Direct answer
The short version.
AI-generated advertising should pass a documented review covering source accuracy, claim substantiation, brand identity, rights, representation, accessibility, platform policy and landing-page continuity before publication.
Key takeaways
Keep these three decisions.
- Use named review gates.
- Check product details and qualifiers against sources.
- Log defects so prompts and inputs improve.
The operating problem
Generated output can look complete before it is trustworthy. Small errors in packaging, product behaviour, people, locations or qualifiers are easy to miss at production speed. Review becomes inconsistent when responsibility is distributed across comments rather than assigned to named gates.
A practical system
Separate review into four passes: factual and legal source checking; creative and brand judgement; technical production QA; and media-destination readiness. Record the reviewer, version and decision at each gate. High-risk claims or sensitive depictions should be escalated rather than solved through another prompt.
What to measure next
Track defects by category and where they were caught. The goal is to move detection earlier, reduce repeated failure modes and maintain a recoverable audit trail. A falling approval time is only healthy when post-publication corrections and rejected ads also decline.
Primary and authoritative references
Sources used for context.
Frequently asked questions
Two useful follow-ups.
Who should approve AI-generated advertising?
The accountable mix depends on risk, but creative, brand, factual and media owners should be explicit rather than assumed.
Can an AI model review its own output?
Automated checks can flag issues, but they should support rather than replace accountable human approval.