Human review is a defined checking step performed by someone able to judge the material and its intended use. It needs more than a person glancing at a polished answer. The reviewer needs the question, the relevant sources and a clear idea of what would count as a failure.
Match the depth of review to the consequence of an error. Check calculations against records, interpretations against source wording and proposed actions against the actual circumstances. Keep unresolved uncertainty visible when the available evidence cannot settle it.
A small-business example
An AI summary identifies customers whose orders have declined and drafts suggested follow-ups. A sales manager checks the underlying period and notices that one customer orders seasonally, another has changed account names and a third has an unresolved service complaint.
The summary helped organise a review, but the records and relationship knowledge changed the proposed actions. The manager records the reasons for those changes so the next report can account for them where appropriate.
Try this
Choose one recurring AI-assisted task. Write a short review checklist containing three checks that could change the decision. Name the reviewer and make the source records accessible from the output. Run the checklist on one plausible but deliberately incomplete example to see whether it catches the omission.
Provenance provides the trail, Define the decision clarifies the stakes and Feedback loops turns repeated corrections into improvements.