Designing the review loop around AI output.

Putting AI output into daily work requires a reliable review process. Define who checks what, and what must be true before the work moves forward.

Separate the reasons for review

Factual accuracy, internal policy and clarity for the reader each require different knowledge. Separating these checks makes ownership clear and reveals where AI can assist.

Give uncertain work somewhere to go

Instead of forcing an uncertain result into a completed state, return it to a person with the missing context made clear. Visible exceptions make everyday operation more dependable.