AI agents are writing code and translating legacy applications for use in the SAP cloud. Sonja Liénard, head of ABAP platform at SAP, explains what this means for the ABAP programming language and ABAP platform.

In an interview, Liénard talks about the evolution of SAP’s proprietary programming language and ABAP platform, and discusses what the innovations announced at SAP Sapphire will mean for customers.

Q: In our first conversation, you explained what ABAP is, what the future looks like, and why agentic AI will change the market. Let’s start from there and then dive deeper. How does ABAP interact with other development technologies in today’s SAP landscapes?

Sonja Liénard: ABAP has been around for over 40 years and has been evolving ever since. With the era of agentic AI, we are now reaching the next stage of that evolution. The modern version of the development model is ABAP Cloud, which has been developed from the outset according to the guiding principles of openness and comprehensive support for the business logic.

We have robust, well-defined APIs that are interfaces to the outside world and offer a full environment with Open Data Protocol (OData) services, modern front ends, and an integration layer. This enables the development of modern web applications. This is in addition to SAP Business Technology Platform (SAP BTP) extensions and an external system like SAP Integration Suite, which can also be integrated.

We currently use Eclipse as a development environment. Starting in Q2 2026, ABAP development tools will also be possible in Visual Studio Code, which is a milestone. The community was quite vocal in requesting this and it was an open door for us. Visual Studio Code is gaining ground and is currently the preferred IDE (integrated development environment) for many developers. Many AI extensions on the market being optimized for it first.

We have redesigned the architecture and are pursuing an open IDE strategy where we can also offer further IDEs for ABAP development. By opening it up, we now have a rich third-party ecosystem that we can leverage for AI, such as GitHub Copilot and Amazon Q.

In addition, we have published an ABAP MCP (Model Context Protocol) server that lets ABAP developers benefit from the entire AI tooling and ecosystem. This is a major, important step and an impressive example of interoperability. Furthermore, we can still rely on the strength of ABAP business logic. With this approach, we are combining the open IDE strategy with a high rate of innovation.

You mentioned the ABAP MCP server. What is that exactly?

Liénard: MCP stands for Model Context Protocol and is an open standard for AI agents to interact with external tools and systems in a structured manner. It is a universal language that AI agents use to ask questions, trigger actions, and retrieve results.

The ABAP MCP server provides ABAP development capabilities based on this protocol. Any agent that supports MCP can interact with ABAP code and our ABAP systems in an intelligent, agent-driven approach. It is a new channel through which we can make our ABAP-specific capabilities available to the outside world.

The ABAP MCP server is an important building block for everything related to agentic AI and an important technical foundation for our new Custom Code Assistant for SAP S/4HANA transformation. The ABAP MCP server for Eclipse is available as of Q2 2026.

What are the risks of using AI in SAP enterprise systems and how do you address them?

Liénard: The entire AI market is incredibly dynamic, fast-paced, and characterized by different interests. As such, we need to carefully examine which solutions are durable, robust, and trustworthy enough to run the world’s business processes. We want our solutions to remain secure, compliant, and true to everything SAP stands for.

We must put our core mission at the heart of all decisions. ABAP platform is known for its ability to run large enterprise business. Our customers and partners trust this capability The AI solutions on the market do not qualify for this through their ability to build short-lived solutions, but instead by supporting our core capabilities. That’s why it helps to take a step back, look at the big picture, and make sustainable decisions, but also to remain open to revising past decisions in response to major shifts in the market.

The second point is the accuracy of the code. AI can generate seemingly plausible code that contains subtle errors. To counter this, we rely on a combination of human review and thorough agent testing, keeping humans in the loop at every critical step. AI agents handle the quality checks and validation, with developers making the judgement calls.

Another risk is the loss of business logic during the transformation. We want to help our customers migrate their legacy applications to modern solutions. We are developing custom code management agents for this purpose. The first was released in June. It is crucial for our customers and partners to retain their business logic during the transformation.

Lastly, security and data protection are central topics. AI models always need context to be effective. In the enterprise environment, this context can contain sensitive business data. That’s why we are taking a very careful approach: ABAP AI services only operate within established SAP compliance and trust frameworks, for example. Customers always have control over what is shared and what isn’t.

Let’s talk about SAP Sapphire in 2026. What innovations from your area were presented?

