When Should an AI Agent Pause for Approval?

An agent may be allowed to draft a recommendation but not to send it, change a customer record, or commit resources. The tricky part is that a chain of small actions can add up to a consequential decision—even when each step looks routine on its own.

Where should the approval boundary sit? Should it depend on the type of action, its cumulative impact, or how difficult it would be to reverse? And when an agent pauses, who owns the trade-off: the person approving the next step, or the team that set the policy?

One practical test is to map a workflow from proposal to execution, mark where consequences become hard to undo, and agree who can authorize that step. What would make that boundary clear enough to use—and easy to review when the workflow changes?