Enterprises are embracing agentic AI at speed, embedding autonomous AI agents into business processes and experimenting with agents in front-office activities such as marketing and customer service, as well as in operational areas such as shipment tracking, demand forecasting, and supply chain optimization.

Agentic AI builds on the economic potential of generative AI, which McKinsey has estimated could add US$2.6 to $4.4 trillion annually to the world economy. This represents the next stage of enterprise AI adoption: a shift from content generation to autonomous execution, and from isolated pilots to operational deployments.

Agent sprawl

That shift creates a new governance challenge. Agent sprawl occurs when AI agents are created, deployed, or connected across systems faster than the enterprise can inventory them, assign ownership, control permissions, monitor behavior, and optimize or retire them when they are no longer fit for purpose.

Underscoring this shift, a recently published agentic AI survey conducted by SAP LeanIX found that 98% of companies have already deployed AI agents or plan to do so. But as adoption accelerates, governance is struggling to keep pace. According to the same report, less than half of the organizations surveyed have visibility into an inventory of AI agents.

The mechanics of agent sprawl are familiar to any technology leader who has navigated a wave of SaaS adoption. Individual teams, motivated by genuine productivity goals, deploy agents independently. Each one is designed for a specific task—a marketing automation agent, a supply chain monitoring agent, an HR onboarding bot—and each works in isolation. Without a centralized platform or governance framework, the organization accumulates a fragmented landscape of agents that do not interoperate, cannot be audited consistently, and accumulate technical debt faster than they generate value.

Gartner estimates that by 2028, the average global Fortune 500 enterprise will have more than 150,000 AI agents in use, yet only 13% of organizations believe they have the right governance in place to manage those agents. Max Goss, senior director analyst at Gartner, told his audience at a London conference in April: “As CIOs and IT leaders see an explosion of AI agents across their organizations, many are contending with an ungoverned sprawl of agents that expose their organizations to a range of risks, including misinformation, oversharing, and data loss.”

He added: “Many organizations resort to blocking or restricting the use of AI agents, but this is not a long-term solution. If employees are unable to work in the sanctioned tools, they will likely go around the organization’s controls and start using shadow AI, which presents far greater risks. Organizations need to find a balance where they can govern agents and manage sprawl, but also safely empower employees to innovate with these tools.”

Agents typically need broad, cross-environment permissions to function, but those permissions are rarely governed with the same rigor applied to human users. The risk posed by unmanaged or rogue AI agents in the enterprise is therefore real and growing.

AI agent security concerns

Publicly reported enterprise-security examples also point to agents leaking sensitive information or acting outside their intended scope, including cases where malicious instructions caused agents to bypass guardrails, delete production records, or trigger irreversible financial transactions.

The security concern is what registers most sharply with enterprise technology leaders. With chatbots and early generative AI, a security failure typically meant bad output: an inaccurate or inappropriate response that could usually be corrected after the fact. In the agentic era however, the consequences of an agent failure or security breach can be far more damaging because agents can take action, call tools, access systems, and initiate business processes.

That is why agent governance is no longer only an IT operations issue. It increasingly touches board-level concerns: risk ownership, regulatory exposure, data protection, auditability, operational resilience, and accountability for autonomous decisions.

The emerging AI governance platform

Leading organizations are beginning to treat agent governance not as a compliance overhead but as a strategic capability that determines whether AI investments compound as advantages or liabilities. As a result,  effective AI agent governance has quickly become a boardroom topic and is contributing to the emergence of a new platform category: the AI governance platform.

The category is still forming, but its purpose is becoming clear. Enterprises need a way to discover agents, understand what they do, control what they can access, verify whether they are compliant, and monitor how they behave in production.

SAP is one of the agentic AI pioneers in this emerging category. Through its 2023 acquisition of LeanIX, SAP gained a foundation in enterprise architecture management. This has quickly become a recognized differentiator for SAP AI Agent Hub—positioning AI artifacts like agents, models, and MCP servers within the full architecture and business context of the organization.

SAP AI Agent Hub builds on this foundation as a command center for managing and governing AI agents and related AI assets across an enterprise, even when they come from different vendors and run on different systems.

