A proof of concept can demonstrate that a model produces useful output and still leave the production decision unresolved. Security, compliance, finance, and operations need to know who may initiate the work, which sources are in bounds, what the AI may change, where a human must decide, and what record remains.
The failure is not always a missing policy. It is often a missing test. The vendor has shown the happy path but the committee has not defined a rejection rule, challenged an unauthorized request, or retrieved the evidence for the demonstrated action.
A stronger proof begins with one representative job. Write the authority map before the demo: human owner, AI Worker, permitted source, action class, approval point, model route where relevant, and required record. Run the job, vary the user or source, and inspect whether the configured boundary holds.
Framework mappings can organize the review, but they are not evidence that a control operated and they are not organizational certification. The useful evidence is deployment-specific, time-bounded, and linked to the workflow the committee actually observed.
This does not make the production decision automatic. It makes the disagreement visible. The committee can identify whether the remaining issue is product fit, integration work, policy ownership, evidence quality, or commercial scope, then decide on that basis rather than on a generic governance promise.