Trusted sustainability data is becoming one of the most valuable assets an enterprise holds. It shapes investor confidence, influences access to capital, and increasingly steers the decisions that determine long-term resilience. That shift is being accelerated globally by the IFRS® Sustainability Disclosure Standards, IFRS S1 and IFRS S2, now being adopted across more than 40 jurisdictions representing roughly 60% of global GDP.

As they take hold, organizations are expected to produce sustainability information that is as accurate, traceable, and decision-useful as their financial information. Sustainability reporting, in short, is becoming finance-grade, and the organizations that treat it that way will be the ones that turn disclosure into an advantage.

The challenge: establishing trusted sustainability data

The pressure to disclose has not eased. According to PwC’s Global Investor Survey, more than 70% of investors say sustainability must be integrated into corporate strategy. Sustainability data, in other words, is now central to safeguarding enterprise value.

For most organizations, the challenge is establishing a trusted data foundation that can support reporting, assurance, performance management, and decision-making at enterprise scale.

Too often, sustainability data remains fragmented across systems, functions, and geographies. Many companies still rely on disconnected processes and manual reporting, even as assurance expectations rise. EY’s 2024 Global Corporate Reporting Survey found that 96% of finance leaders have concerns about the integrity and reliability of their organization’s non-financial data.

Reporting can no longer sit within a single function. Finance, sustainability, operations, procurement, and risk teams must work from a common, governed foundation. And with some organizations reporting against IFRS S1 and S2 for the first time, while others must now map IFRS S1 and S2 requirements onto existing European Sustainability Reporting Standards (ESRS) or Global Reporting Initiative (GRI) disclosures, building a separate process for every framework only multiplies effort, cost, and complexity.

This is a data foundation problem, and it is where SAP is positioned to help.

How SAP helps organizations meet IFRS S1 and IFRS S2

SAP provides a sustainability suite that helps take organizations from compliance obligation to business value, spanning ESG frameworks and regulatory requirements while embedding sustainability insight into operations and business models.

At its center, SAP Sustainability Control Tower can serve as the single-entry point for audit-ready ESG reporting and sustainability performance management. It helps organizations manage disclosures across IFRS S1 and IFRS S2, ESRS, and other frameworks from one governed foundation that connects sustainability, financial, and operational data. With SAP-provided IFRS S1 and IFRS S2 metrics available within the solution, organizations can reduce manual effort and strengthen reporting confidence. 

SAP Sustainability Footprint Management complements this by helping to calculate the emissions, energy, and environmental data relevant to IFRS S2 climate disclosures and other ESG reporting frameworks. Crucially, it draws on the same ERP data that runs finance, supply chain, and operations, grounding footprint calculations in verified business transactions rather than estimates or manual inputs.

The principle is configure once, report across frameworks. Emissions and energy data calculated in SAP Sustainability Footprint Management, together with master data configured once in SAP Sustainability Control Tower, can serve multiple disclosure obligations. Because IFRS S2 and ESRS E1 are highly interoperable for climate disclosures, a single data-collection scope can serve both. And as reporting requirements expand globally, SAP continuously evaluates regulatory developments and makes the most relevant frameworks available out of the box, so organizations can scale as requirements grow and stay focused on performance and outcomes. For IFRS S1/S2 jurisdiction-specific requirements, SAP’s partner ecosystem is well positioned to extend these capabilities to address local reporting needs.

AI extends this further. The Sustainability Regulatory Readiness Agent helps translate materiality assessment outcomes into reporting-scope decisions, while the SAP Sustainability Control Tower AI-assisted ESG report generation capability can generate structured, complete report drafts from validated metrics already in the system. Teams retain full control to review, refine, and finalize before publication, so organizations can scale efficiently while maintaining governance, transparency, traceability, and human oversight.

We see this in what our customers are doing. KNAPP AG, a value chain technology leader based in Austria, transformed its sustainability reporting with SAP Sustainability Control Tower and SAP Sustainability Footprint Management, implemented with KPMG Austria. Integrating about 200 to 250 metrics, the company completed its first round of CSRD reporting well ahead of the 2027/2028 mandate. 

