In-Short
AI Should Not Finish Every Task
Once AI can read connected data, draft customer messages, change files, or prepare decisions, guessing is no longer harmless. The workflow needs an alternative to pushing forward when the input is weak or the consequence is high.
Escalation Is Earlier Than Review
Review checks an output before use. Escalation happens when the workflow reaches missing information, conflicting evidence, unclear ownership, or an action outside its authority. It prevents the wrong output from being treated as finished.
Four Outcomes Are Enough
Continue when the work is low risk and the required input exists. Ask when one missing detail could change the answer. Hand off when a person owns the judgement. Stop when the task crosses an agreed boundary.
Write Rules A Team Can Inspect
"Be careful" is not an operating rule. A useful rule names the trigger, the required response, and the next owner. That makes AI behavior easier to test and improve.
Acting Changes The Risk
Long Read
In a normal chat, a wrong answer is inconvenient. You ignore it, correct it, or ask again.
In a workflow, a plausible answer can become an action.
It can send the wrong promise, update the wrong record, publish an unsupported claim, or hide uncertainty inside a clean report.
The practical question is not only:
Can AI do this task?
It is:
What should AI do when this task is no longer safe or clear enough to finish?
That is the job of an escalation rule.