As SAP CTO Philipp Herzig explained on stage at this year’s SAP Sapphire event, SAP AI Agent Hub is intended to provide a governance layer of record for the enterprise agent ecosystem. “Agents are everywhere,” he said. “Some are great, some are not, and almost no one has a consistent picture—no central governance, no clear view of what each agent does, whether it adds value or whether it adheres to your policies.”

He added: “SAP AI Agent Hub changes that. One entry point and command center to discover, manage, and govern all AI agents, LLMs, and MCP servers in your landscape—vendor-agnostic. [SAP] AI Agent Hub allows you to discover all your agents in context: your landscape, your business processes. Once you have identified the right agents, you can control their risk and define architectural decisions or compliance rules.”

A closing window

Given the pace of AI agent deployment, the window for implementing effective enterprise governance before a serious incident occurs is narrowing. For CIOs, CEOs, and company boards, the question is no longer whether to govern AI agents. It is whether governance gets designed into the architecture from the start or retrofitted after the first serious failure.

Organizations that treat agent governance as a strategic priority in 2026 will be better positioned to scale AI as a durable competitive advantage. Those that defer could spend 2027 cleaning up: in enterprise technology, the cost of speed without structure eventually gets paid. But with AI agents, the bill arrives faster—and at greater scale—than anything that has come before.

SAP has been recognized as a Leader in the first-ever Gartner® Magic Quadrant™ for Digital Twin of an Organization. This recognition follows closely behind SAP’s acknowledgement as a Leader for Process Intelligence Platforms earlier in 2026.

In today’s dynamic business landscape, characterized by the ongoing rise of AI and the need for adaptation in the face of rapid change, companies that understand the impact of operational adjustments—before those changes actually take effect—are best-placed to make the right decisions, faster.

A digital twin of an organization (DTO) mirrors and analyzes how businesses operate and adapt in order to foresee the implications of new ways of working, track realized value, and increase orchestration potential across people, AI agents, processes, applications, and data. This capability is an emerging enterprise imperative as autonomy gains a foothold, and SAP maintains an ongoing dedication to innovation and customer satisfaction in this area.

SAP offers a unique combination of AI-native DTO capabilities that span process intelligence and modelling (SAP Signavio solutions), enterprise architecture management (SAP LeanIX solutions), digital adoption (WalkMe solutions), automation (SAP Business Technology Platform), SAP’s AI solution (Joule), and more, all united within the SAP Business AI Platform. Together, these capabilities can offer businesses a dynamic DTO with continuous observability and AI-driven actionability features that help support agentic readiness, enterprise knowledge activation, transformation management, and value orchestration.

Dee Houchen, chief marketing officer at SAP Signavio, said, “Our aim is to help our customers create a repeatable, sustainable, AI-native transformation capability, rather than treating inevitable organizational adjustments as simply a series of independent projects. Driving greater enterprise observability, supporting smarter, real-time decision-making, accelerating transformation, and ensuring business outcomes are measurable are all key to this approach, which is why effective DTO is such a fundamental benefit to modern organizations.”

The Gartner® Magic Quadrant™ methodology provides a clear, research-based overview of evaluated vendors in a given market. This year’s Magic Quadrant assessed 18 vendors across a range of criteria, including market understanding, offering strategy, innovation, product and service quality, customer experience, and more, as well as a broad range of key use cases: digital twin for business operations, digital twin for customer excellence, digital twin for governance, risk, and compliance, and digital twin for strategy realization.

The Gartner report also provides useful context regarding the state of the DTO market. We feel we were recognized as a Leader in the report thanks to our capacity to:

• Uniquely serve all four transformation dimensions (people, processes, applications, and data) in a dynamic, virtual model
• Enable full agentic life cycle management, allowing organizations to observe, govern, and optimize AI agents as organizational actors in reaching full enterprise potential 
• Support organizations in enterprise knowledge activation, making enterprise context actionable  

The Gartner Magic Quadrant equips businesses with valuable insights to make informed decisions. For a complimentary copy of the latest resource featuring SAP solutions (Gartner, Magic Quadrant for Digital Twins of an Organization Platforms, Marc Kerremans, David Sugden, 27 July 2026) visit https://www.signavio.com/downloads/analyst-reports/dto-2026/.

Lucas de Boer is global marketing program lead for SAP Signavio.

