Business transformation is tough. Adapting the way you work in response to AI advances, supply chain disruption, seismic political shifts, and more can often draw focus and resources away from actually doing the work itself.

The other key characteristic of business transformation: it’s not going away.

Organizations that ignore the need for change find themselves constantly on the back foot, unable to take advantage of new opportunities, and in an endless loop of reactivity.

But even those businesses that know they need to change fall into a common trap: treating “transformation” as a project, something to be ticked off the list as “completed,” never to be thought of again. Until the next system-wide shock, that is.

Transformation as a capability

The organizations best placed for success are those that avoid both these approaches. They succeed by building their transformation muscle—the capacity to run multiple transformations, consistently and concurrently.

Let’s be clear: for modern enterprises, change is not something that happens as a time-limited or even clearly definable event. Change is much closer to an operational reality, something so intrinsically connected to how businesses work that it can’t be separated from decisions, processes, and all the other elements that allow an organization to function.

“Most enterprises run four or more transformations a year. Building a repeatable transformation capability you can strengthen over time makes all the difference,” Dee Houchen, chief marketing officer for SAP LeanIX and SAP Signavio, says. “The capacity to adapt and transform is not just a competitive edge, it’s a basic business requirement. And so, knowing where your transformation strengths and weaknesses lie is critical to ensuring your business can function effectively in today’s complex environment.”

In other words, effective business transformation is just as important to the way a company works as any other aspect you could name. Organizations with the skills and knowledge to transform repeatedly and at scale, and to flexibly apply those skills and that knowledge in different contexts, will be those that survive and thrive.

So how can you determine whether your business has the right transformation muscles?

Assessing your capability

SAP has created a quick and easy online tool that can measure your organization’s transformation capability as it stands right now, so you can make the right decisions to build your business for the future.

Grounded in recent Forrester research assessing levels of business transformation management maturity around the globe, the tool uses this data as a baseline to assess transformation capability across five domains: strategy and leadership, applications and technology, process, data, and people.

Using self-reported information about your business, the tool can take less than 10 minutes to benchmark your capability against peers, as well as pinpoint strengths, gaps, and execution risks. But this is not simply a static information-gathering exercise. The tool can set your baseline, helping determine where your organizational strengths and weaknesses are. It’s up to you to take the next steps.

“The real value of this tool lies in using it to unlock value in your business,” Houchen says. “The baseline is important, but it’s the targeted, actionable recommendations that can really strengthen your transformation capability.”

“The tool provides recommendations across critical areas like executive commitment, strategic planning, technology modernization, process optimization, data management, and organizational culture—and some you can already start putting in place,” Houchen adds. “Within a matter of months, you can build a robust, repeatable transformation capability, or, if you’re more advanced already, continue to strengthen that capability and start to expand the possibilities for value-adding through transformation.”

Building your capability

The transformation maturity assessment tool can also go beyond organizational recommendations and can even provide insights on how you can best improve your underlying approach—the transformation mindset that can help drive future success. The tool can help you explore critical components like:

• The role of strategic commitment in enabling transformation
• Opportunities to modernize your technology foundation
• How processes support value-driven execution
• The best ways to manage transformation data
• How organizational culture supports empowerment and adaptability

“Using this tool helps ensure your readiness to navigate the complexities of modern business, turning business transformation from a project into a part of the operational fabric of your organization—a repeatable, scalable competitive advantage,” Houchen says.

Try the business transformation capability assessment tool for yourself.

Lucas de Boer is a marketing execution senior specialist at SAP.

The recent selloff in SaaS stocks misreads the real disruption. It reveals why enterprise software is more essential than ever. 

Artificial intelligence is the most consequential technology shift since the internet—and the most transformative thing to happen to enterprise software. Not because AI threatens it, but because AI needs it. The breakthroughs in reasoning, code generation, and autonomous agents are real, and they will reshape every industry. 

I see it firsthand. AI is driving double-digit efficiency gains across our own operations. In more than two-thirds of our 2025 fourth quarter cloud deals, customers chose to include AI capabilities. Manufacturers are using AI agents to automate quotation processes, cutting response times dramatically. Consulting teams are reclaiming a quarter of their working week for higher-value work. This is not hype; it is happening, at enterprise scale. 

