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AI & automation

Make review a real workflow.

What makes a human review queue useful in an AI workflow?

Reviewer comparing source and draft on two clean monitors

The decision

A human review queue should show what requires a decision and why. Simply placing a person somewhere in the process does not establish effective oversight. Give reviewers the source, proposed result, uncertainty, and the actions they can take.

In practice

A document workflow may require correcting one field rather than approving the entire output again. Make that distinction clear. Let the reviewer reject, request clarification, or escalate instead of forcing every exception into an approve button.

Put it into practiceYour next checks
  1. Define review criteria, ownership, priority, and handling of overdue items.
  2. Test difficult examples and record corrections.
  3. Confirm that rejected outputs cannot continue into downstream actions and that changes remain traceable.

When to take the next step

Design review before connecting generated output to a downstream action. Give reviewers difficult examples and check whether they can reject or escalate without improvising a workaround.

Questions clients ask

Should every output be reviewed?

Choose review coverage around consequence and uncertainty, with explicit criteria for any automated path.

What makes review measurable?

Decision time, correction patterns, unresolved exceptions, and whether rejected work is prevented from proceeding.

Plan your next step.

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