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner and Magic Quadrant are trademarks of Gartner, Inc and/or its affiliates.

WALLDORF — SAP welcomes the decision of the German Federal Cartel Office (Bundeskartellamt) to conclude its preliminary inquiries and not to initiate abuse proceedings against SAP.

As the authority states, SAP customers and partners have sufficient and permissible technical options to extract data from SAP systems and use it in solutions from other providers. The SAP API Policy does not restrict these capabilities.

Regarding process mining, the Bundeskartellamt notes that SAP offers a range of competition‑compliant licensing models, including options without SAP Signavio.

The Bundeskartellamt’s assessment reinforces SAP’s commitment to providing customers with non‑discriminatory and practical access to their data, while ensuring freedom of choice in the use of both SAP and third‑party solutions.

The state of customer experience in 2026 can be summed up simply: customers have never had more ways to interact with your brand, and they’ve never been less tolerant about friction when engaging.

While the power of technology is at its apex, so are expectations. And the gap between the two is where revenue goes to die.

Brands using AI to deepen human connection by freeing up sellers, marketers, and service agents to focus on empathy, trust, and complex problem-solving are pulling ahead. Those still bolting AI onto fragmented systems, or using it purely as a cost-cutting measure, risk falling further behind.

To help organizations address the rapidly changing factors impacting CX, we’re proud to debut our first quarterly “State of” reports. Designed to pull together the latest research and data across sales, service, marketing, and e-commerce, these thought leadership pieces are available without a gate because we know that experience and expertise matter, and we want to share ours with you. (You can find links to the reports at the end of this post.)

The key takeaways from each report demonstrate that CX is no longer a single department’s job. Rather, it’s a cross-functional discipline, and the stakes for getting it wrong are higher than ever.

The cost of bad experiences is staggering

Let’s start with the number that should be pinned at the top of every leadership deck this quarter: bad customer experiences have put $3 trillion in global sales at risk in 2026, with consumers actively cutting back $2.1 trillion in spending and walking away entirely from $865 billion worth of it, according to Forbes data cited in our State of Service report. That’s not churn. That’s customers voting with their wallets in real time.

And they’re not quiet about why. A striking 82% of consumers say a brand has disappointed them, and 60% admit they don’t pay attention to brands even when their product needs are being met. Translation: satisfying the transaction isn’t enough anymore. If the experience around it feels disorganized or impersonal, customers check out.

On the service side specifically, 75% of consumers say they’re put off by disorganized brands that pass them between multiple people or teams just to solve one problem, and 46% say service flat-out feels too impersonal.

The combustible combination of sky-high financial risk and low tolerance for friction is forcing every customer-facing function to rethink how it operates.

That’s the backdrop. Now let’s talk about what’s actually happening in each corner of the customer journey.

AI is everywhere, trust in it is not

Every function is racing to embed AI, with good reason. AI-driven traffic to U.S. retail sites is up 4,700% year over year, and almost 60% of consumers have already used AI to shop, as cited in our State of E-commerce report.

On the marketing side, our report notes that AI has moved from experiment to foundational: 33% of marketing leaders are using it for hyper-personalized engagement, and 31% say predictive insights and personalization have been a top priority all year.

Meanwhile the State of Sales and Revenue report points out that digitized suppliers leveraging AI are outperforming their peers on sales goals by a jaw-dropping 110%.

But here’s the twist that ties it all together: customers don’t actually love the AI they’re interacting with.

SAP’s State of Service report underscores that point specifically:

• 79% of Americans say they strongly prefer human support over an AI agent
• 63% don’t believe AI can replace humans in service roles at all
• 89% believe brands should always offer the option to talk to a real person
• 81% believe AI is primarily being used to save the company money, not to improve their experience.

That’s the tension every function needs to sit with. AI is delivering real, measurable business value, but if customers believe that AI was deployed to cut costs rather than serve them, you might win efficiency but lose the relationship.

Trust is the currency, and it’s getting harder to earn

Each one of the reports circles back to the same word: trust. In marketing, 61% of B2B buyers say trust and credibility are the most important thing content can deliver, ranking above lead generation. Consumers are leaning on peer and creator trust more than brand messaging, too: 76% of brands report that sponsored content with creators now outperforms traditional advertising, and in social commerce, 45% of Gen Z shoppers say they’re more likely to trust a product once it goes viral.