Liénard: SAP Sapphire is also a very important conference for ABAP AI. In Q2 2026, we published the first release of the ABAP development tools for Visual Studio Code, initially in the ABAP Cloud scope including SAP Fiori app development and with integration of GitHub Copilot and Amazon Q as AI solutions. Another goal is to support classic ABAP development in Visual Studio Code; additional ABAP object types will follow throughout the year. Also, as of Q2 2026, the ABAP MCP server for Eclipse and Visual Studio Code are generally available to connect third-party solutions, particularly AI-specific third-party tools, to the ABAP system.

We also delivered the first Custom Code Assistant in Q2 2026. The feedback is promising. This enables us to automate and accelerate code migration significantly. In this approach, all communication between legacy migration tools and new agents will take place through an engagement layer. Our overall migration strategy, which we presented at SAP Sapphire, comprises seven different agent families across all phases of a migration project, from planning to execution.

Smaller customers and those with older system versions often found it difficult to access AI tools. What is changing here?

Liénard: The barriers to entry are getting much lower. We are switching from users-per-month billing to a usage-based model. Billing will be according to actual usage, based on “AI units” with individual prices. This will help make it easier to use our AI solutions. Customers will be able to better plan how much they want to spend on AI solutions.

In addition, as of Q2 2026, we introduced a side-by-side service that enables the use of all AI solutions, regardless of release. The availability of ABAP AI will be expanded to include SAP S/4HANA Cloud Private Edition for all releases from 2021 and later. This enables us to support most of our customers with AI capabilities, even those that have older releases.

How do ABAP and AI agents fit into SAP’s longer-term product vision?

Liénard: We are following the overall SAP strategy, of course. It was apparent at SAP Sapphire that agentic AI is the new theme. In the past, we had Infrastructure as a Service, Platform as a Service, and Software as a Service. Agentic AI solutions are now being added.

I like to use three concentric circles to describe our vision: ABAP Cloud is at the center, as the modern, clean-core variant of our language for long-term stability. The second circle is the ABAP AI layer: developer tools for code explanation, code generation, and ghost texting. The outer circle is comprised of AI agents, a network of specialized agents for complex and multi-step tasks such as transformation, migration, and quality validation. They can also take on development tasks, however, significantly reducing the required effort. This can free up time for decisions regarding business logic and architecture, as well as for verifying quality.

The circles coexist and reinforce each other. The fundamental orientation of the platform and the core of the solutions remain stable. Agents and AI skills complement this in the best possible way.

What milestones should customers and partners pay attention to?

Liénard: There are four main milestones. The development environment for Visual Studio Code and the MCP server were released in Q2 2026. This enables the development of AI agents in an open IDE ecosystem. We released the first agent for the custom code migration strategy in Q2 2026, along with the extension of ABAP AI to include SAP S/4HANA Cloud Private Edition release 2021 and later. A second agent for clean core transformation is planned for Q3 2026. And we will continue to develop multi-agent orchestration and add more agents to the portfolio in the course of 2026.

Do you have any other takeaways to share?

Liénard: Development should be seen as an opportunity. It’s all about development and collaboration. ABAP and developers remain a strong team. AI will not change anything here. ABAP has a long track record of successful reinvention. AI is just the next chapter, taking over routine tasks and creating freedom for what creates value: knowing your business, making architectural decisions, providing high quality, and meeting security and compliance requirements.

Customers and developers can trust SAP’s AI to be implemented reliably: with a clear road map and high quality, security, and compliance standards that are critical for enterprise systems. We work closely with the community and our customers and partners. That is a key success factor.

This year’s SAP for Energy and Utilities Conference, held in Toulouse, France, marked a notable first: the inaugural presentation of the Energy and Utilities Innovation Award. Companies whose projects stood out were honored in the categories AI, Innovation, Transformation, Customer Experience, and Best Team.

AI as a key element

In the AI category, the Austrian energy company OMV prevailed with its SAP Business AI transformation project. Building on an existing SAP S/4HANA landscape, the transformation focused on intelligent automation, advanced analytics, and AI-driven decision-making in core business processes. A key factor for success was a step-by-step approach: instead of a hasty implementation, OMV first laid a solid foundation and introduced AI in a targeted manner into the user experience and business processes. The focus was on regulation, security, and continuous evaluation. The clear principle was to standardize, integrate, and establish a stable data foundation before it scaled more broadly. Early in the process, the company relied on Joule in SAP SuccessFactors solutions and SAP S/4HANA. In the next step, the transformation will continue so OMV can make even greater use of AI.

