IAB introduces disclosure framework as Gen Z trust in AI ads plummets 19 points

The Interactive Advertising Bureau today launched its first AI Transparency and Disclosure Framework, a risk-based disclosure model designed to guide brands and platforms on when AI use in advertising requires consumer-facing labels. The framework arrives as new IAB research reveals a widening chasm between advertiser optimism about AI-generated ads and actual consumer sentiment.

According to research conducted by IAB in partnership with Sonata Insights, 82% of advertising executives believe Gen Z and Millennial consumers feel positively about AI-generated ads. Only 45% of these consumers actually feel that way. This perception gap expanded from 32 points in 2024 to 37 points in 2026, marking the second consecutive year the disconnect has grown.

David Cohen, CEO of IAB, stated in the announcement: "The digital industry is embracing AI in all of its splendor at breathtaking speed. We are certainly at a critical inflection point with generative AI. 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 the entire value exchange."

The framework introduces a materiality-driven approach that focuses disclosure requirements on AI uses that could mislead consumers about authenticity, identity, or representation. Routine production tasks, background AI tools, and clearly stylized creative work can proceed without disclosure under the model.

Framework avoids blanket labeling mandate

The AI Transparency and Disclosure Framework establishes a two-tier disclosure system combining consumer-facing labels with machine-readable metadata. Consumer-facing disclosures employ standardized text labels or visual cues including watermarks, badges, standardized icons, interactive tap-or-hover information elements, and adjacent placement positioning disclosure next to rather than embedded within creative assets.

Machine-readable metadata follows Coalition for Content Provenance and Authenticity protocols for technical compliance. The framework positions these metadata standards as complementary to rather than replacing consumer-facing disclosure requirements.

Caroline Giegerich, VP of AI at IAB, explained the rationale: "AI is reshaping how advertising is created and scaled, but trust is what will determine its longevity. Our research reflects a clear misperception between how advertisers think consumers feel about AI-generated advertising and how consumers actually experience it. That disconnect is exactly why materially-based disclosure matters."

The framework identifies specific AI applications requiring consumer-facing disclosure. Images or videos generated through text-to-image or image-to-image generation with limited human input beyond refinement qualify for mandatory disclosure when depicting real-world events. AI-generated voices of deceased persons creating statements they never made require disclosure even with estate authorization.

Living persons depicted through AI-generated voices making statements about events, actions, or circumstances that never occurred trigger disclosure requirements. This provision distinguishes between scripted commercial endorsements using AI voices versus synthetic representations of specific false scenarios.

Digital twins of deceased individuals require disclosure in any capacity regardless of estate permissions. Living individuals depicted as digital twins in events, scenarios, or locations that never occurred must be disclosed, though standard product endorsements or brand representations fall outside this requirement.

Synthetic avatars, AI chatbots, and conversational agents simulating human interaction in advertisements require consumer-facing labels according to the framework specifications.

Gen Z consumers demonstrate sharply negative sentiment

The IAB research, which surveyed 505 U.S. Gen Z and Millennial consumers alongside 104 advertising industry executives between October 2025 and January 2026, documented increasingly negative consumer sentiment toward AI advertising. Gen Z consumers proved nearly twice as likely as Millennials to feel negatively toward AI ads, with 39% reporting negative sentiment compared to 20% of Millennials.

The research found consumers significantly more likely than advertisers to describe brands using AI as "manipulative." Twenty percent of consumers selected this descriptor compared to 10% of advertising executives. Similarly, 16% of consumers called AI-using brands "unethical" while only 7% of executives chose this characterization.

Advertisers instead associated AI use with "innovation" at 46% and "uniqueness" at 44%, highlighting perception gaps between the industry and its target audiences. The divergence suggests fundamental misalignment in how the two groups evaluate AI deployment in commercial contexts.

The majority of Gen Z consumers specifically described AI-using brands as inauthentic, disconnected, or unethical according to the research findings. This generational split presents targeting implications for marketers as younger demographics that grew up with digital technology demonstrate stronger skepticism toward artificial intelligence in advertising than older cohorts.

Cost efficiency overtakes creative innovation as primary benefit

Advertiser priorities around AI shifted between the 2024 and 2026 studies. Cost efficiency emerged as the top-cited benefit in 2026 at 64%, up from fifth position in 2024. Creative innovation remained important but declined slightly from 64% to 61% over the two-year period.

The emphasis on cost reduction raises questions about whether some advertisers prioritize production savings over creative quality. Jack Koch, SVP of Research & Insights at IAB, addressed this concern: "This research shows that disclosure can play a decisive role in strengthening consumer relationships and determining whether AI use in advertising becomes a long-term value driver or a short-term liability. It also emphasizes that transparency and creative quality are essential to earning trust, shifting perceptions, and driving performance."

More than half of consumer respondents indicated brands should disclose if an ad was 100% AI-generated or uses AI imagery or video. Nearly half wanted disclosure for AI voices or AI avatars and virtual characters in advertising contexts.

The research documented 73% of Gen Z and Millennials saying clear disclosure would either increase or have no impact on their likelihood to purchase advertised products or services. This finding positions transparency as a trust-building mechanism rather than a deterrent to commercial effectiveness.

