Why does AI trust break as a system property?

Model quality matters, but permissions, source state, review state, audit, handoff, and rollback often decide whether the system can actually be used.

Why does AI trust break as a system property?

The boundary

This is why I distrust category claims that only compare model output. The system either keeps evidence and ownership visible across the decision path, or it forces people to trust a result they cannot inspect.

The evidence gap

The useful proof is a workflow that makes the right thing harder to skip: source capture, owner assignment, review state, audit event, and a rollback story that survives outside the demo.

What would change it

A useful next signal would be a prototype that preserves evidence and ownership across the full decision path.