Intelligent water supply

With a data-driven platform for monitoring its water network, the Belgian water utility Farys was recognized by the jury in the Innovation category. With the help of SAP technology and AI, the utility can now deploy resources more efficiently and optimize its processes in a targeted way. Water leaks can be detected early before greater damage occurs, water quality issues can be predicted, and energy consumption can be reduced. The result: less downtime, lower repair costs, and a noticeably better quality of service. Having a unified solution also fosters cross-departmental collaboration by breaking down existing data silos. In the future, risk assessments for pipelines and facilities will be integrated, and data-driven decisions will help determine where repairs will have the greatest impact. With this strategy, Farys is preparing its infrastructure for the demands of climate change.

Achieving goals through teamwork

E.ON UK won the Best Team category with its SAP S/4HANA transformation project. With its group-wide project running from 2021 to 2027, the company aims to standardize processes and build a future-proof, scalable IT landscape. The central challenge was to consolidate various legacy systems in a highly regulated market. What sets this project apart is the close collaboration between the company, IT, and external partners. The company used workshops, road shows, and a targeted key user network to focus on team culture and cohesion from the very beginning. The result is not only a successful technical transformation, but above all a lived team culture—a key factor to the project’s success.

A new data foundation

In the Transformation category, Electrica Furnizare came out on top. The starting point was a fragmented system in which data was scattered and an overarching overview was missing. The company’s existing infrastructure was neither scalable nor able to respond flexibly to growing regulatory and customer requirements. With the introduction of SAP S/4HANA combined with SAP Business Technology Platform (SAP BTP), SAP Customer Experience solutions, and SAP Business AI, Electrica Furnizare achieved one of the largest transformations in the utility sector. The result: a single, reliable data source for all departments, end-to-end optimized processes, and a solid foundation that paves the way for future innovations and the full deployment of AI capabilities.

Better customer service through comprehensive modernization

Loudoun Water’s far-reaching modernization project won the Customer Experience category, with the company using SAP S/4HANA, SAP Service Cloud 2.0, and SAP SuccessFactors solutions to optimize its processes. With the introduction of SAP Service Cloud 2.0, Loudoun Water is the first utility company worldwide to take this step. The effort paid off: customer service is faster and more modern, work orders are better organized, billing and payments are managed more efficiently, and time tracking for employees has been simplified. The migration was carried out in a single, coordinated step, creating a future-proof, scalable foundation on which Loudoun Water can further expand its position as a technology leader in the industry.

Innovation as a driver of the energy transition

The winners of the first Energy and Utilities Innovation Award demonstrate the wide range of possibilities through which companies in the energy and utilities sector are actively shaping digital transformation. Whether AI-driven decision-making processes, intelligent infrastructure monitoring, or a consistent realignment of the IT landscape, all the projects have one thing in common: they rely on solid foundations, step-by-step implementation, and close collaboration among all stakeholders. Melanie Fiolka, go-to-market & community engagement lead for Utilities at SAP, summarizes it as follows: “The energy and utilities industry is undergoing profound change. The winners of the first Energy and Utilities Innovation Award demonstrate how vision is turned into tangible value through clear strategies, solid data foundations, and the adoption of AI.”

The award makes it clear that innovation in the industry is no longer the exception, but has become a strategic necessity.

A new study by SAP and Oxford Economics has revealed businesses around the world are increasingly driving positive return on investment (ROI) from AI, even as challenges continue to accrue.

While the amount the average global business spends on AI increased slightly to US$28 million this year, the level of ROI from that investment has spiked. Globally, companies expect to drive ROI of 21% this year (US$6.3 million), up from 16% last year. That ROI is expected to grow to 38% in two years’ time (US$15.9 million).

Agentic AI is central to those ROI expectations. In the next two years, average ROI from agentic AI is expected to reach US$17.6 million, more than quadrupling from last year’s estimates (US$4.3 million).

These insights have been revealed in new global research, Value of AI Report 2026, which surveyed 2,600 business leaders across 13 countries.*

Commenting on the research, SAP Chief AI Strategy Officer Sean Kask noted, “AI has moved from experiment to execution, and that’s beginning to show real returns. But there’s still a long way to go. Because AI that lacks context—whether that’s processes, data, or governance—at best creates activity without outcomes and at worst creates risk.”

