Where Do You Stand? Business Transformation Maturity Assessment Tool Now Available

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.

Assess your organization’s transformation readiness and see how to level up

“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.

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Software Is Entering Its Most Powerful Era

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

Achieve company-wide ROI and transform how work gets done with agents grounded in business data

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.

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Information About Upcoming Merger of emarsys interactive services GmbH into 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

SAP Announces Q1 2026 Results

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.”

Find all results in the Quarterly Statement

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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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.

The Real Risk to AI in HR Is Fragmentation

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.

Read the IDC report to see how SAP SuccessFactors HCM can deliver greater workforce accuracy and efficiency

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.

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SAP and Google Cloud Expand Partnership to Deploy Multi-Agent AI


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

Deliver personalized, AI-driven engagement across every channel and touchpoint

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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AI Is Raising the Bar for Customer Experience: SAP and Google Cloud Are Building What Comes Next

Imagine your customer opening your app after receiving a personalized email offer. They are expecting a seamless experience.

SAP and Google Cloud Expand Partnership to Deploy Multi-Agent AI

Instead, they immediately encounter friction. They’re asked to repeat information they’ve already shared across multiple channels and departments. Then they see an offer for the item they just purchased, rather than something similar or new. And when they encounter an issue down the line, customer support doesn’t recognize their history.

Micro moments like these do not feel minor to customers anymore. They feel inexcusable. Customer expectations have changed faster than most brands can keep up. Customers now assume brands know who they are, what they need, and what’s happening right now. And they expect brands to act on that knowledge instantly.

At the same time, businesses are embracing a new era of AI. Dubbed “agentic AI,” it represents a paradigm shift where AI doesn’t just analyze or recommend products, but increasingly plans, decides, and acts through a network of agents. This creates a massive opportunity for customer experience (CX) leaders today, in particular marketers, who, according to McKinsey, are leading in AI adoption amongst business functions. But it also raises the stakes.

Because when AI moves faster than your data, systems, and processes, it exposes everything that’s broken. That tension—between rising expectations and disconnected reality—is exactly what SAP and Google Cloud are addressing together.

Using AI to Scale Social Impact

The first time Flavio Proietti Pantosti entered a prison, he was immediately struck by the sense of oppression: “Walking down the long, straight corridors, the intense feeling of confinement was overwhelming, matched only by the profound relief upon leaving.” This first encounter as a volunteer in an Italian correctional facility inspired Proietti Pantosti, founder of social enterprise Reoassunto, to help inmates regain control of their lives during imprisonment.

“Reoassunto provides dedicated support for reintegration,” Proietti Pantosti said. “Our goal is to significantly reduce the rate of reoffending among first-time convicts.” 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’t have the skills or funds to create an AI prototype to realize his concept.

The Engagement Divide: 15 Reasons It’s Time to Fix CX

Customer engagement is at a breaking point, and the most recent data proves it. Even as organizations accelerate their investment in AI, automation, and analytics, experiences often feel disconnected, impersonal, and reactive.

Connect AI, data, and customer-facing applications to deliver winning experiences

The problem is not the promise of AI. It’s the gap between intelligence in the system and connection in the moment. Customers are increasingly disengaging because intelligence is not being applied where it matters most.

Technology, particularly AI, has fundamentally changed what customers expect. They assume brands can recognize them across channels, understand context in real time, and anticipate their needs. When that doesn’t happen, the miss feels less like oversight and more like indifference. Timing is off. Service lacks continuity, and personalization stops at the surface, despite all the data behind it.

While many enterprises are trapped in siloed systems and disconnected data, consumer expectations are growing. Brands that don’t deliver the expected experiences are quickly abandoned.

In addition, global socioeconomic factors are increasing rapidly and unpredictably, challenging bottom lines and making customer loyalty more critical than ever—at a time when consumers are less loyal than ever. 

When economies falter, companies usually take one of two approaches. Some hunker down, cut costs and staff, and hope to survive. Others zero-in on differentiators like CX to drive growth and boost profitability.

The importance of CX for key metrics like churn, retention, loyalty, new sales, and competitive differentiation is well-established, so not investing in customer experience could be considered akin to saying you are willing to let those mission-critical metrics falter.