On the e-commerce side, trust shows up as transparency. With tariffs pushing import costs up 15-30% across major categories, brands that explain price increases rather than quietly passing them along are building goodwill that pays off in retention. And in sales, the numbers show that your existing customers–the ones who already trust you–are an underused asset: 45% of revenue leaders are now focused on improving handoffs across marketing, sales, and service, while 39% are chasing expansion and upsell revenue instead of only hunting net-new logos.

The people problem behind the technology story

There’s one more thread that doesn’t get enough attention in the AI headlines: the humans delivering these experiences are stretched thin. Call center turnover is running 40-45% in 2026, spiking to 55-60% in high-stress sectors, while replacing a single agent can cost up to $46,000 when accounting for lost productivity.

As AI absorbs the easy tickets, what lands on human agents is the hard stuff: it’s complex, is emotional with high-stakes, and burnout is quietly eating away at CSAT and first-contact resolution scores. This matters because customer experience isn’t just a technology stack or a personalization engine. It’s fundamentally delivered by people; whether that’s a service agent handling an escalation, a seller navigating a buying committee, or a marketer trying to sound human in an AI-saturated feed. Protecting the people doing that work isn’t a wellbeing initiative separate from CX strategy. It is CX strategy.

Fragmentation is the enemy of good CX

If you weave every stream together, the state of CX has one clear directive: stop treating AI, data, and channels as separate initiatives owned by separate teams, and start treating the customer experience as the single thread that runs through all of them.

That means AI-shopping agents that use clean, structured product data. It means first-party data strategies that replace the crumbling third-party targeting most marketing was built on. It means service and sales teams that know exactly when to step back and let self-service work, and exactly when to step in and be human. And it means service organizations that give their people better tools instead of just more automation.

Future success won’t be shaped by the brands with the most AI; it will favor the brands that make customers feel understood, even as the experience becomes more automated. That’s not a technology bet. That’s a trust bet, and right now, trust is in short supply.

You can find our “State of” reports here:

• State of Sales
• State of Service
• State of Marketing
• State of E-commerce

Jessica Keehn is chief marketing officer of SAP Customer Experience.

Modern B2B buyers expect seamless experiences across web, mobile, marketplaces, and partner portals. In fact, 84% of B2B buyers say it is important for suppliers to operate across multiple online and offline channels.*

To meet these expectations, organizations must move beyond siloed commerce channels toward a connected autonomous CX model that integrates commerce, order sourcing, fulfilment, and customer support across the full customer journey.

The Advanced Success Plan for SAP Customer Experience supports this shift by accelerating omnichannel capability build-out through outcome-based governance. It helps organizations move from fragmented execution to coordinated operations—enabling consistent cross-channel experiences, aligning commerce with sales and service execution, and improving conversion and repeat purchase through end-to-end alignment.

Reality of B2B buying

B2B buying is rarely linear anymore. Buyers often switch between digital channels, sales teams, and service touchpoints before deciding. Research from McKinsey’s B2B Pulse highlights that buyers typically engage across multiple interaction channels before making a decision.**

This reflects how digital commerce has become a core part of the buying process, with 58% of global B2B retailers selling on at least three e-commerce platforms.†

At the same time, expectations have shifted. Consistency across channels is assumed, digital self-service is often the starting point, and speed and transparency are baseline requirements.

That creates a dual challenge for organizations: improving customer experience while also managing increasing operational complexity behind the scenes.

Convergence of commerce, sales, and service

B2B environments combine complex operations with tightly connected customer journeys. Organizations must manage customer-specific pricing and contracts, large and dynamic product catalogs, multi-step approvals, distributed fulfilment models, and integrations across commerce, ERP, sales, and service systems. Customers, however, do not see this complexity. They experience a single journey, from discovery to purchase, fulfilment, and support, and expect it to feel seamless.

