Set approvals by the risk of the finished marketing asset, not by whether AI touched it. Give a named content owner accountability for every asset, add specialist review for claims or content that could mislead, and record the exact version and evidence approved. This practical framework is an internal control—not a universal approval matrix prescribed by regulators.
What should an AI marketing approval policy cover?
Define the policy around the material your audience may see, rather than limiting it to text generated from a prompt. It can cover drafted or AI-transformed copy, images, audio, video, synthetic voices or likenesses, testimonials, chat assistants, and other consumer-facing interactions. Decide separately whether internal-only drafts, research, or planning materials need the same checks as published campaigns.
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The IAB Framework V2 addresses multiple media forms and consumer-facing interactions, but it is industry guidance, not a general legal rule. Your policy should also identify which markets, channels, business units, and product categories it covers. Laws and platform requirements can differ by location, format, audience, and the role your organization plays.
How should you tier approvals by risk?
A tiered process lets a team review routine material efficiently while reserving specialist attention for claims and representations with greater potential to mislead or cause harm. The categories below are a suggested implementation; the FTC and NIST do not mandate this particular tier system.
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| Tier | Examples | Minimum reviewer | Decision |
|---|---|---|---|
| Routine | Formatting, spelling, low-stakes ideation, or ordinary copy without a material factual claim | Trained content owner | Check brand fit, obvious errors, and that the approved asset is the version being published. |
| Claims-bearing | Product benefits, performance, comparisons, price or availability, environmental statements, or measurable outcomes | Content owner plus the owner of the claim or supporting evidence | Approve only wording and qualifications supported by the evidence. |
| Elevated risk | Health or financial claims; endorsements, testimonials, or reviews; content aimed at children; audience-sensitive material; or synthetic depictions or voices that could mislead about a person | Content owner plus relevant subject-matter, legal, privacy, or compliance reviewer | Hold publication until the relevant specialists resolve the issue and any disclosure decision is recorded. |
The FTC identifies advertising claims, endorsements, reviews, children’s marketing, and health claims as areas requiring attention; specialized categories can carry additional rules. The right specialist depends on the subject and target market, so name the role in the policy rather than routing everything to an undefined “legal” queue.
Who should approve AI-generated ad copy?
Assign one accountable content owner to each campaign or asset. That person coordinates review, confirms the publishing version matches the approved version, and does not treat specialist sign-off as a transfer of overall responsibility. Add reviewers according to the risk tier:
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- Content or campaign owner: checks purpose, audience, channel, brand requirements, completeness, and version control.
- Claim or product owner: verifies factual claims against the evidence and confirms that wording does not exceed what it supports.
- Subject-matter reviewer: checks specialized claims, such as health or financial statements, when relevant.
- Legal, compliance, or privacy reviewer: assesses applicable legal, disclosure, audience, or data concerns when the asset warrants escalation.
- Publishing owner: confirms the released copy, media, placement, and disclosures match the approved record.
Define what each approval means. A brand approval is not evidence that a product claim is substantiated; a claim review does not automatically decide whether an AI-related disclosure is required. NIST’s AI Risk Management Framework is voluntary guidance for incorporating trustworthiness considerations into AI design, development, use, and evaluation. It does not provide a ready-made marketing sign-off chart.
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Check claims against evidence
The FTC’s Advertising and Marketing guidance states: “Under the law, claims in advertisements must be truthful, cannot be deceptive or unfair, and must be evidence-based.” Apply that check to the finished asset, including its images, comparisons, qualifiers, and context—not just to the prompt or an earlier draft.
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- Is each objective claim true and supported by appropriate evidence?
- Does the final wording stay within what the evidence establishes, including any necessary qualifications?
- Could a claim about health, the environment, origin, performance, or a specialized product category face additional requirements?
- Could an image, voice, quote, testimonial, or chatbot exchange create a misleading impression about who said or did something, or whether an endorsement is genuine?
- Does the actual publishing version still match the wording and evidence that were reviewed?
Apply extra scrutiny to endorsements and reviews
Do not use generated testimonials, endorsements, or consumer reviews to create a false impression of genuine consumer experience. The FTC’s endorsement guidance covers endorsement relationships, influencer marketing, and native advertising; its Consumer Reviews and Testimonials Rule is also relevant. Where a material connection requires disclosure, make it clear and conspicuous in context. FTC guidance says an affiliate disclosure should be close to the recommendation and link; hiding it in comments is avoidable and not clear and conspicuous.
Make the approval decision traceable
Record the campaign or asset ID, intended channel and market, final copy or media version, relevant AI tool or use if your policy tracks it, claims and supporting evidence, disclosure decision and rationale, reviewer names and roles, decision date, and any approval conditions. Keep the record with the version that was approved so a later reviewer can tell what decision applied to what material. This is a recommended internal control; the cited sources do not prescribe this exact record schema.
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When should an AI-generated ad disclose AI use?
Do not assume that internal AI assistance automatically requires a consumer-facing label on every asset. Decide by the target jurisdiction and channel, the media type, applicable law or platform terms, and whether the finished content could materially mislead people about its origin, a person, or an interaction. Distinguish an internal drafting aid from an output or experience that an audience could mistake for something real.
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The IAB’s August 18, 2026 announcement of Framework V2 describes a risk-based, materiality-driven approach. Its examples for disclosure consideration include generated images and videos, some synthetic voices and avatars, certain digital twins, and chatbots that might be mistaken for humans. It says routine production uses and text or copy do not automatically require labels under the IAB framework. The framework is an industry resource, not a replacement for applicable regulation or platform rules.
The same IAB announcement reports January 2026 research with Sonata Insights: more than half of respondents wanted brands to disclose when an ad was fully AI-generated or used AI imagery or video, and 73% of Gen Z and Millennial respondents said clear disclosure would increase or have no impact on their likelihood to purchase a product. The announcement excerpt does not provide the sample size or full methodology, so these figures should not be treated as representative of every consumer or as creating a legal duty.
For EU-facing work, the consolidated text of AI Act Article 50 distinguishes provider marking of covered synthetic outputs from deployer disclosure for deepfakes and certain public-interest text. It includes conditions and exceptions; for public-interest text, the cited text includes an exception where human review or editorial control occurs and a natural or legal person holds editorial responsibility. The Act applies from August 2, 2026, according to that consolidated text. Assess whether the specific asset and activity fall within the provision’s scope rather than treating it as a blanket label requirement for all AI-assisted marketing.
How do you put the rules into operation?
- Register the asset. Give each asset or campaign a stable ID and note its owner, audience, channel, market, format, and whether it is internal or consumer-facing.
- Assign a tier before publication. Use the highest relevant risk in the asset. A routine headline paired with a synthetic endorsement or a health claim needs the stronger review path.
- Collect claim evidence. Have the claim owner provide substantiation and identify wording or qualifications the evidence permits. If evidence does not support the proposed claim, revise or remove it rather than relying on an AI tool’s output.
- Route the right reviews. Obtain content-owner approval for all tiers, claim-owner approval for claims-bearing assets, and the relevant specialist approvals for elevated-risk work.
- Decide disclosure separately. Record the applicable market and channel, the rule considered, whether disclosure is required, and the reason for that decision.
- Lock the approved version. Store the final copy or media and its evidence, reviewer decisions, date, conditions, and revision history together. A material edit after approval returns the asset to the appropriate review step.
- Reopen approval when circumstances change. Reassess if claims, offers, media, target market, placement, or applicable legal or platform requirements change.
A workflow tool can help route these reviews and preserve decisions, but the policy should define owners, evidence standards, and escalation conditions independently of any particular vendor or software.
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