Make room for human judgment.

An AI-generated answer can be fluent, organised, and easy to read. The person using it still needs to decide whether it is useful, accurate enough for the task, and appropriate to share.

Good review begins before the answer appears. It starts with knowing what the work is for and who is responsible for the result.

Define what needs checking.

Different tasks need different reviews. A brainstorming exercise might need a discussion about relevance. A factual summary needs comparison with its source. A message to a customer needs attention to accuracy, tone, and promises.

Write those expectations down in a way the team can use. “Check the output” is much less helpful than “compare every date and commitment with the approved source.”

Keep the context close.

When a result moves from one person to another, pass along the information needed to review it. That might include the original brief, an approved reference, or an explanation of what has already been checked.

Make the remaining uncertainty visible. A polished document should not obscure an unresolved question.

Give someone the decision.

Agree who can approve the work and what should happen when they are unsure. For sensitive or consequential decisions, involve the people with the right responsibility and expertise.

AI can contribute to a workflow. The team still needs a clear understanding of who owns the work.