When Should an AI Agent Escalate to a Human?

An agent should escalate to a human when an action is consequential, falls outside the policy it was given, or is genuinely uncertain — and escalation should be a designed, first-class outcome, not an error. Good escalation gives the human enough context to decide quickly and records the decision, so the boundary between what the agent handles and what a person approves is explicit and auditable rather than improvised.

Escalate when

Consequential, out-of-policy, or uncertain

Escalation is

A designed outcome, not a failure

Gives human

Context to decide, and records it

Boundary

Explicit and auditable

Escalation as a feature

A system that treats asking a human as a failure will train itself to stop asking. Treating escalation as a normal, well-instrumented path — with the context a person needs and a recorded decision — is what lets an organisation grant autonomy safely, because the cases that should reach a person reliably do.

Questions

Doesn’t escalation slow the agent down?

Only on the actions that warrant it. In-policy, low-risk actions proceed autonomously; escalation is reserved for the consequential and the uncertain.

What should an escalation include?

Enough context for a human to decide quickly — the proposed action, why it escalated, and the options — plus a record of the decision made.