The following 15 takeouts from SAP’s 2026 Global Engagement Index Report highlight some of the most common CX pitfalls and opportunities.

1. 82% of consumers say a brand has disappointed them

Modern customers do not go quietly into the bad experience night. A whopping 82% of consumers say a brand has disappointed them, even when the product itself meets their needs. The issue isn’t the product or service; it’s the experience of purchasing and post-purchase care.

This is the essence of the “Engagement Divide”: the distance between what customers expect in the moments that matter, and what brands are actually delivering.

2. 60% do not pay attention to brands anymore and 48% care more about experience

Consumer attention in a difficult economy has shifted from logos and taglines to experiences that feel useful, contextual, and personal. So, what’s a brand to do when 60% of consumers say they simply don’t pay attention to brands and 48% care more about the experience than the product?

This is where CX outcomes become clear: engagement is no longer about shouting louder; it’s about showing up better and building experiences powered by unified data and intelligent orchestration.

3. Left unread: only 16% of customers skim email headlines, while 29% read one or two sentences

Consumer behavior in the inbox shows just how fragile engagement is:

  • Most consumers only read the subject line
  • Others will read one to two sentences before deciding whether to delete or engage further

Combined with the fact that 58% of consumers think most marketing emails they receive aren’t relevant, brands are staring down a massive relevancy problem. Sending more emails into the engagement abyss doesn’t solve this problem, but gaining a holistic understanding of your customers as individuals does.

4. 37% do not think brands personalize to their needs

For well over a decade we’ve been talking about the importance of personalization, but today 37% of consumers believe brands don’t personalize engagements to their needs. Surface-level personalization—names in subject lines, basic segmentation—is no longer enough.

This aligns with our assessment that 79% of companies have low or moderate CEM scores, meaning teams can access portions of shared data and deliver basic personalization, but coordination across marketing, sales, service, commerce, and product teams remains limited. Experiences often feel disconnected, forcing brands to rely on short-term tactics rather than building deeper relationships.

Consumers expect real-time, behavior-driven personalization based on context, intent, and history, not just boiler-plate persona buckets. Customers can see and feel investments in personalization and it matters.

5. 46% say customer service feels too impersonal, while 41% believe brands do not understand them as a person

Considering how much data brands collect, it’s striking that nearly half of consumers (46%) say customer service feels too impersonal.

Customers are asking a simple, and valid, question: “If you have all this information about me, why isn’t my experience better?” When data doesn’t translate into empathy and action, it starts to feel like surveillance, not service.

With 46% of consumers saying service isn’t personal, it should be no surprise that a nearly equal amount (41%) believe that brands don’t understand them as a person. However, 34% agree that AI can help brands better understand them and what matters most to them.

This presents brands with a real-time opportunity: use AI and data to close the perception gap. Instead of just predicting purchases, enterprises should also be anticipating customer needs and reducing friction.

6. 78% of brands say they deliver seamless cross-channel engagement, consumers disagree

Seventy-eight percent of brands say their engagement strategies offer seamless multichannel experiences with glowing outcomes like increased CLV, retention, and advocacy, but consumers are simultaneously reporting little emotional connection and frequent disappointment. In fact, 44% say that brand interactions feel less personal and more generic than ever before.

The takeaway: internal dashboards can create a false sense of success if not tied directly to real customer sentiment and behavioral signals across channels.

7. 54% of enterprises cannot access and use real-time data, and 66% still rely on third-party data

Fifty-four percent of enterprises can’t access and use real-time data. On top of that, 60% suffer from “dark data,” which is information that’s collected but not used throughout the customer journey.

Without real-time, connected data, brands are mostly flying blind. AI, personalization, and omnichannel orchestration don’t fail because the ideas or execution are wrong; they fail because the foundations are.

Although privacy regulations and legislation are increasing while third-party cookies decline, a majority (66%) of enterprises are still heavily reliant on third-party data. Simultaneously, 55% say their data is too unstructured to use effectively.

The lethal combination of overreliance on external data plus underutilized internal data keeps brands from building strong, first-party relationships rooted in trust and value.

