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Key Takeaways
What you need to know
Define the execution gap Identify where AI today stops at recommendations (dashboards, copilots) instead of executing SAP transactions or workflow steps. Prioritize processes where closed-loop execution (e.g., auto-posting, exception handling, approvals) would generate measurable business value.
Pick pragmatic, high-value use cases Cluster near-term use cases around document automation, SAP data Q&A, code/spec generation, exception triage agents, and predictive scenarios (maintenance, demand, etc.). Tie each use case to a specific KPI (cycle time, error rate, FTE hours, cash, compliance) and make that the primary success metric for the pilot.
Treat copilots and chatbots as entry points, but design the target state as AI agents that can orchestrate and execute multi-step workflows inside SAP with human-in-the-loop guardrails. Decide upfront which steps an agent can execute autonomously and which require approvals, dual control, or audit logs.
Separate AI reality from vendor promises. Explore the 10 questions SAP leaders are asking about Joule, ECC, S/4HANA, AI agents, governance, and practical implementation strategies.
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