Every major platform shift follows a pattern. Early on, value accrues to the lowest layers of the stack: the compute, the models, the infrastructure—the shovels in the gold rush. Over time, enduring value migrates upward to the application layer, where technology translates into business outcomes. The internet made that clear. Cloud computing confirmed it.

AI will be no different. Software is not reaching the end of the line; it’s just getting started. In other words: software is becoming AI’s superpower. 

Where the real value lies 

Across industries, companies are pouring billions into AI, driven by real breakthroughs in capability and productivity. Yet many are struggling to translate experiments into measurable, enterprise-wide outcomes. The root causes are well-known: fragmented data landscapes, siloed processes, inconsistent governance, and AI bolted on to aging legacy systems.  

Regardless of their industry or size, every customer I speak with wants one thing: AI that deeply understands their business and does so securely and reliably. That requires integrated applications, harmonized business data, and clear controls. Without these, AI operates in a vacuum, disconnected from business reality. 

If it doesn’t understand how finance connects to procurement, how a supply chain interacts with manufacturing, what compliance rules govern a transaction, or how to handle exceptions, AI cannot reliably run a business. The smallest mistake—using outdated, incomplete, or incorrect data—can quietly cascade into wrong decisions, faulty transactions, and significant losses before anyone notices.

Far from eliminating software, AI exposes the indispensability of the systems that coordinate work at scale.  

Enterprise AI succeeds where agents and governance meet 

Building an agent is becoming increasingly easier—the tip of the iceberg. Deploying it across end-to-end supply chains or financial close processes, with full compliance and audit trails, is where most of the effort lies. Orchestration, policy enforcement, and workflow determinism are the gatekeepers of trust. The more autonomous agents you deploy, the more valuable the governed systems that constrain and supervise them become, and that’s where the platforms that already run the world’s core operations come into their own.

What agents need to operate at scale 

To deliver real outcomes reliably, agents need three things. First, deep domain and industry knowledge encoded in systems, so agents understand context, relationships, and end-to-end processes. Second, accurate, semantically rich business data that provides a reliable source of truth. And third, enterprise-grade governance: validation rules, compliance checks, approval flows, identity management and audit trails to keep autonomy safe.  

These are the elements that separate the AI that can truly and reliably run a business from the AI that merely impresses in a demo. 

What changes, what stays true 

AI makes software faster and cheaper to build. Large language models will be commoditized. Business models will evolve as usage patterns shift from users to agents. Entirely new interfaces will emerge. Users will increasingly converse with AI rather than navigate applications, and front-ends will be generated dynamically in real time. 

But the need for continuously updated, governed systems only grows. AI raises the bar for secure updates, telemetry-driven improvement, and shared controls: all strengths of mature SaaS. AI agents don’t replace enterprise software. They rely on it.  

The winners will not be those who own marginally better foundation models. They’ll be those who deliver value at the application layer: business outcomes grounded in deep domain expertise, integrated across functions, and governed for deployment at scale. 

Software is becoming the operating system for trusted autonomy. The companies that recognize this will embed AI into the systems that run the world’s economy. The rest will run more experiments, generate more prototypes, and wonder why the outcomes lag the hype. 

Long live software. 

Christian Klein is CEO of SAP SE.

Announcement by SAP SE, Walldorf, pursuant to Sec. 62 para. 3 sent. 2 cl. 1 UmwG

– Notice of upcoming merger –

1. It is intended to merge emarsys interactive services GmbH (Local Court of Charlottenburg, HRB 118447) as the transferring company with SAP SE as the acquiring company by way of a simplified intra-group merger. The transfer of the assets of emarsys interactive services GmbH shall take effect internally as of January 1, 2026, at 12:00 a.m. (“Merger Effective Date”). From the Merger Effective Date until the time of the dissolution of emarsys interactive services GmbH pursuant to Sec. 20 para. 1 no. 2 UmwG, all acts and transactions of emarsys interactive services GmbH shall be deemed to have been conducted on behalf of SAP SE.