As Bernhard Bischof, solution reporting architect at KNAPP AG, put it: “Through our collaboration with SAP and KPMG, we are able to realize a resource-efficient and automated approach to sustainability reporting. We rely on innovative software solutions, in particular SAP Sustainability Control Tower and SAP Sustainability Footprint Management, to make our reporting efficient and sustainable.”

As organizations expand reporting beyond CSRD to include IFRS S1 and S2, the same trusted sustainability data foundation can help reduce duplication, improve consistency, and support more efficient reporting across frameworks.

From audit-ready reporting to performance management

With audit-ready ESG reporting as the starting point, the best value is derived from what trusted data enables beyond disclosure: understanding actual performance, identifying where action is needed, and making sustainability a genuine input to business decisions.

That value shows up across the organization. Trusted sustainability data strengthens governance and risk management, supports investor confidence and transparency, improves business steering, and shapes access to finance, cost of capital, and long-term resilience. KPMG’s ESG Assurance Maturity Index 2025 found that 60% of CSRD Wave 1 companies expect ESG assurance to expand their market share or client base.

SAP Sustainability solutions help move organizations from reactive reporting to proactive performance management. Embedded initiatives can turn strategy from a set of intentions into a portfolio of tracked, measured, and accountable actions, each linked to the metrics and targets that define an organization’s ESG commitments. With that foundation in place, sustainability becomes embedded in enterprise processes rather than a stand-alone reporting activity, applied where decisions are made rather than as a downstream task. This is the foundation of SAP’s vision for the Autonomous Enterprise, where sustainability is embedded in the decisions that run the business.

What organizations should do now

Two priorities stand out for leaders today. First, build a trusted sustainability data foundation, with governance, traceability, and auditability established from the start. Second, prepare to report across multiple frameworks and jurisdictions from one common foundation, rather than building parallel processes for each.

Organizations that establish trusted sustainability data foundations today will be better positioned to meet IFRS Sustainability Disclosure Standards, strengthen governance, support investor confidence and access to capital, and create long-term business value.

For more information, visit: www.sap.com/products/scm/sustainability-control-tower

Gunther Rothermel is SAP Sustainability chief product officer.

There’s a classic Harvard case study, where a rowing coach selects his best eight rowers for the top team and his bottom eight rowers for the junior team. Contrary to what you would expect, the top team, with the fastest and strongest rowers, consistently lost to the junior team.

The top team’s rowers focused entirely on maximizing individual power. If the boat slowed, they rowed harder in isolation, disrupting the oars’ synchronized rhythm and creating water drag. Meanwhile, the junior rowers knew they were individually weaker, so they rowed in harmony.

Enterprises have faced countless variations of this problem: implementing systems that maximize productivity at the individual or team level but actively hinder the wider enterprise. Many organizations are experiencing something similar with AI today.

AI and sub-optimization

Sub-optimization is a systemic failure that occurs when the performance of a specific part of a system is maximized, inadvertently hampering the performance of the entire system. There are three intertwined themes: intensity, context, and prediction, which, taken together, explain how AI can sub-optimize an organization by making individuals and local systems stronger while straining the broader organization.

Research reinforces this disconnect between individual or even company-wide AI adoption and the value it delivers. McKinsey’s State of AI report shows near-universal enterprise AI adoption: 88% of respondents report regular AI use in at least one business function, but only 39% report an earnings before interest and taxes (EBIT) impact from AI at the enterprise level. Even worse: only six percent of companies can be categorized as high performers that already capture significant organization-wide value from AI.

What makes it so hard to move from AI adoption to measurable value capture? I believe there are three themes that influence a company’s ability to benefit its entire organization.

Intensity

AI tools often don’t reduce work; they intensify it. A study from Berkeley found that employees who heavily use AI worked faster, took on a broader range of tasks, and worked longer hours, often without being asked. So, what appears to be higher productivity in the short run is actually silent workload creep and mounting pressure as employees manage new AI workflows and do more with less. Another study found that the most mentally taxing form of AI engagement was oversight; AI tools that require direct monitoring increased feelings of being overwhelmed by the volume of information at work.

It is easy to see why AI can feel intense: tasks that once required days can now be prompted into existence almost immediately. People start more things; they do more analysis and write more memos. However, like an eight-lane highway that suddenly narrows to a single-lane toll booth, individuals must still consume all this output. This bottleneck only compounds at the organizational level, as all employees produce more than ever, leaving both individuals and the organization as a whole struggling to keep up. Creation has scaled. Absorption has not.