A typical journey may include discovering products online, aligning pricing with sales, placing orders through self-service channels, and resolving issues via service interactions. Expectations for real-time visibility, fast issue resolution, and consistent engagement continue to rise, as highlighted in research such as DHL’s B2B E-Commerce Trends. The same DHL report also shows that 78% of B2B retailers expect website sales to grow over the next three to five years, which reinforces how central digital channels have become.†

Yet many organizations still operate in silos. The result is often inconsistent data, limited visibility across interactions, slower issue resolution, and disconnected customer experiences. This is why omnichannel transformation is not about adding channels, but about connecting commerce, sales, and service into a unified operating flow.

Process excellence as a foundation

As complexity increases, end-to-end process alignment becomes critical. Customers experience outcomes, not systems, and those outcomes depend on how well processes are connected across commerce, sales, service, and fulfilment.

Breakdowns typically occur when sales agreements are not reflected in commerce systems, fulfilment is not aligned with order promises, service teams lack customer context, or data differs across channels. These are not isolated system issues, but symptoms of disconnected processes.

In practice, that can mean a customer sees one price in the portal, a different one in the quote, and another one in the order confirmation. It can also mean service teams have to ask customers to repeat information that already exists elsewhere in the organization. Even when the underlying technology is in place, the experience still feels broken if the process is not connected.

Organizations that invest in process excellence are better positioned to deliver consistent experiences, reduce friction, improve operational efficiency, and scale complex B2B models. Process alignment also makes it easier to respond to change, because teams can adapt faster when the underlying journey is not held together by disconnected handoffs.

Why omnichannel matters

Omnichannel in B2B is not just about offering more ways to buy. It is about making those ways work together. When the customer starts on one channel and finishes on another, the handoff needs to feel natural. If not, the customer experience becomes fragmented very quickly.

That matters because B2B buyers are increasingly comparing their business purchasing experience to the consumer experiences they already know. They expect simple navigation, transparent pricing, reliable order updates, and a service team that understands the full context of the account. In other words, they want the convenience of digital commerce without losing the support and complexity that B2B purchasing often requires.

This is also where many companies struggle. They may have a strong storefront, but weak back-end coordination. Or they may have good sales support, but poor visibility once the order has been placed. Omnichannel transformation closes that gap by connecting the customer-facing experience with the operational processes behind it.

Accelerating outcomes with the Advanced Success Plan for SAP Customer Experience

The Advanced Success Plan for SAP Customer Experience helps organizations accelerate omnichannel capability build-out through outcome-based governance and alignment between strategy and execution.

Rather than focusing only on implementation, the emphasis is on measurable outcomes across the full customer journey. This includes enabling consistent omnichannel experiences, aligning SAP Commerce Cloud, SAP Sales and Service Cloud, and fulfilment processes, managing catalog and contract complexity at scale, improving order sourcing and fulfilment coordination, and strengthening end-to-end process alignment.

The goal is to ensure all capabilities operate as one connected system rather than separate functions.

That becomes especially important in B2B environments where a single transaction can involve multiple stakeholders, custom pricing rules, approval steps, and several systems working together at once. Without clear governance and alignment, even well-designed digital tools can create confusion instead of clarity.

With the right operating model, however, organizations can turn complexity into a strength. They can reduce friction for customers, improve efficiency internally, and create a more reliable buying experience across every channel.

The Advanced Success Plan for SAP Customer Experience includes access to Business Process Best Practices which helps customers understand the end-to-end process flow and best practices for executing business processes across SAP Sales and Service. This service showcases reference processes and bridges the gaps that can occur during rapid implementations of solutions in complex landscapes or when implementation of multiple solutions creates fragmented processes without taking into consideration unique end-to-end view.

Conclusion

Omnichannel commerce and B2B digital transformation are reshaping how organizations engage customers and deliver value. Success depends on connecting commerce, sales, service, and fulfilment into a unified operating model supported by strong end-to-end processes.

Organizations that focus on process excellence and outcome-based governance are better positioned to scale effectively and meet rising customer expectations. The Advanced Success Plan for SAP Customer Experience enables this by connecting strategy to execution and supporting consistent outcomes across the customer journey.

For B2B companies, the real shift is not just digital adoption. It is building a model where channels, processes, and teams work together in a way that feels simple to the customer, even when the operation behind it is complex.

Nikola Stojanovski is a product manager for the Advanced Success Plan for SAP Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for SAP Customer Experience.

*Digital Commerce 360, 2025
**McKinsey, 2021
†DHL, 2025