AI inching closer to enterprise maturity

While global investment in AI increased slightly from US$26.7 milion in 2025, there were significant changes in key markets. Investment increased significantly in Brazil, UK, Australia, and Germany, while leading markets like China and India saw funding decreases.

Today, almost a third of all tasks (30%) in the average business are supported by AI, a figure expected to increase to 48% in two years. Yet, while strategic investment in AI has almost doubled year-on-year to 17%, piecemeal approaches remain by far the most prevalent (41%).

Some of this may be a leadership problem. Under a half of companies have a dedicated AI leader responsible for AI adoption (46%), clear frameworks about AI development (52%), or even training on AI capabilities and risks (41%).

Yet, despite those challenges, 69% of businesses are satisfied with their current AI ROI, even though more than two-thirds are not convinced AI is achieving its full potential.

Some of this optimism is due to agentic AI, since over eight in 10 (83%) businesses say agentic AI has moderate to very high potential to transform their organization. Yet, it is still early days for the technology, with only three percent of businesses saying they are fully prepared for agentic AI, while the majority say they are either partially prepared or not prepared at all.

Global businesses meeting key AI challenges

Organizations are facing a range of challenges achieving ROI from AI, including data, workforce, and governance issues.

Data quality remains the biggest challenge for global organizations. The number of businesses that say they are data ready for AI dropped from last year, with 73% of companies revealing challenges with incomplete data. And that is impacting day-to-day work, with 79% of businesses experiencing rework, delays, or backlogs due to low quality AI outputs.

Similarly, businesses are managing the workforce impacts of AI. Almost eight in 10 businesses (78%) are either unsure or agree their company upskilling is not keeping up with the evolution of AI tools. And just one percent of respondents said AI will have no impact on their workforce planning. Meanwhile shadow AI use is increasing year-on-year, with 69% saying it happens at least occasionally.

“The next step in achieving value will be to integrate AI deeply with contextual data and processes,” Kask said. “But businesses across the world must understand AI often provides value that is harder to measure than expected, and risk that moves faster than most governance can keep up with. Businesses are quickly discovering that AI governance plays a foundational role in unlocking the value from AI.”

Governance is a critical obstacle in the way of enterprise AI value. Just 12% of businesses say either their skills or their processes and frameworks are fully ready to govern AI effectively.

These issues may be exacerbated in an agentic future. Today, 38% of companies do not have a human-in-the-loop process for agentic workflows, 37% don’t have permission and access controls for agents, and only 44% have a registry of the agents in their business. This is critical, given more than two-thirds of businesses (69%) either agree or are unconvinced if they are deploying agents quicker than they can govern them.

Future of value from AI is the Autonomous Enterprise

“Realizing real value from AI is not going to be easy because it demands a new approach,” Kask concluded. “Businesses large and small will need to connect AI to the data and processes that run their organizations, and make sure it has the context and governance to drive trusted results. That’s what we call the Autonomous Enterprise. This isn’t a technical change; it’s a human one. Because you can only achieve real value if agents, processes, and people work as one.”

*Australia, Brazil, Canada, China, France, Germany, Italy, India, Japan, Singapore, Thailand, United Kingdom, and United States.

Imagine a customer moving effortlessly through their journey from marketing through discovery, purchase, and fulfillment.

They see a personalized ad, explore a product through an AI assistant, respond to an offer in their inbox, and open your app expecting everything to simply work. They expect relevance, continuity, and immediacy across every interaction in their entire journey.

Instead, they hit friction:

• They’re asked to repeat information they already shared.
• Promotions don’t reflect inventory availability.
• Fulfillment updates arrive late or not at all.
• And when support is needed, no one has the complete picture.

These are not isolated breakdowns. They are systemic customer experience failures.

In the era of agentic AI, those moments compound quickly. Customers now assume brands understand who they are, what they need, and what is happening in real time, and they expect businesses to act on that intelligence instantly across the entire customer journey.

The agentic era is accelerating this shift dramatically.

This goes beyond surfacing insights or recommendations. Agentic AI systems are increasingly capable of planning, reasoning, decision-making, and coordinated action across networks of agents. AI is fundamentally reshaping how customer experiences are created, delivered, and optimized in real time.

But it also exposes a fundamental truth: when AI moves faster than your data, systems, and processes, it reveals everything that’s broken.