The solution isn’t necessarily to use less AI, but to change where and how AI shows up. AI should understand user intent and surface the insights needed to answer the question, rather than generating static assets or requiring you to switch between different apps and systems.

If your question creates more things, it’s not helping absorption. SAP’s answer is Joule Work, a central workspace across SAP and non-SAP systems that uses AI agents to handle tasks.

Ask, “Which stores run out of 65‑inch TVs in the next 72 hours, and where is stock I can move?” It will pull data across systems and orchestrate agents to act on the user’s behalf. In this case, SAP’s answer is autonomous action combined with a highly individual user experience for that specific situation, not more assets to be absorbed. If employees can avoid juggling systems and consuming assets, they can spend more time exercising judgment on actions that matter. This is how AI can alleviate intensity.

Context

Most AI systems understand the world, but not the enterprise in which they operate. There is a difference between a system of record—transactions, master data, process logic—and tacit knowledge—emails, chats, unwritten rules. And enterprises run on both. If AI only sees the system of record, its answers might be technically correct but contextually wrong because they don’t reflect the organization’s lived practice.

Even the most ostensibly basic questions require company context. Asking “Which suppliers can I source coconuts from?” requires knowledge of an organization’s process landscape across procurement, supply chain, compliance, finance, and other domains. This type of enterprise knowledge is usually scattered across process models, policies, chats, spreadsheets, and applications, so it’s tough to maintain. And even if they find it, agents cannot turn it into action without procedural knowledge of the involved people—the unwritten rules, decisions, and steps—that make a process executable.

SAP Company Memory preview continuously captures institutional knowledge and makes it usable for both people and agents. It turns written inputs, chat inputs, process knowledge, policy guidance, and application logic into reusable building blocks that AI agents can consume. Blocks are captured once, governed centrally, and reused across the company. So when someone asks Joule Work about coconuts, the answer is driven by the company’s memory and reflects actual rules the process owners agreed upon—for example: “Only source from Brazil; others require formal exception approval.”

SAP Company Memory is not a one‑time implementation; it’s continuous. In this way, company knowledge behaves like infrastructure, ensuring agents act contextually, not just correctly, as policies and teams change.

Prediction

Business decisions are fundamentally prediction problems that rely on structured data. Most organizations use LLMs, which are great at unstructured data like text but for architectural reasons not so great at working with and generating the structured numerical data that underpins good predictions. Delay prediction, forecasting, anomaly detection, stock optimization, and credit risk are everyday operating questions that depend on structured, tabular data and forward-looking judgment.

Asking LLMs for reliable forecasts on enterprise tables is simply the wrong tool for the job. At the same time, traditional custom machine learning approaches are too slow for many real-time questions: after extracting data, sending it to specialists, and waiting weeks, the question often has changed by the time the answer comes back. This combination means predictive capabilities are either restricted to specialists or rendered inaccurate by generic LLMs; in either case, the organization’s decision-making is weakened.

Reliable forecasting and risk assessment should be a system property, not an individual hack. SAP-RPT-1.5 and TabPFN 3 are models that excel with tabular data and will integrate with Joule Work and SAP Business Data Cloud for forward-looking questions directly on live tables.

SAP-RPT-1.5 for SAP data and TabPFN 3 for any tabular data are specialized prediction engines for structured data. They enable decision-makers working in the core systems to ask, “Should I reroute volume? What’s the probability of on‑time delivery? What’s the cost delta across scenarios?” and get answers grounded in real enterprise data.

Availability across the organization eliminates specialist bottlenecks and better equips the enterprise to handle uncertainty through prediction. This enables informed top-level decisions that really move the needle for a company.

AI for the benefit of the whole organization

AI has already proven it can make people more capable, but that does not automatically help the wider organization. AI shouldn’t be about optimizing isolated tasks; it should be about reshaping how work, knowledge, and decisions flow through the company.

Joule Work, SAP Company Memory, and SAP-RPT-1.5/TabPFN 3 are great examples of how SAP designs system-level capabilities. They offer a unified engagement layer, a living institutional memory, and a prediction engine for structured business data that elevate AI from individual-level hacks into a collective benefit for the enterprise.