Consumers also indicated preferences for disclosing other creative manipulation techniques. Thirty-five percent wanted digitally adjusted images or video disclosed, 31% supported disclosure of manipulated photo shoot techniques, and 23% believed stock photo usage should be identified to audiences.

Disclosure intensity varies by industry category

The research examined disclosure importance across multiple industry categories. Pharmaceutical and healthcare advertising ranked highest, with 69% of advertisers and 65% of consumers considering disclosure very important in this sector. Political advertising followed closely at 70% of advertisers and 63% of consumers.

Financial services advertising showed 71% of advertisers considering disclosure very important compared to 58% of consumers. Entertainment advertising ranked lowest in disclosure importance, though 54% of advertisers and 53% of consumers still considered it very important in this category.

Consumer products, fashion and beauty, and travel and hospitality sectors fell in the middle range. The cross-category consistency suggests broad agreement that AI usage warrants disclosure regardless of product type, though intensity varies based on perceived stakes and regulatory sensitivity.

Heavily regulated industries including pharmaceuticals, finance, and political advertising face existing disclosure requirements that extend to AI-generated content. The framework provides structured guidance for these sectors already managing complex compliance obligations.

Industry faces mounting transparency pressures

The framework release coincides with growing concerns about AI transparency across the advertising ecosystem. Lindsay Rowntree, COO at ExchangeWire, recently characterized agentic AI as "a giant black box" during podcast discussions about the Ad Context Protocol launched in October 2025.

According to 2023 research cited in industry discussions, transparency challenges resulted in only 36 percent of post-transaction programmatic budgets reaching valid, viewable, measurable impressions. These longstanding issues predate current AI adoption but compound as automated systems increase opacity in advertising operations.

Platform-specific AI implementations have proliferated throughout 2025 while coordination across industry stakeholders remains limited. Google introduced AI Max for Search campaigns in August 2025 with enhanced Performance Max reporting addressing advertiser transparency demands. Amazon launched AI agents for campaign management in November 2025. These platform-specific tools deliver operational benefits but lack standardized disclosure approaches.

IAB Tech Lab CEO Anthony Katsur warned in December 2025 that the advertising industry must fix transparency and privacy issues before embracing agentic AI. "Protocols don't solve for misaligned incentives and bad actors," Katsur stated during a podcast appearance on December 29, 2025.

The framework positions IAB as setting industry leadership standards ahead of regulatory mandates. Multiple jurisdictions have implemented or proposed AI disclosure requirements for political advertising specifically. New York pursued restrictions on AI use in political ads during the final 90 days of elections. The European Union's AI Act entered force in August 2024 with most obligations beginning August 2, 2025.

Consumer trust concerns extend beyond political content

Research released throughout 2025 consistently documented consumer skepticism toward AI-generated content across categories. A Raptive study published in July 2025 found suspected AI content reduces reader trust by nearly 50%. The research showed 14% decline in purchase consideration when consumers believed content was AI-generated.

DoubleVerify's 2025 Global Insights Report documented 65% of marketers expressing brand suitability concerns about advertising adjacent to AI-generated content. The ad verification company surveyed 1,970 marketing decision-makers across 21 countries, revealing heightened anxieties about content adjacency and contextual appropriateness.

Consumer privacy concerns intensified as AI reshapes data collection practices. Verve survey data released in December 2025 showed 65% of consumers expressing more concern about AI data training than two years prior. The research documented 97% of respondents agreeing that app publishers and platforms need greater transparency about data collection and handling practices.

These converging trends create pressure for standardized disclosure approaches that address both regulatory compliance and consumer trust maintenance. The IAB framework attempts to balance these competing demands through risk-based materiality assessments rather than universal labeling requirements.

Regulatory landscape drives adoption incentives

IAB emphasized regulatory momentum as strategic motivation for framework adoption. The European Union's AI Act, U.S. state laws, and platform-specific disclosure requirements create fragmented compliance landscapes that standardized frameworks could streamline.

Organizations adopting the framework signal leadership, trustworthiness, and regulatory readiness according to IAB positioning. Early adoption potentially provides competitive differentiation as transparency expectations increase across consumer segments and regulatory jurisdictions.

The framework invites advertisers, agencies, publishers, and technology partners to publicly commit to principles of transparency, proportionality, consistency, and clarity in AI disclosure practices. This voluntary compliance model parallels other IAB technical standards that achieved broad adoption through industry coordination rather than regulatory mandate.

Machine-readable metadata requirements align with C2PA protocol development occurring across technology sectors. C2PA embeds information about content creation, modification, and AI involvement directly within digital files. Major technology companies including Adobe, Microsoft, and others have supported C2PA development as a technical standard for content provenance.

The dual disclosure approach combining consumer-facing labels with technical metadata addresses both immediate transparency needs and long-term infrastructure development. Consumer labels provide immediate comprehension while metadata enables programmatic verification and supply chain transparency.

