Where Human Review Is Needed in AI Workflows
Design review points that give people the evidence, time and authority to catch mistakes before they matter.
Key takeaways
- Place approval before consequential actions.
- Make the source evidence available to reviewers.
- Test whether reviewers can detect and correct failures.
Start with the consequence of an error
Map where an output becomes an action: an email is sent, a record changes or a commitment reaches a customer. Decide what harm an incorrect result could cause and whether it can be reversed.
Keep higher-consequence decisions under appropriately qualified human control. Define restricted uses and escalation routes before connecting tools to live actions.
Give the reviewer a specific job
Checking that an answer sounds reasonable is too vague. Ask reviewers to verify names, amounts, policy references or other task-specific facts against an authoritative source.
Provide the original input and relevant evidence alongside the draft. A reviewer should be able to reject or change the output without pressure to accept it.
Build a workable review queue
Decide who reviews, how quickly they must respond and what happens when they are unavailable. Separate routine corrections from cases requiring specialist judgement.
For an illustrative customer response, staff could approve policy details and escalate a disputed refund. See our AI customer service workflow guide for handoffs.
Test the human control
Use examples with plausible errors, missing information and conflicting sources. Check whether reviewers notice them and whether the interface makes correction possible.
Google’s People + AI Guidebook is a human-centred design reference. Review time and repeated missed errors should inform whether the workflow is ready.
Review the review process
Monitor corrections, overrides, missed issues and backlog. If review becomes a rubber stamp, reduce the scope or redesign the task. Keep a route for pausing the system.
Connect these controls to your AI governance approach and train the team using actual work examples.
Sources and further reading
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