This is AI that bridges the individual-to-institutional value gap, moving from simply getting AI into the company to generating value throughout the company.

Florian Kunzke is global director of AI Strategy at SAP.

WALLDORF — SAP SE (NYSE: SAP) announced today that HARTING Technology Group, a leading provider of industrial connectivity, has signed a long-term contract for RISE with SAP, marking a decisive milestone in its global IT and digital strategy.

Moving to SAP Cloud ERP Private as part of the RISE with SAP journey, the company will consolidate its enterprise resource planning (ERP), business process intelligence, and service capabilities in a unified cloud-based subscription model. This creates the foundation to support further growth, optimize processes and integrate new technologies.

“Moving to SAP Cloud ERP Private is a strategic decision that goes well beyond IT infrastructure. With RISE with SAP, we are creating the foundation to run HARTING as a more agile, data-driven business—standardizing our global operations, accelerating the integration of new technologies and unlocking the potential of AI across our processes. This contract marks a pivotal step in how we intend to grow and compete over the next decade,” said Philip Harting, CEO, HARTING Technology Group.

SAP Cloud ERP Private will enable HARTING to transition to a future-proof, scalable and innovation-driven ERP environment. Cloud transformation will allow HARTING to consistently automate and standardize operations and infrastructure, direct IT resources toward value-adding topics and innovation, and continuously benefit from updates and new functionalities. At the same time, RISE with SAP opens additional potential in the area of artificial intelligence and data-driven business models, with integrated AI functionalities and new automation options enabling faster, more substantiated data-based decisions. As a long-standing consulting partner, NTT DATA Business Solutions AG will accompany HARTING on its transformation path.

“Industrial companies are under real pressure to move faster, operate leaner and integrate AI into their core processes as a present-day advantage. HARTING’s move to SAP Cloud ERP Private with RISE with SAP reflects exactly the kind of decisive, long-term thinking that separates technology leaders from those who wait, and positions them to scale efficiently and respond to market change with confidence,” said Dirk Haeussermann, Managing Director, SAP Germany.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

Media Contact:
Mariana Guerrero, +1 786 255 6334, mariana.guerrero@sap.com, ET
SAP Press Room; press@sap.com

Top image courtesy HARTING Technology Group

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When Alex de Minaur steps onto the court in Flushing Meadows-Corona Park this month, with his Wilson Ultra v5 tennis racket, it represents much more than years of athletic preparation and training. From its origins at the Wilson Innovation Center in Chicago to the court at the US Open, the racket is the outcome of a concise and connected journey.

The hand-crafted stringing on the face of the racket, the customized design, the packaging and distribution, and the systems that enable each touchpoint are all part of a global supply chain that ensures the racket gets from the warehouse into the gear bag of the world No. 5 exactly when he needs it.

That journey—from raw materials and global suppliers through manufacturing, warehousing, customs, and last-mile delivery—is a supply chain story. And SAP helps power it.

The carefully curated racket, along with Wilson’s shoes, shirt, cap, and shorts de Minaur chooses to wear as he competes at the highest level, are just a few of the thousands of products Wilson manufactures and delivers to athletes and customers around the world.

Behind each product is an interconnected global operation spanning manufacturing, warehousing, retail, e-commerce, and B2B channels and a digital foundation that helps Wilson keep it all moving seamlessly.

Powering a global sporting goods business

Wilson is a global leader in sports equipment and apparel, with a legacy of more than a century of innovation across tennis, basketball, baseball, golf, and other sports. From developing high-performance equipment for the world’s best athletes to creating products for players at every level, Wilson combines deep sporting expertise, innovation, and craftsmanship to help athletes perform at their best.

For almost two decades, Wilson has trusted SAP to run its global operations, connecting hundreds of employees across finance, sales, logistics, warehousing, and other critical retail functions.

Wilson’s SAP landscape spans core enterprise resource planning (ERP), supply chain management, data and analytics, procurement, travel, global trade, integration and enterprise architecture. Its current environment includes SAP ERP Central Component (SAP ECC), SAP Analytics Cloud, SAP Datasphere, SAP Business Data Cloud, and SAP Business Technology Platform, as well as SAP Ariba, SAP Concur, and SAP LeanIX solutions, among others.