8. 78% of brands say AI is essential for customer retention in 2026

AI is everywhere, and 78% of brands view AI as critical to retaining customers in 2026. However, 66% report they can’t use AI to optimize campaign performance in practice, while many also note they can’t utilize real‑time AI optimization in day‑to‑day campaigns.

A quick translation of the above stats: an AI strategy is crucial, but execution is lagging because of fragmented systems, poor data quality, and integration issues.

9. Only 30% share engagement data with a CX or CRM platform

Despite the collective agreement that a comprehensive customer profile is important, only 30% of brands share their customer engagement data within a CX or CRM platform. This means that most brands are attempting to deliver personalized experiences without having a unified engagement core.

If engagement data lives in campaign tools, service systems, commerce platforms, and ERP, but never gets connected via CX or CRM, customers will feel every fracture along their journey.

10. 30% of consumers have used AI agents that act on their behalf

AI is not just an enterprise capability; it’s also a customer behavior. Thirty percent of consumers say they’ve used AI agents to make decisions and act on their behalf when buying from brands.

This is a game-changer when it comes to engagement. Brands are now engaging not only with humans, but also with AI buyers that ruthlessly and continuously optimize for relevance and value. If your systems can’t keep pace, AI will select your competitor whose systems are operationalized for success.

11. When it comes to customer engagement maturity, 79% of brands have yet to integrate data, systems, and teams across their business; only two in five decision-makers see their departments as actually coordinated

The Customer Engagement Maturity (CEM) scoring model assesses how well brands align people, processes, and technology to deliver cohesive, intelligent experiences. Looking at the SAP Engagement Maturity Index:

  • 16% of brands reside at low maturity
  • 63% sit in the moderate middle
  • 21% have high maturity

Despite year-over-year progress, most organizations are stuck in developing or evolving mode, able to execute campaigns but not orchestrate truly connected, enterprise-wide engagement. And leaders agree, with only two in five decision makers believing there is effective collaboration across departments.

12. Just 21% of brands are high-maturity, and they are gaining ground against their competition

High-maturity brands rise above the competition because they connect data and intelligence across marketing, service, sales, commerce, and operations. They use AI and automation to deliver personalized, omnichannel engagement in real-time, at scale.

And the maturity gap is becoming a performance gap. As top performers turn real-time intelligence into growth, the cost of competing with them rises for everyone else.

13. Personalized means personal: 58% of consumers respond positively to localized content

Personalization is more than a word or industry term. It means actually understanding and empathizing with your customer, including their regional traditions and social norms.

When engagement is done right, consumers respond:

  • 63% say their favorite brand delivers seamless, connected experiences across mobile, web, and in-store
  • 58% value localized content and product recommendations
  • 55% appreciate highly personalized content
  • 50% believe their favorite brand uses data to make interactions better

Customers aren’t against data or AI at heart. However, they are opposed to wasted data collection and bad experiences. It’s the job of brands to provide a great CX. If that job isn’t taken seriously, you can bet that other brands are willing to roll up their sleeves to fill the gap.

14. 77% of businesses plan to invest in AI-powered engagement in 2026

When it comes to the future state, 77% of businesses plan to invest in AI-powered customer engagement in 2026, and 76% are investing in omnichannel engagement technologies. At the same time, 29% say their top priority is connecting customer and stakeholder data across marketing, sales, service, commerce, and ERP systems.

The signal is clear: investment alone won’t close the Engagement Divide. The winners will be the brands that invest in connection—of data, teams, and systems—not just in tools.

15. 15% say seamless integration will be the biggest driver of success

Lastly, and possibly most importantly, 15% of businesses believe seamless integration of engagement systems will be the single biggest driver of success. While that may sound like a small number, it captures a critical strategic shift: engagement is no longer a marketing problem or a channel problem. It’s an enterprise discipline that depends on unified data, coordinated teams, and embedded AI.

Artificial intelligence provides an evolving service for businesses. Employing cloud-based systems that can store, analyze, and route data will be the differentiator for brands in the marketplace.

