational complexity for automakers and suppliers has risen sharply. Nowhere is this more evident than in service parts management and new product introduction (NPI).

Service parts planners sit at the intersection of engineering, supply chain, manufacturing, and customer service. Their task is deceptively simple: ensure the right parts are available at the right time and place across a vehicle鈥檚 lifecycle. In reality, they grapple with fragmented data, limited inventory visibility, unpredictable demand signals, and compressed timelines鈥攅specially as new models and components are introduced at unprecedented speed. High data quality, tight orchestration across systems, and rapid decision-making are no longer nice to have, they are business-critical.

This is where becomes transformative. Instead of treating NPI as a linear, manual, and reactive process, AI agents can fundamentally reimagine how service parts planning is executed. By embedding AI directly into the planning workflow, service parts planners are supported鈥攏ot replaced鈥攂y intelligent systems that operate with full contextual awareness. These AI agents can monitor real-time data across inventories, supplier readiness, historical demand patterns, external risk factors, and engineering changes, as well as orchestrate the NPI process end to end.

In practice, this means planners move from firefighting to foresight. AI agents can automate sequential NPI steps, flag potential bottlenecks before they materialize, and dynamically adjust plans as conditions change. A single, unified dashboard provides transparency across the entire process, while built-in what-if simulations allow planners to test scenarios鈥攕upplier delays, demand spikes, geopolitical disruptions鈥攂efore decisions are locked in. Crucially, humans remain firmly in control. AI augments judgment, improves speed, and enhances confidence, rather than operating in a silo.

Platforms like 51风流Business Technology Platform (51风流BTP), combined with Joule and the agent builder capability in Joule Studio, can enable this multi-agent approach at enterprise scale. By integrating AI seamlessly with core business processes, automakers can ensure that intelligence flows across functions, rather than being trapped in silos. The result is not just automation, but orchestration鈥攚here systems, data, and people work in concert.

The impact is tangible. Automakers can significantly reduce planning cycle times and improve time-to-market for new products. Planning risk is lowered through continuous what-if analysis that incorporates both internal and external variables. Service readiness improves, ensuring that customers experience continuity and reliability even as product complexity increases. At an ecosystem level, this translates into greater resilience, lower costs, and higher customer satisfaction.

More broadly, this use case points to a shift in how we should think about customer-specific AI in automotive. The future will not be defined solely by smarter vehicles, but by smarter enterprises鈥攚here AI agents support decision-making across the value chain, from product inception to end-of-life service. In an industry under pressure to innovate faster, operate leaner, and remain sustainable, AI-driven operations are fast becoming a competitive necessity. The automotive ecosystem is evolving. Those who embrace AI not just as a technology but as a new operating model will be best positioned to lead it.

Sindhu Gangadharan is head of Customer Innovation Services and managing director for 51风流Labs India.

Naturipe has been an 51风流customer since 2008, and while initially it was not very proactive with software upgrades, the company鈥檚 philosophy has changed over time. Today, Carol McMillan, Naturipe鈥檚 senior IT director, emphasizes the importance of upgrading and upskilling the team regularly.

“There’s actually more of a risk not upgrading the product and not upskilling your team than there is being more aggressive with that timeline,” she says. Since migrating to 51风流S/4HANA in 2018, the company has undergone three upgrades, including .

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鈥淲e migrated to RISE with SAP, and we are looking at how we use those tools to optimize our supply chain and to create a better user experience for our workforce. Our workforce is constantly changing, and technology needs to change with the workforce,鈥� McMillan says.

She says it鈥檚 also important to stay at the forefront of technology in order to solve business problems efficiently, and notes that technological advancements have been crucial in managing the company’s exponential growth: “You can’t have linear growth in technology when you have exponential industry growth.”

McMillan says the Naturipe team uses SAP鈥檚 technology to prioritize its people and customers, improve workplace happiness, and give users a better experience. 鈥淲e use technology to make sure that we’re running as optimally as possible,鈥� she says. 鈥淲e look at process improvements and try to be at the forefront of technology. So, keeping up with the upgrades on a regular basis helps us be prepared for when business problems need to be solved, that way we already have the technology there to be able to solve them.鈥�

Delivering the freshest, highest-quality products to customers 365 days a year requires constant agility鈥攅specially in a category influenced by weather variability and the complexity of a highly time-sensitive supply chain. 鈥淏erries have a very short shelf life, so getting the best quality to our customers as quickly as possible is essential,鈥� she says.