And Wilson’s SAP digital transformation is continuing. The company is preparing for a major SAP S/4HANA transformation beginning in 2027, which will unlock new capabilities across areas such as extended warehouse management (EWM), transportation, quality, and omnichannel operations. As part of its SAP S/4HANA journey, Wilson uses Joule to assist with code conversion marking the beginning of introducing AI-powered capabilities into its business operations

One connected foundation for a connected customer experience

Beyond professional athletes such as de Minaur that choose to utilize Wilson to perform on and off the court, Wilson’s global customers interact with the company in many ways—through retail stores, e-commerce, and B2B channels. Behind those experiences is a complex network of products, inventory, orders, warehouses, and business processes that need to work together.

Built for the pace of sport

The world of professional sports moves quickly. A tennis match can turn in a matter of seconds. Consumer goods organizations like Wilson run an equally dynamic and demanding global operation: designing, manufacturing, moving, and selling products to customers and athletes around the world.

A major event, such as a Grand Slam or a Wilson ambassador winning a tournament, can bring heightened demand for the products athletes use and fans want to buy. This requires Wilson to coordinate inventory, production, warehouses, retailers, and e-commerce across markets and respond quickly as demand changes. SAP solutions such as SAP Extended Warehouse Management, SAP Global Trade Services, SAP Concur and SAP Ariba provide Wilson with the digital foundation to run smarter, operate faster, and respond to the ever-changing demands running a global retail business

This September in New York fans will see Alex de Minaur compete with his trusted Wilson racket and adorn his new customized Wilson kit. What they won’t see is the integrated ecosystem and the multifaceted journey behind every single racket, every pair of shoes, every piece of apparel—and the SAP technology powering it.

Tennis is a game of preparation. When I walk onto the court, every detail matters—from how the racket feels in my hand to the kit I’m wearing. Knowing that Wilson and the technology behind their business makes sure everything is ready exactly when I need it, that’s the kind of confidence that lets me focus on competing at my best.

Alex de Minaur

Whether it’s a game of tennis or the demands of a global business, success depends on having everything working in harmony. With SAP, Wilson can perform at its best.

And on the court, Alex de Minaur knows he can trust that everything is in place when the moment matters most.

Enterprise integration has always been foundational work. But in the age of agentic AI — where autonomous software agents are being deployed to orchestrate business processes across sprawling, multi-vendor application landscapes — the stakes of getting integration right have never been higher.

For most enterprises, the integration environment they built over the last decade was never designed for what’s being asked of it now. Point-to-point connections, legacy middleware, fragmented tooling across dozens of systems: these were manageable constraints when the work was batch processing and scheduled dataflows.

Agentic AI changes the equation entirely. Autonomous agents need real-time access to data across the full application estate, consistent governance, and an integration layer that can scale without becoming a bottleneck. The organizations that have already modernized their integration foundation are finding that they have a meaningful head start.

SAP commissioned IDC to conduct an in-depth analysis of organizations using SAP Integration Suite, including its advanced event mesh capability. SAP Integration Suite is SAP’s flagship integration platform as a service, delivered on SAP Business AI Platform, the unified foundation for SAP’s AI, data, and integration capabilities.

For this Business Value White Paper, IDC conducted in-depth interviews with eight organizations across manufacturing, consumer products, energy, fintech, healthcare, retail, and transportation — enterprises with an average of 48,529 employees and $14.53 billion in annual revenue, operating across the U.S., Germany, Denmark, India, and the UK. The results were quantified from actual outcomes, not a modeled composite.

What the IDC Business Value White Paper found: SAP Integration Suite customers are achieving a 368% three-year return on investment with an eight-month payback, generating an average of $47,900 in annual benefits per integrated application, or $9.36 million per organization.

Numbers that matter

The IDC Business Value White Paper documents measurable impact across the full breadth of what integration touches in a modern enterprise:

• Integration speed and scale
  • 78% more application integrations
  • 41% less time to complete per application integration
  • 99% more application messages processed
• Operational reliability
  • 58% fewer unplanned outages
  • 35% faster to resolve integration errors
  • 19% fewer integration errors
• Business process automation
  • 49% more business processes automated
  • 21% efficiency gains for business process teams
  • 32% less time to onboard a business partner
• Developer and team productivity
  • 29% improvement in development team productivity
  • 31% faster development life cycle for new applications
  • 32% more efficient application integration teams

These aren’t projections. They are the average outcomes across eight real enterprises, documented through in-depth interviews by IDC analysts Shari Lava, group vice president for AI, Data, and Automation, and Matthew Marden, research vice president for Business Value Strategy.

