Enterprise AI from PoC to production. SAP Business Data Cloud, data products, agentic AI. Most of it fails a layer above the tech.
Köln
Joined November 2010
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Hardening your model does not answer the question that decides your agent risk.
Model hardening asks whether the agent can be tricked into doing something it should not. Useful, real, and the smaller of two exposures.
1/11
Where that is unresolved, the organisation escalates instead of acting, and escalation during an incident consumes exactly the hours that determine its size.
A decision matrix with named roles costs nothing.
It fits in one workshop.
10/11
If you run agents in production today: can you name, per agent, the process steps it may trigger without asking? That question has an owner and a threshold, or it has no answer.
#AgenticAI #EnterpriseAI #CISO #AIGovernance
11/11
A framework agreement sets prices. It almost never sets accountability.
That gap is invisible while everything works and decisive the moment it does not.
1/9
The exercise that changes it, and it fits on one page: for each critical process, write down which supplier owns the result, which metric shows it is going wrong, and who decides in a conflict.
8/9
If that page cannot be filled in, the gap is real and it is not a procurement problem.
Anyone on the buying side: does your framework name an outcome owner per process, or only rates per profile?
#Sourcing #Procurement #ServiceDelivery #COO #VendorManagement
9/9