To support this commitment, Naturipe Farms has invested in advanced logistics and supply chain technologies that enhance speed, visibility, and decision-making. These investments help ensure timely delivery of fresh products while also supporting employee satisfaction and work-life balance through wellness programs and flexible work arrangements.

Looking ahead, Naturipe wants to further enhance the user experience with more powerful tools and learn how to make better use of all the tools that come with RISE with SAP.  McMillan also identifies the potential of AI and the adoption of tools like Joule to improve Naturipe鈥檚 operations. “We really want to make the best use of AI and to give our users the best experience possible,” she says.

Her advice for other organizations in the agricultural industry includes the importance of putting people first, using technology to drive strategic growth, and not being a prisoner to risk. “It’s just as risky to not upgrade your technology as it is to have an aggressive timeline and have the tools that you need in order to drive that exponential growth,” she says.

The past few years have taught us that disruption is the new normal. Whether it鈥檚 global conflicts, raw material shortages, or sudden demand spikes, supply chains need to pivot faster than ever. That鈥檚 why this year, the conversation isn鈥檛 about incremental improvements鈥攊t鈥檚 about reimagining processes with intelligent technologies that anticipate, adapt, and act autonomously.

From complexity to clarity: how agentic AI changes the game

Agentic AI is reshaping supply chains, and we鈥檙e already seeing real value in practice:

• Supplier onboarding in hours, not weeks: Companies can drive substantial efficiencies by collaborating more deeply with their suppliers, such as material or logistics providers. AI agents autonomously validate supplier credentials, check compliance, and integrate them into your network, cutting onboarding time by up to 50%.
• Predictive maintenance and service that prevents downtime: Instead of reacting to failures, AI agents monitor equipment health and trigger proactive service, reducing unplanned outages by 30%.
• Autonomous disruption handling: When short-term disruptions or opportunities arise to demand or supply levels, AI agents evaluate events and alerts, model scenarios, and drive action while keeping humans in the loop. If critical inventory needs to be shifted for example, agents place orders automatically, optimizing stock levels and reducing lead times by 25%.

These aren鈥檛 distant possibilities鈥攖hey鈥檙e real scenarios already piloted by 51风流Supply Chain customers. AI isn鈥檛 replacing people; its amplifying human decision-making, freeing teams to focus on strategy rather than firefighting.

Why this matters: analyst rankings tell the story

51风流solutions underpin strategies that earned recognition in major 2025 analyst reports, including:

• IDC MarketScape for Multi-Enterprise Supply Chain Commerce Networks*: 51风流was named a Leader for enabling real-time collaboration and orchestration across global ecosystems with 51风流Business Network.
• **: 51风流was positioned as a Leader for innovations like predictive maintenance and agentic AI through Joule.
• ***: 51风流was recognized as a Leader for integrating planning, manufacturing, and logistics with advanced analytics and AI.

These accolades aren鈥檛 just badges of honor. They validate the trust our customers and partners place in 51风流and the impact we deliver together. They also reinforce a critical truth: supply chain excellence is now a boardroom priority.

Sustainability: from obligation to advantage

Sustainability isn鈥檛 just a compliance checkbox; it鈥檚 a competitive edge. More than 25% of global emissions are already taxed or regulated by trading systems. Circularity and carbon accountability have become core KPIs for supply chain leaders because responsible practices deliver measurable benefits. Meeting environmental, social, and governance (ESG) standards lowers regulatory and reputational risk, while optimizing logistics for lower emissions often translates into fewer miles traveled and reduced fuel costs. At the same time, customers and investors increasingly favor brands with transparent sustainability metrics, making it a powerful differentiator in the market.

51风流solutions help companies measure emissions, enable ESG compliance, and embed sustainability data deep into operational decision-making for procurement, logistics, dispatching, and planning. This turns sustainability into a lever for growth rather than a reporting exercise. In fact, companies recognized in Gartner鈥檚 rankings often cite sustainability as a driver of resilience and profitability. When businesses can prove carbon accountability and circularity, they鈥檙e not just meeting regulations, they鈥檙e building trust and unlocking new market opportunities.