More than an SAP platform

One finding in this study deserves particular attention for customers and partners evaluating SAP Integration Suite in mixed-vendor environments: on average, 64% of integrated applications in the study are non-SAP, and 82% of integrations touch at least one non-SAP application.

SAP Integration Suite is not an SAP-only platform. It is the integration backbone for the full, heterogeneous application environment that modern enterprises actually operate, one where SAP and non-SAP systems must work together reliably at scale.

One study participant described what that means in practice: “SAP Integration Suite is our main connection to the outside world. Every time anyone needs to connect to our SAP systems, it goes through [SAP] Integration Suite. It’s our main front door for API access, for data access, for collaborating with us, and for transferring data in and outbound into our SAP systems.”

Built for the AI era

The timing of this study matters. Organizations are moving fast on agentic AI, deploying autonomous agents that need to orchestrate, monitor, and act across their entire application estate in real time. Integration is no longer a back-office concern; it is the operational layer on which AI-driven automation either succeeds or stalls.

As part of SAP Business AI Platform, SAP Integration Suite brings together API management, event-driven architecture through advanced event mesh, and AI-native capabilities — giving organizations the governance, observability, and real-time connectivity that agentic AI workloads require. That includes native support for MCP, LLM connectivity, and agent-to-agent orchestration, making it a ready foundation for autonomous enterprise processes.

Study participants described this directly. One said: “The real value of [SAP] Integration Suite is the combination of its different capabilities: cloud platform integration, API management, and advanced event mesh. It’s the full set of these capabilities that makes it so important for us.”

Another captured the business case for reliability in AI-driven environments: “What we’re starting to see with SAP Integration Suite is a level of reliability and standardization in the integrations we’re building, which enables positive levels of further scalability. We no longer have that kind of point-to-point integration, which had been a risk and a source of technical debt for us.”

Business case is clear

A 368% three-year ROI and eight-month payback is a compelling headline. But what sits behind those numbers is equally significant: enterprises can connect more of their application estate, automate more of their business processes, resolve failures faster, and onboard partners more quickly — all on a platform that is ready for the AI workloads they are investing in right now.

“We can innovate more with SAP Integration Suite because it’s easier and the developers are happier working with the tool. It gives good results, so we continue to build on the foundations we have already created.”

That is the right foundation for what comes next.

Read the full IDC Business Value White Paper here.

Sid Misra is chief marketing officer of Technology Foundation for SAP Business AI Platform at SAP.

Source: IDC Business Value White Paper, sponsored by SAP, The Business Value of SAP Integration Suite (Doc #US54820926-BVWP, August 2026) , IDC Business Value Snapshot, sponsored by SAP, The Business Value of SAP Integration Suite (Doc #US54820926-BVS, August 2026)

Organizations today face increasing pressure to align workforce strategies with rapidly changing business needs. Whether planning for future skills, addressing talent gaps, or improving organizational agility, leaders need more than data. They need clear, actionable intelligence that helps them make informed decisions with confidence. 

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

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

People analytics: a cornerstone of Autonomous HCM 

The future of HR isn’t simply about automating processes. It’s about providing leaders with the workforce intelligence needed to align talent strategies with business priorities. Industry research, including the IDC MarketScape: Worldwide People Analytics and Performance-Driven Workforce Planning 2026 Vendor Assessment, points to growing demand for solutions that bring together people analytics, workforce planning, performance data, and AI-powered insights. Together, these capabilities can help organizations move from reactive decision-making to a more proactive and strategic approach to workforce management. For HR leaders, that means spending less time gathering and reconciling information and more time focusing on actions that improve workforce performance, organizational agility, and business results. 

Connecting workforce insights to business outcomes 

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

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

From workforce intelligence to workforce action 

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

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

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

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

The path forward for Autonomous HCM 

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

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

Learn more 

Explore the IDC MarketScape: Worldwide People Analytics and Performance-Driven Workforce Planning 2026 Vendor Assessment to learn more about the trends shaping the future of workforce intelligence, planning, and decision-making, and why SAP was recognized as a Leader. 

