Interactive Advertising Bureau has updated its framework for disclosing artificial intelligence in advertising, giving agencies, advertisers, publishers, platforms and technology partners a more specific test for when AI involvement should be visible to consumers.
The new version matters because disclosure debates are moving beyond a simple question of whether AI was used at all. IAB’s approach focuses on whether AI materially changes what consumers think is authentic, who or what they are seeing, or whether the content represents something real.
Key Takeaways
- IAB’s Version 2 framework gives the advertising industry a more practical test for when AI involvement should be disclosed.
- The framework centers disclosure on changes to authenticity, identity and consumer perception rather than requiring labels for every use of AI.
- For agencies, the operational challenge shifts toward documenting where AI enters the creative process and who is responsible for disclosure decisions.
Table of contents
Jump to each section:
- What the updated IAB framework changes
- Why the framework focuses on material consumer impact
- What this means for agency workflows
- Why industry guidance still does not replace legal review
What the updated IAB framework changes
IAB’s AI Transparency and Disclosure Framework Version 2 gives the industry practical guidance on when and how to disclose AI involvement in consumer-facing advertising and marketing content. The guidance is meant to apply across advertisers, agencies, publishers, platforms and technology partners rather than only to the company that generated the content.
The important shift is that the framework does not treat every AI-assisted action as equally significant. Routine uses of AI in editing, optimization or workflow support do not automatically carry the same disclosure expectation as content that could change a consumer’s understanding of who created something, who appears in it, or whether an event or representation is real.
That makes the framework more useful operationally than a blanket “AI was used” rule. It gives marketing teams a decision standard they can build into creative review rather than forcing the same label onto every AI-supported asset.
Why the framework focuses on material consumer impact
The updated standard reflects a problem many agencies are already facing: AI now appears at multiple points in the production process. A campaign may use AI for ideation, image cleanup, synthetic voice, audience adaptation or full asset generation, and those uses do not create the same risk for consumers.
MarTech’s coverage of the update highlights the same boundary, describing the framework as drawing the disclosure line around changes to authenticity, identity and what consumers believe is real. That framing matters because it moves the conversation from tool usage to likely consumer interpretation.
For marketers, this creates a more defensible review question: would a reasonable consumer understand the ad differently if they knew how AI was used? That is a more practical standard than simply asking whether any AI touched the asset.
What this means for agency workflows
The biggest consequence may be procedural. Agencies that use AI across creative, production and media workflows now need a reliable way to document where AI enters the process and who makes the final disclosure call.
That could mean adding AI-use fields to creative briefs, requiring vendors to disclose synthetic elements, or making AI review part of final legal and brand approval. The framework also puts pressure on agencies to distinguish low-risk assistance from AI use that changes identity, realism or authenticity in a way consumers may care about.
This is especially relevant for teams working with synthetic people, altered voices, virtual influencers or heavily generated product imagery. In those cases, a disclosure decision cannot be left to the final publishing step because the underlying creative choices happen much earlier.
Why industry guidance still does not replace legal review
IAB’s framework is industry guidance, not a substitute for laws or platform rules. That distinction is important because advertisers operating across markets may face legal disclosure duties that are broader, narrower or structured differently from the IAB standard.
The practical value of the framework is that it gives agencies and brands a common operating language before legal requirements are applied. Teams can use it to identify higher-risk AI uses, document decisions and escalate assets that need jurisdiction-specific review.
The larger signal is that AI governance is becoming part of ordinary campaign operations rather than a separate policy exercise. For agencies, the question is increasingly not whether they use AI, but whether they can explain where it was used, why it matters to the consumer, and who accepted responsibility for the final asset.
