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 takes a risk-based approach that focuses on consumer impact – disclosing AI use only if it materially affects authenticity, identity or representation in a way that could mislead people.
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“We are certainly at a critical inflection point with generative AI,” said David Cohen, CEO of IAB, in a statement. “As AI transforms the way we work, from ideation to execution and measurement, we must ensure transparency and disclosure or risk losing the trust that underpins the entire value exchange.”
At the heart of the framework is a simple question: AI involvement meaningfully changes what a consumer thinks they see, hear or interact with? If the answer is yes, disclosure is expected. That includes scenarios such as AI-generated or heavily synthesized images and videos that depict real-world events, synthetic voices of real people making statements they never made, digital twins placed in situations that never happened, and conversational agents or avatars designed to simulate human interaction in advertisements.
Importantly, the IAB does not call for disclosure every time AI is involved in a campaign. Routine use – such as AI-assisted editing, optimization, or background workflows – does not automatically trigger labeling. The idea is to avoid disclosure overload while protecting consumers from being misled.
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To make this workable for all channels and platforms, the framework introduces a two-tier model. One layer is consumer-facing and uses standardized text labels or visual cues such as badges, icons, watermarks, or interactive information elements placed near the creative. The other layer is machine-readable and relies on metadata standards such as 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 take a closer look at the use of AI, having a shared industry standard gives teams an easier way to balance speed, creativity and responsibility – without guessing where the line is drawn.
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