TrustRadius has announced its Top Rated awards for 2026, and SAP Customer Experience (SAP CX) is proud to share that SAP Sales Cloud, SAP Service Cloud, and SAP Commerce Cloud have each been recognized as Top Rated products in their respective categories. In a landscape crowded with vendor-sponsored rankings and paid analyst reports, TrustRadius stands apart. These awards are driven entirely by verified customer reviews: no paid placement, no analyst opinion.

To earn a TrustRadius Top Rated badge, a product must meet three stringent criteria:

1. At least 10 verified reviews submitted within the past year
2. A trScore of 7.5 or higher
3. A meaningful presence in its category

Every submission passes through TrustRadius’ fraud-protection verification process. That means these three wins are a direct reflection of what SAP customers experience every day, and they said it loudly and clearly.

What customers are saying

Across sales, service, and commerce, SAP customers consistently highlighted the depth of integration, reliability at enterprise scale, and the tangible business impact of AI-powered workflows. These aren’t features on a road map; they’re capabilities customers are using today, and the reviews prove it.

SAP Sales Cloud

“We had a comparison between SAP Sales Cloud, Microsoft Dynamics, and Sales Force Optimization. We selected SAP Sales Cloud for three main reasons: SAP Sales Cloud meets our requirements the best, especially in comparison with Sales Force; pricing is more attractive; and as we use multiple SAP products, the integration between different SAP products works well.” – Verified Reviewer
Read the full review here.

“SAP Sales Cloud is well suited for predictive analysis and strong integration with ERP, SAP S/4HANA. AI-driven recommendations for next best actions.”
Read the full review here.

SAP Service Cloud

“The enhanced service efficiency has unified agents’ workspace by consolidating emails, phone, and chats into a single control panel, eliminating the need for our agents to switch between systems. Also, AI-powered automation has reduced agents’ workload and increased efficiency by initiating automated ticket categorization and “next best action” recommendations.” – Chris Kithinji, Business Systems Analyst
Read the full review here.

“We can add an AI-based model for resolving customer queries without any human effort or intervention. It streamlines the customer support process by simply adding the automation.” – Kanika Rajpal, Technical Architect
Read the full review here.

SAP Commerce Cloud

“It is actually a cloud-based commerce platform, which is a package with lots of features, and we are using that for our Business to Business, Business to Customer, and even for Business to Business to Customer (kind of selling your product to another business and they are going to connect with the end customer) model. As it is very good to customize the features as per your need, and also we can integrate with other SAP products like SAP ERP, which is very beneficial to support the described model operation from anywhere.” – Ajay Thakkar, Software Engineer
Read the full review here.

“We switched to SAP Commerce Cloud four years ago. The software has simplified our e-commerce processes, particularly inventory management, payment processing, marketing, and general order management. Use of the software has enabled us to ensure a good customer experience across various channels. It has also enabled unlimited interaction between the customer service team and our clients, as well as third-party integration.” – Denis Bacarella, Digital Marketing Assistant
Read the full review here.

What’s next: agentic AI across the customer experience portfolio

Winning today’s recognition motivates us to keep pushing forward. SAP’s approach to AI goes beyond chatbots and dashboards.

As Balaji Balasubramanian, president and CPO of SAP Customer Experience, put it: “AI alone is no longer a differentiator. What matters is where intelligence operates inside of a business.”

That philosophy is driving a new wave of agentic AI innovation across all three award-winning products.

SAP Sales Cloud now features an email-to-quote capability through a Microsoft Outlook add-in that can automatically populate SKUs from deal and email context, helping to turn a seller’s inbox into a quoting engine. A new deep research feature can synthesize SAP Sales Cloud and SAP Service Cloud data with external market intelligence to help supercharge account planning.

SAP Service Cloud is rolling out an Agent Inbox that can consolidate cases, tasks, and service orders into a unified command center with live workload insights. A new Digital Service Agent handoff can intelligently summarize customer intent before ticket creation, helping to reduce friction and improve resolution speed.

SAP Commerce Cloud is embedding AI directly into catalog management, extracting product details from uploaded documents to help auto-enrich descriptions and improve product discoverability at scale.

