Why Your AI Is Only as Good as Your SAP Data — And What to Do About It

In virtually every large enterprise, SAP is the system of record for the operational data flowing into every major downstream platform. This means the quality of every enterprise AI decision traces back, directly or indirectly, to whether SAP data is managed and governed correctly. A demand forecast model that produces unreliable outputs is not failing because the algorithm is wrong — it is failing because the material master records it was trained on are incomplete, duplicated, or inconsistently maintained. That failure is invisible until it produces a bad business decision, at which point it appears to be an AI failure. It is, in practice, a data management failure that originated in SAP.

In this webinar, we’ll show how Precisely Automate addresses data quality at the point of creation — automating, orchestrating, and governing SAP ERP processes so that the data flowing downstream into analytics and AI is accurate from the start. You’ll see a live demonstration of how automation eliminates the manual handoffs and inconsistent entries that silently corrupt your data foundation.

You’ll leave with a clear framework for identifying where SAP process gaps are creating downstream AI risk, and a concrete picture of how automation addresses those gaps — with less time, cost, and operational burden than traditional data remediation initiatives.