AI operations and measurement

Human review and quality control for AI-assisted marketing

AI-assisted work needs a review process matched to the consequences of error. Assign a person who can verify the claims, understand the context and decide whether the output is fit for use.

Define what the reviewer must check

Separate factual accuracy, interpretation, voice, originality and required approvals. Check names, figures, quotations and source support against the underlying evidence. A fluent draft can still contain unsupported connections or omit a condition that changes the meaning of a claim.

Keep evidence traceable

Provide the brief, approved source material and a record of significant revisions. Label illustrative scenarios clearly. Do not create a personal expert byline, customer quote or claim of review without authorization. Where specialist claims are involved, route them to someone qualified to assess them before publication.

Review the process as well as the draft

Track repeated error types and the work required to repair them. Improve instructions or remove the task from the workflow when review effort outweighs the benefit. Define who approves public release and how errors will be corrected later. Human review should be an accountable decision, not a checkbox added after generation.

Put the decision into practice

  1. Check factual claims against evidence.
  2. Review omitted conditions.
  3. Verify voice and authorization.
  4. Assign release approval.
  5. Record recurring errors and corrective actions.

Bring the business question, the evidence already available and the constraints that matter. Discuss your next step with Nancy Chou.

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