   SAP SE is the sole shareholder of emarsys interactive services GmbH as of the date relevant for the application of the group exemption provision under Sec. 62 UmwG, namely the filing of the merger with the respective commercial register and the respective date of registration. A merger resolution by the acquiring company SAP SE is not required pursuant to Sec. 62 para. 1 sent. 1 UmwG. Consequently, it is also not necessary to convene a general meeting of SAP SE to approve the merger. For the same reason, neither a merger report, a merger audit, nor a merger audit report is required, Sec. 8 para. 3 sent. 3 no. 1 lit. a), Sec. 9 para. 2, Sec. 12 para. 3, Sec. 60 UmwG.

2. The shareholders of SAP SE are hereby notified of their right to demand the convening of a general meeting to vote on approval of the merger if the shares held by the shareholders making such a demand together amount to one-twentieth of the share capital of SAP SE (Sec. 62 para. 2 sent. 1, and para. 3 sent. 3 UmwG).
3. A resolution by the shareholders’ meeting of emarsys interactive services GmbH approving the merger agreement with SAP SE is not required, since, as of the date relevant for the application of the intra-group exemption provision of Sec. 62 UmwG – namely, the filing of the merger with the respective commercial register and the respective date of registration – the entire share capital of emarsys interactive services GmbH is held by SAP SE, Sec. 62 para. 4 sent. 1 UmwG.
4. The following documents are available as of the date of this announcement:
   1. The draft merger agreement between SAP SE and emarsys interactive services GmbH.
   2. The annual financial statements and, where required, the annual reports of the companies who are parties to the merger for last three fiscal years:

      2023 SAP SE Statutory Financial Statements and Review of Operations (HGB)
      2024 SAP SE Statutory Financial Statements and Review of Operations (HGB)
      2025 SAP SE Statutory Financial Statements and Review of Operations (HGB)
      2022 emarsys interactive services GmbH
      2023 emarsys interactive services GmbH
      2024 emarsys interactive services GmbH

SAP SE, April 24, 2026

The Executive Board

WALLDORF — SAP SE (NYSE: SAP) today announced its financial results for the first quarter of 2026.

At a glance

• Current cloud backlog of €21.9 billion, up 20% and up 25% at constant currencies
• Cloud revenue up 19% and up 27% at constant currencies
• Cloud ERP Suite revenue up 23% and up 30% at constant currencies
• Total revenue up 6% and up 12% at constant currencies
• IFRS operating profit up 17%, non-IFRS operating profit up 17% and up 24% at constant currencies

Christian Klein, CEO:

“We had a strong start to the year, with Current Cloud Backlog growing by 25% and Cloud Revenue up 27% at constant currencies. This performance is supported by our momentum in Business AI as we are already delivering real outcomes for customers today. We are growing faster than the market and are gaining share as customers expand across our Suite and with our AI solutions. At Sapphire, we will show how we are taking the next leap forward.”

Dominik Asam, CFO:

“We delivered a solid start to the year, supported by disciplined execution in revenue and profitability. At the same time, we have remained focused on managing our cost base and maintaining profitability as we navigate an increasingly complex and uncertain macroeconomic and geopolitical environment.”

About SAP

As a global leader in enterprise applications and business AI, SAP (NYSE:SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.

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

HR leaders often worry about moving too fast—embracing new trends, over-investing in new technology, or introducing more change than the organization can absorb. But a new business value study from IDC sponsored by SAP*, based on organizations using SAP SuccessFactors solutions to run core HR, time, and payroll, points to a different risk altogether: fragmentation. And not only as an operational inefficiency, but as a fundamental barrier to realizing the full potential of AI in HR.

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 “work,” 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 “slow” decisions

The impact of fragmentation isn’t 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—not 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’t human—they’re structural

Disconnected systems don’t 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’t 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—whether for career growth, scheduling, or compensation—when they trust the underlying data. Without that trust, even the most advanced AI capabilities remain underutilized.

Fragmentation doesn’t just slow execution—it 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’t just operational; it’s 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—not just operationally, but strategically.

The real risk isn’t innovation

Innovation draws attention because it’s 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—better insights, faster planning, stronger compliance, and improved employee experiences—the limits of disconnected systems become harder to ignore.