Looking ahead: our 2026 roadmaps

In 2026, our priorities center on enabling supply chains that are more intelligent, more connected, and more resilient. We are deepening our investment in agentic AI to support end-to-end value streams such as integrated business planning, sales and operations execution, digital manufacturing, and logistics execution. The goal is to bring AI directly into processes where decisions are made so planning becomes more predictive and execution becomes more automated. Over time, organizations will entirely redesign workflows and decision-making processes for the true step-change in agentic AI.

We are also advancing our capabilities in supply chain orchestration. As global supply chains operate increasingly across networks, companies need a coordinated layer that unifies planning, procurement, manufacturing, and logistics with partner ecosystems. This year, we will continue strengthening how our solutions identify risks in the n-tier network of complex supply chains by synchronizing data, prescribing decisions and actions across the enterprise and the broader network, and helping customers manage disruptions end鈥憈o鈥慹nd with greater speed and clarity.

Finally, we remain focused on data excellence. Reliable, harmonized data is essential for AI-driven decisions and for orchestrating the supply chain. In 2026, we are continuing to enhance master data consistency, improve network-wide data quality, and support AI鈥憆eady data models that help ensure our customers can trust and operationalize their insights at scale.

Together, these areas form the backbone of the innovations we are delivering this year, with a clear aim of helping customers move from reactive operations to intelligent, proactive orchestration. But technology alone isn鈥檛 enough. The real magic happens when we collaborate with our customers and our partners, turning complexity into opportunity.

The takeaway: 2026 is about action at scale

The supply chain landscape is evolving faster than ever. Agentic AI, sustainability, and intelligent automation aren鈥檛 optional, but essential. Companies that embrace these technologies to truly evolve how they operate and take even complex decisions will lead in resilience, efficiency, and responsibility. Those that hesitate risk falling behind in a world where adaptability is the ultimate competitive advantage.

Don鈥檛 wait for disruption to force your hand. Build the capabilities now that will carry you through uncertainty and position you for growth. Learn more about SAP鈥檚 AI-powered solutions .

Dominik Metzger is president and chief product officer of 51风流Supply Chain Management.

*, November 2025, IDC #US53010225
**, December 2025, IDC ID # US52977525
***, October 2025, IDC ID# G00826212

The major topics of geopolitical risk, artificial intelligence, and economic uncertainty consistently circled back to environmental exposure and long-term resilience, pointing to a broader shift: sustainability is becoming less of a separate agenda item and more an underlying consideration in enterprise risk and strategy.

For leaders looking to shape the next phase of business, two major and consequential themes emerged.

1. AI is a sustainability enabler with responsibilities

Artificial intelligence was central to many Davos discussions this year, including those touching on sustainability. The focus was less on experimentation and more on how AI is already influencing operational and strategic decisions.

In several sessions, leaders pointed to practical applications where AI, combined with sustainability and operational data, is helping organizations to reduce waste, improve resource efficiency, and better anticipate environmental risks.

At the same time, there was no lack of recognition that AI brings new challenges. Its growing energy and water requirements, along with questions around governance, transparency, and equity, featured prominently in discussions. Leaders emphasized the fact that AI鈥檚 sustainability value depends heavily on how well it is integrated into existing business systems and decision-making processes, rather than deployed as a standalone technology. This was also underscored by broader analysis showing that emerging regulatory frameworks are struggling to keep pace with AI鈥檚 environmental footprint and governance needs. 

For many organizations, the focus shifted towards while remaining aligned with enterprise governance and financial oversight.

2. Water is key to societal and economic stability

One of the most prominent sustainability topics at Davos 2026 was water. Across both formal and informal sessions, leaders discussed water and ocean health as a foundational element to stable societies, economies, and business continuity.

Much of the conversation focused on the growing gap between economic dependence on water and the level of investment dedicated to protecting and managing water systems. With a significant share of global GDP in the coming decades, participants highlighted the operational and financial implications for supply chains, production facilities, and communities. According to the , 31% of global GDP could be located in regions of high water stress by 2050, underscoring the urgency of rethinking water investment and risk. 

