SAP has a big vision for AI agents. It wants them to run business processes, connect data across enterprise systems, and eventually be priced on the outcomes they deliver.
While this might sound great on paper, CX leaders would be forgiven for wondering where the customer service wins are.
There’s plenty of sizzle, but is there enough steak?
During SAP’s Q2 2026 earnings call, the vendor talked at length about its Autonomous Enterprise strategy, new AI capabilities, and the potential of Joule Work.
Yet when it came to live customer-facing deployments, contact center transformations, or service outcomes, the evidence was thin.
During the call, Christian Klein, CEO and Member of SAP’s Executive Board, made the company’s ambition clear:
“In the age of agentic AI, SAP is leading the way.”
That is a bold claim. But much of the AI story shared during the call remains tied to Q3 launches, beta programs, and longer-term promises.
Joule Work Is Coming, Not Here Yet
The centerpiece of SAP’s next phase is Joule Work, a new AI workspace intended to provide employees with a single interface for collaborating with AI agents across SAP’s portfolio.
Klein explained that during Q3, SAP “will also launch our new end-to-end user experience, Joule Work.
“It’s a single entry point and interface across all our portfolio solutions for all tasks where users can collaborate with our AI agents.”
SAP suggested that a salesperson could use the platform to create a “complete data rich customer pitch in just a few minutes.” This has clear CX connotations, especially for sales teams that need a fuller view of the customer.
However, it is not a contact center deployment. Nor is it evidence that SAP is already improving customer service metrics, such as first-contact resolution, customer satisfaction, or average handling time.
The same applies to SAP’s AI Agent Hub, which Klein described as “our command center to discover, manage and govern SAP and non-SAP agents, MCP servers and more.”
Again, the concept sounds impressive. Enterprises will need a governance layer if they are to deploy multiple AI agents across sales, service, finance, and other functions without creating a security, compliance, or data-management headache.
Still, SAP did not provide evidence of broad customer rollout during Q2. Instead, it pointed to future availability and early interest, saying that “the beta programs for our new platform, Suite and Joule Work were immediately oversubscribed.”
Oversubscribed beta programs are encouraging, but they are not the same as proven production outcomes.
SAP Has AI Results, But They Are Mostly Operational
To be fair, SAP was not all talk.
The vendor shared examples of AI delivering tangible results for customers. But these examples sat largely in finance, procurement, data, and ERP modernization rather than customer service.
SAP and Amadeus developed an AI agent that reconciles unstructured payment data, which Klein said was “already clearing around 40,000 incorrect transactions.”
Meanwhile, Danish wholesaler Lemvigh-Müller deployed custom AI agents to verify purchase orders. According to Klein, the solution achieved “over 90% touchless processing and 98% matching accuracy.”
PwC also selected SAP AI to transform a complex billing process, cutting “a 35-minute task to just 5 minutes while improving accuracy and end user satisfaction.”
These are credible examples of operational automation. They demonstrate that SAP’s AI strategy is not entirely theoretical.
Yet they also underline the gap in its Q2 narrative. SAP is showing that its AI can make internal processes faster and more accurate. It has not yet offered the same depth of evidence around customer-facing workflows.
For CX leaders, an autonomous enterprise is only as interesting as its impact on customers and the employees serving them.
ERP Modernization Is Becoming Part of the AI Pitch
SAP’s answer is that AI agents need better data and simpler processes before they can work reliably at scale.
Klein said that “for AI agents to deliver the accurate outcomes at scale that all of these companies need a harmonized data foundation and simplified process layer is essential.”
That may be true. Enterprises with fragmented customer data, heavily customized ERP environments, and disconnected service systems will struggle to deploy trusted AI agents.
SAP is using that argument to bind AI adoption more closely to RISE with SAP and ERP modernization. The company claimed customers using its AI ERP migration toolchain are achieving “faster time to value and up to 30% lower ERP migration costs.”
However, these remain SAP claims. They should not be mistaken for independently verified outcomes.
The vendor is also beginning to sketch out how it may monetize agents. Klein said: “We are pricing our agent based on value.”
That could eventually reshape how organizations buy automation for finance, sales, and service. But it is still an intent, not an established pricing model with disclosed customer results.
An Ambitious Roadmap, With CX Proof Still to Come
SAP’s Q2 call showed a company moving aggressively to position itself at the center of enterprise AI.
It has strong cloud momentum, a growing AI pipeline, and several operational use cases that deserve recognition.
But for now, SAP’s strongest evidence remains behind the scenes.
Its customer-facing AI narrative is more roadmap than reality. Joule Work, governed agent orchestration, and outcome-based AI pricing may yet become important components of the CX technology stack.
For the moment, though, SAP has offered more detail on what those tools will do than on the customer service outcomes they have already delivered.