That tension—between rising customer expectations and disconnected CX reality—is exactly what SAP and Google Cloud are solving together with SAP Customer Experience.

The customer experience reality: ambition outpacing execution

Most organizations want to deliver seamless, connected experiences, but they struggle to operationalize those moments.

According to SAP research, 78% of businesses say AI will be essential for retaining customers in 2026. Yet fewer than two in five share their customer data across CX (37%) or CRM (39%) platforms.

This is an enterprise operations problem, and its impact is felt across the entire CX business. And when these touchpoints are disconnected, the customer feels it first. And by the time the company feels that friction, it may be too late to win that customer back.

A new model for customer experience built on trusted enterprise data

SAP Customer Experience plays a key role in the expansion of SAP and Google Cloud’s partnership to enable a fundamentally new approach to CX—one that connects data, AI, engagement, and commerce in real time.

“Agentic customer experience starts deeper in the stack than the customer ever sees—in the quality of the data, the way processes run, and the strength of the platform underneath. With SAP and Google Cloud, we’re building that foundation together, so AI moves beyond insight to action. This delivers continuous, intelligent experiences with the control, context, and execution required at enterprise scale.”

Muhammad Alam, Member of the Executive Board of SAP SE, SAP Product & Engineering

SAP Commerce Cloud endorses Universal Commerce Protocol: powering the next era of agentic commerce

As digital commerce enters the age of AI-driven experiences, a new standard is emerging to reshape how consumers discover and purchase products.

The Universal Commerce Protocol is an open standard designed to enable AI agents to manage the entire shopping journey, from product discovery to checkout and even post-purchase support.

Unlike traditional commerce integrations that rely on fragmented APIs and bespoke connections, UCP creates a shared language for retailers, payment providers, and AI systems. This allows intelligent agents to interact directly with commerce platforms, dramatically simplifying how products are surfaced, evaluated, and purchased.

In essence, UCP transforms commerce from a series of disconnected steps into a unified, agent-driven experience.

SAP Commerce Cloud, long known for powering enterprise-grade digital commerce for global brands, is now aligning with this new paradigm. As part of the growing UCP ecosystem, SAP plans to work with Google to enable its customers to participate in AI-native commerce experiences that extend beyond traditional storefronts and help its merchants’ products be discovered and purchased across the Gemini app and Google Search, including AI Mode.

“Our goal with UCP is to build an open, trusted standard for the future of AI-driven commerce,” said Ashish Gupta, VP/GM, merchant shopping at Google. “Having a leader like SAP endorse the protocol is critical as we work toward bringing seamless, secure agentic commerce to everyone.”

For merchants, this means dramatically lower integration costs, faster onboarding into new AI-driven channels, and the ability to reach new customers beyond their storefront experiences.

In addition, SAP Commerce Cloud will leverage Google Gemini capabilities to power a Shopping Assistant that brands can deploy directly to their own customers. This enables organizations to offer a real-time, AI-driven shopping experience across their digital touchpoints. The Shopping Assistant engages shoppers through chat, voice, and text to help them discover products, answer questions, and turn intent into transactions.

Unlike traditional storefront interactions, the Shopping Assistant can create a persistent, conversational experience that follows the customer across the shopping journey, continuously refining recommendations and guiding decisions in real time.

It can also curate creative ideas—such as themed outfits or complete event concepts—by intelligently combining products based on customer requests. By unifying behavioral signals, real-time inventory, and promotional intelligence, it can increase conversion rates, improve average order value, and ensure every recommendation is both relevant and fulfillable.

SAP Engagement Cloud and Google Cloud: how agents work together for marketing

This new expanded partnership comes alongside another historic milestone for SAP and Google Cloud, announced earlier this year. A fundamentally different approach to marketing execution is now offering marketers a new model for engagement that is built on trusted enterprise data.

By combining customer data and real-time signals like inventory, orders, and fulfillment status with operational truth, marketing teams can now build, launch, and optimize personalized customer engagements, grounded in business context and executed at scale through an autonomous multi-agent framework.

At the heart of this partnership:

• SAP Business Data Cloud (SAP BDC) connects semantically rich data across the enterprise with AI to help enable real-time insights and drive personalized interactions grounded in business context. This includes SAP Business Data Cloud Connect for Google BigQuery with bidirectional, zero-copy data access and built-in enterprise-grade governance and security.

