AI workflow failures are rarely random. Most of them repeat as missing evidence, conflicting records, permission gaps, ambiguous ownership, policy uncertainty, or downstream system constraints.

Build an exception taxonomy before expanding automation. Each class should define the trigger, owner, fallback route, user message, evidence packet, and resolution target.

The taxonomy makes automation safer because agents stop improvising when work leaves the happy path. It also gives operations teams a clean backlog for reducing exception volume over time.