Modern HR outcomes don’t 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 SAP SuccessFactors are evolving—not 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’t whether organizations can afford to modernize HR. It’s whether they can afford to limit the impact of AI by building on fragmented foundations.

AI doesn’t transform HR on its own; it amplifies what’s 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 SAP SuccessFactors.

*IDC Business Value White Paper Sponsored by SAP, The Business Value of SAP SuccessFactors Core HR, Time, and Payroll Solutions, #US53971225-BVWP, January 2026.

Lara Albert is chief marketing officer for SAP SuccessFactors.

Customers can deploy Joule Agents in SAP CX Solutions to build, launch, and optimize marketing campaigns

Gemini Enterprise acts as a central hub for agents to take action across SAP and Google Cloud platforms

LAS VEGAS — SAP SE (NYSE: SAP) and Google Cloud today announced a new partnership that will help marketers put AI agents to work at scale.

Through new integrations between the SAP Engagement Cloud, SAP Customer Experience (SAP CX) and Joule solutions and Gemini Enterprise, joint customers can now deploy agents that securely access unified data stored across both ecosystems to execute complex marketing strategies based on high-level goals defined by the user.

Together, SAP and Google Cloud provide a unified foundation for data and AI agents to operate across both ecosystems. Gemini Enterprise will act as a central hub for data integrations and multi-agent coordination, allowing agents to take action across a customers’ SAP and Google Cloud solutions. These integrations will be supported by the SAP Business Data Cloud Connect solution for Google and BigQuery, which enable bidirectional, zero-copy data access between the two platforms, with enterprise-grade security and governance. Capabilities across both Gemini Enterprise and agent gateway APIs from SAP will allow customers’ agents to more securely exchange context, trigger actions and optimize outcomes across platforms, enabling true multi-agent orchestration.

The integration allows marketers to prompt an agent within SAP Engagement Cloud with a clear objective like, “Increase repeat purchases from the last 30 days,” or “Maximize customer lifetime value while reducing campaign operational costs.” An agent, like a Joule Agent, will handle the end-to-end process—from content personalization to visualization to conversational engagement.

“This is more than a data integration; it’s a leap forward for AI agents that can collaborate naturally and execute seamlessly,” said Balaji Balasubramanian, President and Chief Product Officer, SAP Customer Experience and Consumer Industries. “By combining SAP Business Data Cloud Connect for Google with interoperable AI agents across SAP and Google Cloud, we’re giving organizations a path from AI experimentation to AI-enabled customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

“To realize the full potential of agentic AI, businesses need their systems to speak the same language,” said Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud. “By uniting SAP’s enterprise data and customer engagement platform with Google Cloud’s AI, we’re enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.”

According to research from SAP Engagement Cloud, more than half of marketers say fragmented, outdated data prevents them from acting in the moment. SAP and Google Cloud are helping remove that roadblock by unifying data and letting AI agents turn insights into action. Using Joule with SAP Engagement Cloud, campaigns can move from planning to activation automatically without manual stitching across tools.

Customers will benefit from autonomous campaign generation, optimization and continuous improved performance. Businesses will achieve faster speed-to-market, lower operational overhead and always-on optimization that drives higher ROI, while giving teams more time to focus on strategy and end-to-end campaign execution.

While marketing is the first example, and will be available to customers in H2 2026, this multi-agent orchestration model is designed to support high-value use cases across the SAP CX portfolio, laying the foundation for AI-driven customer experience, powered by trusted, unified real-time data and interoperable agents.

For more information about SAP Customer Experience solutions, visit sap.com/cx.

For more information about Gemini Enterprise, visit cloud.google.com/gemini-enterprise.

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

About Google Cloud

Google Cloud offers a powerful, optimized AI stack — including AI infrastructure, leading models like Gemini, data management capabilities, multicloud security solutions, developer tools and platform, as well as agents and applications — that enables organizations to transform their business for the Agentic Era. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.

About SAP

As a global leader in enterprise applications and business AI, SAP (NYSE:SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP’s 2025 Annual Report on Form 20-F.
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