On the 18th August, the Interactive Advertising Bureau (IAB) released a second, updated version of its AI Transparency Disclosure Framework, which aims to give the advertising industry a practical guide on how to properly disclose the use of AI in marketing content.
Building on its first framework released in January 2026, the new edition aims to reflect regulatory shifts across the US, UK and Asia – where most regulators have moved from proposal to enforcement.
The IAB highlights distinct regulatory Acts that have come into play recently, which have included:
– New York’s Synthetic Performer Law, June 9 2026 – advertisers must disclose when a synthetic performer has been used in an ad or face fines of $1000 for a first offence or $5000 for subsequent violations.
– California’s SB 942, August 2nd 2026 – providers of GenAI systems with over 1 million monthly users must offer a free AI-content detection tool and embed visible and hidden disclosures marking content as AI-generated.
– South Korea’s AI Basic Act, January 2026 – a national framework requiring providers of AI-generated and high impact AI to disclose AI use, imposing extra safety obligations.
– EU’s Article 50 AI Act, August 2nd 2026 – providers of certain AI systems and deepfakes must disclose AI involvement to users, with fines of up to $15 million or 3 percent of global turnover for non-compliance, and deployers have disclosure obligations concerning deepfakes and manipulated public-interest text.
A Two-Layer Disclosure
An IAB study found that clear disclosure is the third-highest driver of consumer attention for AI-generated ads. Additionally, 73 percent of Gen Z and Millennial respondents say that an AI ad would either increase or have no effect on their likelihood to purchase.
Already a part of the January framework, IAB doesn’t just provide a recommendation for a visual label (explicit text label or sparkle icon), but also suggests a two-layer disclosure model, which includes a visible label and an invisible metadata label, such as the Coalition for Content Provenance and Authenticity (C2PA).
The Negative Impact of Over-Disclosing
As international brands navigate these major compliance shifts, the updated IAB guidelines continue to highlight consumer perceptions of AI-use in advertising, and how AI disclosure impacts trust and the brand-consumer relationship.
IAB says that content that warrants disclosure are from high-risk use cases, particularly where consumers could be misled. Much of the content it suggests labeling are when AI is heavily used – such as videos generated from prompts, synthetic voices and avatars, content generated of deceased individuals, and AI chatbots that could be mistaken for a human.
AI used for internal workflows, post-production, or standard audio enhancement does not automatically require labels, IAB outlined.
‘Label Fatigue’
The framework is underpinned by an ethos of targeted labelling of AI content, instead of universally labelling content helped by the technology. This is because, as the IAB puts it, consumers can become fatigued by AI labels, especially as so much advertising content becomes AI-fuelled in some capacity.
The framework highlights a phenomenon called the “implied truth effect” whereby the presence of AI labels on some content can lead audiences to perceive unlabelled content as more credible or authentic by comparison.
If content is over-labelled, they can become meaningless, potentially leading to consumers overlooking them.
“Not every use of AI needs a label – labeling everything teaches consumers to ignore labels and could negatively impact advertisers,” said Caroline Giegerich, VP for AI at IAB. “This is why we take a meticulously nuanced position in this framework.”
