SAP’s latest thinking on agentic AI centres on a straightforward question: can enterprises trust autonomous agents to act on their behalf within complex data environments? The answer requires more than better software. It requires people who understand where human oversight ends and machine autonomy begins.
A client in Zurich recently asked us for an SAP architect who could also draft governance frameworks for autonomous processes. The role specification mentioned data lineage, audit trails, and something they called trust architecture. That last term came directly from internal discussions about where AI agents should be permitted to make decisions without human review.
The skill combination sits at the intersection of three disciplines: SAP functional knowledge, data governance, and AI risk management. Most candidates have depth in one, maybe two. The third is usually missing. Companies building agentic capabilities will need to decide whether to train existing SAP specialists in AI governance or recruit externally from data ethics and compliance backgrounds.
Candidates with SAP experience who add fluency in data trust concepts, explainability requirements, and audit frameworks become substantially more attractive to these companies. These are learnable skills. We filled one such role in Frankfurt last quarter only after expanding the search to include compliance professionals willing to learn SAP integration. The original specification had sat open for four months with no viable shortlist.
Autonomous agents acting on enterprise data will need human-designed boundaries and human oversight of those boundaries. The companies investing in agentic AI are starting to realise they need to invest in the people who will govern it. That hiring has already begun in Zurich and Frankfurt.
Prompted by reporting from SAP News Centre.