Loyalty is transactional, and driven by great CX and a connected enterprise

Digital engagement has raised the bar when it comes to customer expectations, with more demands and a plethora of competitive choices if a brand doesn’t deliver.

It’s not a big leap to state that better customer experiences increase customer loyalty, which in turn leads to more purchases, augmented product utilization, and increased brand affinity and sentiment. And let’s not forget that an enhanced CLV lowers customer acquisition costs.

After all, loyalty is transactional and forged by the experiences customers encounter. In my conversations with customers across the globe, it’s clear that only the brands with CX truly at the heart of their operations will retain and grow their customer bases in the enterprises of the future.

That ambition relies on a technology foundation that can consistently deliver those experiences at scale. For British-founded luxury fragrance brand Molton Brown, moving from legacy systems to SAP Commerce Cloud provided a high‑performance platform built for peak‑season resilience and continuous innovation. The impact was immediate: 100% uptime during peak trading, even as volumes surged to one order every three seconds during major events.

This kind of reliability is increasingly critical as the moments that shape experience and loyalty expand beyond owned channels. As product discovery shifts to social platforms and AI‑powered assistants, consistent content and availability help the brand remain visible and trusted wherever customers engage. SAP’s evolving agentic commerce innovations are designed for this reality, keeping products discoverable, credible, and actionable across both human and AI interactions.

Ultimately, technology and AI are not the goal—the experience is. The brands that succeed will be the ones that use AI to show up more human, not less, turning insight into relevance and automation into trust.

The future of CX is for companies that operationalize intelligence across the enterprise—connecting data, systems, and teams so AI can orchestrate experiences, not just analyze them.


Manos Raptopoulos is global president of Customer Success Europe, APAC, Middle East & Africa, and a member of the Extended Board SAP SE.

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SAP at Hannover Messe 2026: Operationalizing Agentic AI to Drive Resilient, End-to-End Manufacturing

Manufacturing is entering a decisive moment. Rising costs, intensifying global competition, expanding regulatory requirements, and the rapid acceleration of agentic artificial intelligence are reshaping how products are designed, planned, produced, delivered, and serviced. Volatility is no longer an exception; it is the operating environment.

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—even as disruption is constant.

At Hannover Messe 2026, the world’s leading stage for industrial transformation, SAP will introduce a new set of AI‑powered 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.

Build a more agile, resilient, and customer-centric supply chain with AI

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’s 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.

SAP 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‑time prediction and execution, working to deliver resilience, regulatory readiness, and measurable customer impact from day one. Creating tangible ROI is what matters most—whether 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’s focus at Hannover Messe is end-to-end supply chain orchestration with AI.

SAP helps manufacturers connect processes and data not only across internal teams, but also across company boundaries—with suppliers, logistics partners, and service providers. By using AI agents to connect design, planning, procurement, manufacturing, logistics, service, and asset management—and by integrating seamlessly with ERP and line-of-business systems—SAP 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, SAP 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 SAP 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—including operations and work centers—and 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—such as alternative components or rescheduling options—that planners can review and approve, reducing manual work and keeping production aligned with real‑world 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—driving 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‑driven actions to help teams resolve issues faster and improve operational reliability. General availability is planned for Q3 2026.
  • Asset Health Agent analyzes time‑series 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‑based 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—reducing 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‑time, 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 SAP SuccessFactors Workforce Scheduling, skills, certifications, availability, and labor rules are aligned with real-time operational demand so workforce plans can adjust automatically as production changes.

In logistics, SAP S/4HANA Cloud Public Edition, AI‑assisted backorder processing, together with the new SAP Logistics Management 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 SAP Asset Performance Management helps teams identify risks earlier, prioritize actions, and reduce unplanned downtime. In parallel, SAP Document AI can automate the processing of incoming quality certificates, improving throughput, data quality, and compliance at scale.

Regulatory readiness and what’s next

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

Expanded SAP Business Network capabilities also deliver built‑in e‑invoicing 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—where 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 SAP Sapphire.

Visit SAP at booth F08 in Hall 15 at Hannover Messe 2026, April 20–24, to see how AI-infused orchestration, embedded AI agents, and end‑to‑end supply chain applications are redefining manufacturing.


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

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