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AI ads: labelling, approval and rejection (2026)

Distinguish AI labelling from rejection, record the submitted version and investigate the actual reason for a decision.

Kevin Dosanjh
Kevin Dosanjh
Co-founder / CMO, AI Vidia · Updated
A phone and printed vertical ad frames on a review desk, one frame carrying a small blurred disclosure chip in the corner
On this page7 sections
  1. 01A label provides information about content
  2. 02Check the actual ad and placement
  3. 03A hypothetical product presentation
  4. 04Make handoff clear
  5. 05When an ad is rejected
  6. 06Separate corrections from new campaign ideas
  7. 07Set realistic expectations for production review

Labelling and rejection are different questions. Assess an AI ad through its content, presentation and the current requirements for its intended placement.

A label provides information about content

Meta's June 2026 update describes extending AI transparency to ads created or edited with third-party tools. It is therefore incorrect to assume only content from Meta's own tools can receive AI information.

This does not mean all AI ads are automatically rejected. Separate how origin is disclosed from whether the particular ad meets relevant requirements. A label does not fix inaccurate products or unsupported claims.

A phone displaying a blurred product video with a small marker beside ad cards.
A phone displaying a blurred product video with a small marker beside ad cards.

Check the actual ad and placement

Record where the ad will run and what was generated or changed: background, setting, person, voice or larger parts of the video. This helps the uploader consult relevant guidance and choose appropriate settings.

A review for one market or platform does not automatically cover every other one. Assess specific uncertainties against the actual ad and relevant platform and market conditions.

A hypothetical product presentation

Imagine a synthetic person holding a drinking bottle and explaining its documented size. First check the bottle and whether the person appears as a presenter rather than a real customer with invented experience.

A hand sorting ad cards into two piles beside a magnifier and clipboard.
A hand sorting ad cards into two piles beside a magnifier and clipboard.

Then check audio, captions, disclosure requirements and destination. If a later rejection concerns a claim in the copy, removing AI information does not solve it. Investigate the stated reason and correct the problem. This example illustrates a workflow, not advance approval for a particular ad.

If the correction changes a product claim, the product owner needs to approve the new version. A technical fix and a changed message are separate matters even within the same file.

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Make handoff clear

  • Approved filename and version.
  • Description of generated and edited elements.
  • Approved product claims and supporting evidence.
  • Agreed channels, markets and destinations.
  • Open questions to resolve before publication.

Keep this information beside the final file. A filename rarely explains every relevant condition. The campaign owner should be able to retrieve it without reconstructing production history.

When an ad is rejected

Save the message and time, then locate the exact submitted version. Read the reason before editing. Inspect copy and destination when they form part of the issue. Rejection does not automatically establish AI production as the cause.

Correct the identified error or use the platform's relevant clarification process if you believe the decision is wrong. Do not create numerous arbitrary minor variants to bypass review. The goal is an accurate, acceptable ad the team can explain.

Separate corrections from new campaign ideas

A rejection may prompt several people to suggest changes. Keep the necessary correction distinct from ideas unrelated to the reason, or it becomes unclear which change was submitted for review.

Retain the submitted file and a short change list for the replacement. Product claims or destination changes need the appropriate reviewers again. Even a purely technical correction requires a final export check.

Connect the platform's actual response and date to the submitted version. A new upload is approved only when the status confirms it.

Set realistic expectations for production review

A producer can check the product, file and agreed requirements before delivery. That is different from guaranteeing every future platform decision or a particular rejection rate.

Use the quality review workflow before handoff and have the campaign owner check current requirements at upload. This keeps the production decision and publication status separately documented.

Frequently asked questions

01Are all AI ads rejected?
There is no basis for that conclusion. Assess the particular ad and the reason for any rejection.
02Is adding an AI label enough?
No. Product, claims, file and destination must also be correct and meet relevant requirements.
03Can a producer promise zero rejections?
No. A producer can review material before delivery, but the platform makes the actual decision.

Sources

  1. 01Meta: GenAI transparency, June 2026 update

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