When does an AI agent become trusted workflow infrastructure?

The painful threshold is when ownership, approval, audit, handoff, exception handling, and rollback matter more than one impressive completion.

When does an AI agent become trusted workflow infrastructure?

The question

I am looking for the moment where ownership, approval, audit, handoff, exception handling, and rollback matter more than raw model ability.

The useful threshold is not whether the agent can complete a task once. It is whether the workflow keeps authority, review state, and reversal visible when the task becomes part of a real organization.

Why it matters

A demo can hide the hard parts by keeping the user, data, and failure surface narrow. Workflow infrastructure has to survive handoff, exception handling, review pressure, and the moment a quiet write could become expensive.

What would change it

The strongest evidence would be an operator using the system on a real workflow and naming which audit event, approval step, rollback path, or permission boundary made the difference between useful automation and a risky assistant.