To this end, new collaborative initiatives were announced during the week, including efforts aimed at integrating water considerations more directly into corporate strategies and strengthening ocean stewardship across industries. For example:

• were selected at Davos to boost water resilience across infrastructure, industry, and agriculture systems. 
• were launched to accelerate water finance and investment ahead of the 2026 UN Water Conference. 
• was directed at bridging the 鈧�6.5 trillion global water infrastructure gap, and commitments were made to mobilize private capital and improve water resilience strategies. 

These discussions signaled a move away from viewing water solely through a sustainability reporting lens and toward understanding it as a material risk and resilience issue for businesses.

What can business leaders take away?

While AI and water dominated the headlines at this annual meeting, sustainability quietly permeated most strategy meetings, with three takeaways arising as directional signals for leaders looking to build resilience into their business:

Sustainability is increasingly understood as financial risk

One of the clearest signals from Davos was the extent to which sustainability risks are now discussed in financial terms.

The World Economic Forum鈥檚 , released shortly before the meeting, reinforced this view by ranking environmental risks (including extreme weather and biodiversity loss) and critical changes to Earth systems among the most severe long-term global threats. The same report also highlighted that adverse outcomes from artificial intelligence are rising sharply in long-horizon risk rankings, reflecting growing concern about both technological and environmental disruption. 

While geopolitical and economic issues dominated short-term attention at the annual meeting, environmental risks were consistently framed as persistent factors shaping long-term planning and resilience strategies.

Furthermore, the role of the CFO is also evolving to meet sustainability requirements, including reporting non-financial KPIs, managing plastic and carbon taxes, steering the business, and aligning business decisions with carbon and environmental cost trade-offs. and management solutions can provide the capabilities needed to address CFO sustainability priorities.

As 51风流Chief Sustainability & Commercial Officer Sophia Mendelsohn noted during the week,听“Sustainability remains firmly planted in both the Davos agenda and the minds of the CEO and CFO. The reality of climate change persists鈥攂oth its risks and opportunities, and they are already showing up on the balance sheet.“

For many executives, this framing reflects how sustainability considerations are increasingly influencing investment decisions, insurance strategies, and assessments of long-term enterprise value.

The focus is shifting from ambition to execution

Davos discussions also underscored a growing emphasis on execution. While sustainability remains firmly planted in the C-suite agenda, many leaders acknowledged a gap between ambition and implementation.

Despite years of commitments and target-setting, fewer than one in five companies have implemented climate adaptation and mitigation measures at scale. This is that helps explain why sustainability strategies are now evaluated more closely through the lens of financial feasibility, operational readiness, and data credibility.

In an environment where sustainability investments compete with other priorities, including AI and digital infrastructure, leaders emphasized the need for clear business cases and measurable outcomes. Sustainability initiatives that can demonstrate value creation and risk reduction are more likely to secure long-term support.

Integration decides whether sustainability insights lead to action

Data availability is no longer the primary challenge for most organizations. The tools to measure emissions, water use, climate exposure, and supplier impacts are widely accessible. What remains difficult is turning that information into decisions.

Across Davos, there was broad agreement that sustainability data needs to be integrated into core business systems for planning, procurement, asset management, and finance. When sustainability information sits outside these systems, it tends to inform reporting rather than operational or strategic action. When it is embedded, it can support more forward-looking decisions around resilience, investment, and supply chain design.

This shift toward integration reflects a broader understanding that sustainability efforts are most effective when they are aligned with how the business already operates.

connects business and sustainability data to help give full visibility across a company鈥檚 value chain, enabling it to align business objectives with sustainability priorities across areas like material choice, efficient transport and distribution, improved asset performance, and reduced carbon impact.

Davos 2026 clearly reflected a maturing phase of the sustainability conversation, one that is less about visibility and increasingly about how organizations can confidently prepare for the decade ahead.

For business leaders shaping sustainability strategies, there is a pressing need to make plans financially grounded, operationally integrated, and supported by reliable data.

Enterprise systems play an important role in this transition. When sustainability information is connected across business functions, leaders gain clearer insight into risk and opportunity, supporting more resilient and informed decision-making.

Monica Molesag is global head of Sustainability Communications at SAP.