SAP has today announced the release of several new products to reposition AI as a system of execution, aiming to redefine how enterprise software will be used over the next decade.
Unveiled at SAP Sapphire 2026, the launches intend to replace fragmented copilots with governed, autonomous systems that run real business processes, including customer experience.
For CX leaders, the move signals a shift away from channel‑specific automation toward AI‑driven orchestration across marketing, commerce, sales, and service.
Jessica Keehn, CMO at SAP, told CX Today that SAP is deliberately shielding end users from AI complexity by managing agent coordination behind a unified data foundation.
“The goal for brands should not be to introduce more agents, but to connect the right agents around a shared source of truth so teams can act faster and with less friction,” she explained.
“That complexity should take place behind the scenes, so the user experience feels simple.
“They should be able to state the outcome they want and have the right assistant coordinate the work.”
From Assistance to Execution
SAP’s intentional shift from fragmented, role‑specific AI copilots toward orchestrated, outcome‑driven AI systems that operate across the entire customer lifecycle, will enable enterprises to execute customer journeys end‑to‑end.
Until recently, many CX platforms have introduced AI in pieces, offering individual assistance for each department, but these approaches eventually increase complexity.
These tools often operate on different data sets, optimize for narrow tasks, and require users to manage the handoffs themselves, resulting in more interfaces, more decisions, and more friction for CX teams.
“That complexity should take place behind the scenes, so the user experience feels simple,” Keehn continued.
“A marketer should not have to know which agent can identify a key audience, check inventory, generate content, adapt a campaign, or trigger the next best action. A service team should not have to hunt across systems to understand an order, entitlement, or billing issue.
“They should be able to state the outcome they want and have the right assistant coordinate the work.
Rather than optimizing individual touchpoints in isolation, teams now require consistent, real-time experiences that connect the customer journey, grounding AI in a unified data foundation and hiding coordination logic from the user, allowing CX teams to focus on outcomes.
This allows CX teams to fit the shifting customer expectations beyond traditional omnichannel engagement, which Keehn argues is no longer important on its own.
“Traditional omnichannel experience required being present and consistent across channels: web, mobile, stores, call centers, email, and social. That still matters, but it is no longer enough,” she explained.
“Constant experience requires continuity across touchpoints, context, and operations. Every interaction must reflect the same view of who the customer is, what they need, what they have already done, and what the business can deliver in that moment.”
SAP's product releases are designed to move AI from isolated assistance toward coordinated execution across the customer lifecycle, introducing a layered architecture that combines data, orchestration, and user experience.
SAP Business AI Platform
As the foundational layer for enterprise AI, the platform aims to address the lack of business context, where 95% of enterprise AI projects fail because AI systems are disconnected from real business processes, data, and rules.
This approach combines SAP Business Technology Platform, SAP Business Data Cloud, and SAP’s Business AI capabilities into a single, governed environment to ensure AI models are trained, deployed, and executed within the same operational context as the business itself.
By enabling AI to work inside the company’s operational system, this will allow the tools to see live business data and understand business rules so actions can be audited and decisions can be governed.
This platform includes SAP Knowledge Graph, a tool that provides AI agents with a clear understanding of processes and relationships across an enterprise’s landscape.
From here, AI agents are able to reason using a shared map, detailing how the organization runs for a safer, more reliable autonomy.
Furthermore, the business AI platform also includes Joule Studio for developers, designed to build, deploy, and manage AI agents to improve access to enterprise-grade AI development while maintaining governance.
