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Where AI still needs human review

Workflow Signal Editorial Team · September 2026

AI can classify, summarize and draft. Whether it may act without review depends on the consequence of being wrong, the quality of the evidence, and how easily a decision can be undone.

Use a simple risk screen

Keep a human reviewer when the output can change a person’s rights, money, access, reputation, safety, legal position, or essential service. Also keep review when the model is asked to infer a fact that is not available in the supplied records.

Separate recommendation from action

A low-risk workflow may prepare a draft, rank options or route a request. A human can then confirm the decision. This preserves speed without hiding accountability.

Define the stop condition

Do not tell a system to “handle everything.” State when it must stop: low confidence, conflicting evidence, absent records, unusual values, a policy exception, or a request outside its approved scope.

Good review design: show the reviewer the source facts, the proposed output, and the reason for the recommendation. A reviewer cannot meaningfully approve a black-box conclusion.

Review the workflow itself

Check exception logs and corrections regularly. A workflow can drift when its inputs, policies or connected systems change.

Before setting review points, map the workflow. For a tool-selection approach, read our evaluation guide.