Trust as a foundation for innovation

These TrustRadius Top Rated awards confirm what SAP has always believed: that great software earns trust through outcomes, not marketing. As we continue to evolve SAP Sales Cloud, SAP Service Cloud, and SAP Commerce Cloud with agentic AI capabilities, the voice of our customers remains our most important compass.

Learn more about SAP Customer Experience innovations here. Explore the TrustRadius Top Rated methodology at trustradius.com.

Artificial intelligence has entered a new phase. The conversation is no longer about whether organizations should adopt AI.

Across industries, businesses are already experimenting with AI to automate tasks, improve productivity, and create better customer experiences. The real question now is how do we move from experimentation to enterprise-wide transformation that delivers meaningful business outcomes?

At SAP, our answer is clear: the next wave of transformation will be driven by Industry AI. This belief is also reflected in the evolution of our own organization, as Customer Innovation Services evolves into Customer Industry Solutions. This is more than a name change; it represents an expanded mission and a recognition that the future of enterprise AI will be shaped by the combination of technology, deep industry expertise, engineering excellence, and customer-centric innovation.

The opportunity ahead is immense. Analysts estimate that generative AI alone could create between $2.6 trillion and $4.4 trillion in annual economic value globally, while global spending on AI is projected to exceed $630 billion by 2028. Yet, realizing this value will require enterprises to move beyond experimentation and deploy AI in ways that are deeply relevant to their industries.

For years, enterprises have pursued digital transformation through broad platforms and horizontal capabilities that could be applied across functions and sectors. AI has followed a similar trajectory. Large language models (LLMs) and general-purpose AI tools have demonstrated remarkable capabilities and unlocked entirely new possibilities. However, as organizations move beyond pilots and proofs of concept, one thing is becoming increasingly clear: generic AI can only take us so far.

“In the enterprise world, context is everything. The future of AI lies not in generic intelligence but in intelligence that understands industries, business processes, and how enterprises create value,” said Dominik Metzger, Global Head of Industry AI. “This is where Customer Industry Solutions plays a pivotal role, bringing together deep industry expertise, customer insights, and engineering excellence to bridge the gap between innovation and real-world business impact.”

A manufacturer seeking to optimize its supply chain faces challenges that are fundamentally different from those of a retailer personalizing customer experiences. A bank navigating regulatory requirements operates in a vastly different environment than a life sciences company accelerating research and development. Every industry has its own processes, data models, regulations, and ways of creating value.

This is precisely why Industry AI represents the next frontier of enterprise transformation. The Industry AI portfolio combines the power of AI with deep domain expertise and business context. It understands not only language, but also the nuances of industries and the realities of how businesses operate. It can address industry-specific challenges and deliver outcomes that are measurable, scalable, and relevant to the enterprise.

Building on our strong foundation of customer co-innovation, the Customer Industry Solutions organization brings together deep industry expertise, customer insights, and engineering excellence to accelerate Industry AI at scale. Importantly, we are also bringing together the strengths of customer innovation and forward-deployed engineering.

This combination is powerful. Customer innovation teams bring a deep understanding of business challenges, industry processes, and customer outcomes. Forward-deployed engineering brings the ability to rapidly build, deploy, and operationalize solutions in complex enterprise environments. Together, these capabilities enable us to bridge the gap between breakthrough innovation and real-world business impact.

Our role is not simply to help customers adopt new technologies. It is to work alongside them to address complex business challenges, rapidly translate ideas into solutions, and help move organizations from AI experimentation to enterprise-wide transformation.

Industry AI also changes the way innovation itself happens. The most valuable insights often emerge from solving real customer challenges. They come from understanding pain points on the ground, identifying opportunities to simplify complexity, and applying AI in ways that create tangible business value. This requires closer collaboration among customers, industry experts, engineers, and product teams than ever before.

This is another critical role that the Customer Industry Solutions organization will play. By working closely with customers across industries and regions, and by systematically capturing insights from the field, we can help inform future product development and accelerate the adoption of industry-specific AI capabilities at scale.

Every customer engagement becomes an opportunity to learn, refine, and build solutions that can benefit entire industries.

Sindhu Gangadharan is head of Customer Industry Solutions at SAP.