The IAB is entering into the AI accountability conversation with a brand new framework aimed squarely at one among marketers’ biggest open questions: when, exactly, should AI use be disclosed in promoting?
On Thursday, the trade group rolled out its first AI Transparency and Disclosure Framework, positioning it as a practical guide for brands, agencies, publishers and platforms navigating generative AI at scale.
Rather than imposing blanket disclosure rules, the framework adopts a risk-based approach that focuses on consumer impact — disclosing AI use only when it materially affects authenticity, identity or representation in ways that might mislead people.
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“We are actually at a critical inflection point with generative AI,” David Cohen, CEO of IAB, said in a press release. “While AI is transforming how we work from ideation to execution and measurement, we must get transparency and disclosure right, or we risk losing the trust that underpins all the value exchange.”
At the center of the framework is a straightforward query: Does AI involvement meaningfully change what a consumer thinks they’re seeing, hearing or interacting with? If the reply is yes, disclosure is predicted. That includes scenarios reminiscent of AI-generated or heavily synthesized images and videos depicting real-world events, synthetic voices of real people making statements they never made, digital twins placed in situations that never occurred, and conversational agents or avatars designed to simulate human interaction in ads.
Importantly, the IAB is just not calling for disclosures each time AI is involved in a campaign. Routine uses — reminiscent of AI-assisted editing, optimization or background workflows — don’t mechanically trigger labeling. The idea is to avoid disclosure overload while still protecting consumers from being misled.
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To make this workable across channels and platforms, the framework introduces a two-layer model. One layer is consumer-facing, using standardized text labels or visual cues like badges, icons, watermarks or interactive info elements placed near the ad creative. The other layer is machine-readable, counting on metadata standards reminiscent of C2PA to support technical compliance and downstream transparency.
For marketers, the framework is less about checking a compliance box and more about future-proofing AI adoption. As regulators, platforms and consumers scrutinize AI use more closely, having a shared industry standard gives teams a more straightforward option to balance speed, creativity and responsibility — without guessing where the road is.
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