• Google BigQuery unlocks real-time signals across the Google ecosystem, such as geolocation, weather, ad engagement, and rich analytics, for AI-driven segmentation, personalization, activation and analytics.

• SAP Customer Experience solutions can provide the real-time behavioral context: customer profiles, transactions, orders, service interactions, and consented engagement data.

• SAP Engagement Cloud can activate enterprise data, AI insights, and predictions through intuitive tools and AI agents to help securely orchestrate real-time, personalized interactions across the entire customer life cycle.

Why this partnership matters

The collaboration between SAP and Google reflects a broader shift in how commerce and marketing teams operate.

For commerce leaders:

• From search to agents: Consumers are no longer just searching. AI agents are acting on their behalf, making decisions, and completing purchases.
• From channels to ecosystems: Commerce is moving beyond owned channels into distributed, AI-powered environments like search, assistants, and chat interfaces.
• From integration to interoperability: Open standards like UCP eliminate the need for one-off integrations, enabling scalable participation in the AI economy.

With UCP, AI agents can seamlessly access product catalogs, manage carts, process payments, and handle post-purchase workflows, all without forcing retailers to rebuild their infrastructure.

For marketing leaders:

• From prompt to performance: Agentic intelligence becomes operational where business goals, enterprise signals, and marketing processes direct AI agents, translating into real customer interactions and automated lifecycle journeys.
• From manual to generative: Advanced generative capabilities powered by Google Gemini models, such as Nano Banana 2, introduce new agentic skills that help marketing teams dynamically generate messaging, imagery, and campaign variations.
• From dark data to unified data context: With every interaction grounded in business context and continuous engagement signals, messages become truly dynamic. Text messages can turn into immersive conversations with Google Rich Communication Services (RCS) and advertising creative and offers can continuously evolve.

Agents collaborate across SAP and Google Cloud to personalize, activate, and continuously optimize campaigns in real time across engagement channels and media networks.

“With this partnership, SAP and Google Cloud bring together connected AI and a unified data foundation to create real-time understanding of the customer and business context. This enables organizations and CX teams to move from fragmented interactions to continuous, intelligent execution—embedding AI into end-to-end processes and unlocking meaningful gains in productivity, speed, and business impact.”

Jan Gilg, Global President Customer Success & Americas, Member of the Extended Board

Unlocking new value for enterprises

For SAP Commerce Cloud customers, this partnership can unlock several strategic advantages:

• Increased discoverability in AI-driven shopping experiences
• Faster time-to-market through standardized integrations
• Ownership of customer relationships, even in third-party AI environments
• Future-proof architecture aligned with emerging commerce standards

As AI continues to compress the distance between intent and transaction, accessibility to agents becomes just as important as visibility in search results. In this new model, success in commerce is no longer defined by storefront experience alone—it’s defined by how effectively your products, data, and systems can be accessed, interpreted, and transacted on by AI agents.

For SAP Engagement Cloud customers, this partnership unveils a new network of interoperable AI agents, grounded in enterprise data and shared context across SAP and Google. Organizations can achieve measurable outcomes, including:

• Faster speed-to-market through autonomous campaign and content generation
• Lower operational overhead by eliminating manual execution steps
• Always‑on optimization that continuously improves performance
• Higher ROI through relevant, timely, and consistent engagement at scale

Marketers can spend less time managing workflows and more time shaping strategy, creative direction, and customer value.

“What matters is delivering real value to our customers. As customer experience becomes more agentic, organizations need to move faster, stay connected, and operate consistently across every interaction. By bringing commerce, marketing, and service together, we help our customers reduce complexity, respond more quickly, and deliver more relevant experiences that strengthen engagement and drive sustainable growth.”

Manos Raptopoulos, Global President Customer Success Europe, APAC, Middle East & Africa and Member of the Extended Board SAP SE

The future of AI-driven commerce and marketing: what this means for your CX strategy

The partnership between SAP and Google for marketing and commerce marks a foundational shift toward what many are calling an agentic revolution—a world where AI doesn’t just assist CX teams and shoppers but actively participates in the buying process and shapes their customer experience.

For enterprise CX leaders, the message is clear: success in this new era will depend on how well your commerce and marketing platform can communicate with AI agents. With SAP and Google Cloud, SAP Customer Experience is positioning itself—and its customers—to thrive in that future.