Advertiser concerns shift from consumer perception to operations

The 2026 research documented substantial changes in advertiser priorities compared to 2024 findings. Consumer perception ranked as the second-biggest advertiser concern in 2024 alongside potential for errors or inappropriate content. In 2026, consumer perception fell significantly in priority rankings.

Advertisers instead focused on impact on human creativity, implementation cost, and brand authenticity in the current study. Legal and ethical concerns declined substantially between survey periods, suggesting either increased confidence in compliance approaches or reduced emphasis on risk management relative to operational efficiency.

This inward focus on operational impacts rather than external reception creates potential risks as consumer skepticism grows. The research suggests advertisers may be optimizing for internal metrics while consumer sentiment moves in opposite directions.

The 89% of advertisers using generative AI who at least sometimes disclose this usage represents marginal increase from 2024 levels. However, less than half always disclose, indicating substantial variation in transparency practices even among advertisers acknowledging disclosure importance.

Disclosure emerged as the third-highest driver of consumer attention in research findings, trailing only high-quality visuals and funny content. This suggests transparency serves dual functions as trust mechanism and attention-capturing creative element rather than being purely compliance-oriented.

Framework provides guidance for complex synthetic media cases

The framework addresses nuanced scenarios where AI involvement creates ambiguity about disclosure requirements. Digital twins of public figures require disclosure when depicted in scenarios that never occurred, but voice synthesis for commercial endorsements following scripts falls outside mandatory disclosure.

Deceased person representation receives strict treatment requiring disclosure regardless of estate permissions or context. This provision acknowledges unique ethical considerations around posthumous digital resurrection that extend beyond standard advertising practices.

The distinction between prompt-driven generation with minimal human oversight versus AI-assisted editing reflects materiality thresholds. Photographers using AI tools for color correction or minor retouching would not trigger disclosure under framework guidelines, while generative creation of entire scenes from text prompts would require labeling.

Synthetic avatars and chatbots face disclosure requirements based on their simulation of human interaction rather than mere animated character usage. This targets consumer protection against deceptive relationship formation with AI systems presented as human representatives.

The framework specifications acknowledge that disclosure practices will require industry testing and iteration. IAB positioned the initial release as establishing principles and approaches rather than finalized technical specifications ready for immediate universal implementation.

Implementation challenges remain for scaled adoption

The framework provides conceptual guidance but leaves significant implementation questions for individual organizations and platforms. Standardized visual indicators, placement guidelines, and text label specifications require additional development before achieving consistency across advertising environments.

Platform-specific technical constraints affect disclosure implementation feasibility. Social media platforms, connected television environments, audio advertising, and display formats each present distinct challenges for visual indicator placement and interactive disclosure mechanisms.

The reliance on advertiser-led decisions about consumer-facing disclosure creates potential for inconsistent application across competitive contexts. Brands may interpret materiality thresholds differently based on risk tolerance, legal guidance, and competitive positioning.

Machine-readable metadata adoption depends on content management system support, creative tool integration, and supply chain coordination. C2PA protocol implementation requires technical infrastructure investments that smaller advertisers and publishers may struggle to prioritize.

Verification and enforcement mechanisms remain underdeveloped in the framework specifications. Third-party measurement companies and platforms will need to develop detection capabilities and policy enforcement approaches as disclosure becomes expected practice.

The voluntary nature of framework adoption limits its immediate impact on advertisers who view transparency as competitive disadvantage or unnecessary operational burden. Regulatory mandates may ultimately prove necessary to achieve universal compliance.

Research methodology and limitations

IAB conducted the research using the IAB Insights Engine platform powered by Attest. The survey included 505 U.S. Gen Z consumers aged 16-27 and Millennials aged 28-43 who engaged with advertisements. Additionally, 104 U.S. advertising industry executives working for companies with annual media spending of at least $1 million participated.

The survey occurred between October 2025 and January 2026. The comparison survey from 2024 included 300 U.S. Gen Z and Millennial consumers and 75 U.S. advertising industry executives, conducted between August and October 2024.

The research focused on U.S. markets and may not reflect international consumer attitudes or regulatory contexts. Gen Z and Millennial focus excludes older demographic perspectives that could differ substantially from younger cohorts.

Self-reported attitudes about AI-generated advertising may not predict actual behavior when encountering disclosed content in commercial contexts. The research measured stated preferences rather than observed responses to disclosed advertisements in real campaign environments.

Advertising executive respondents represent companies with substantial media budgets potentially skewing toward sophisticated advertisers with dedicated AI strategies. Smaller advertisers and local businesses operating with different constraints remain underrepresented in research findings.

Timeline

• August 2024: European Union's AI Act enters force, establishing framework for high-risk AI systems
• August 2025: Most EU AI Act obligations begin taking effect across member states
• August 2025: Google Ads API v21 introduces AI Max for Search campaigns with enhanced Performance Max transparency tools
• October 2025: Ad Context Protocol launches, sparking industry debate about agentic AI standardization needs
• October 2025-January 2026: IAB conducts research on AI advertising sentiment using Insights Engine platform
• November 2025: Amazon launches AI agents for campaign management following September seller platform updates
• December 2025: IAB Tech Lab CEO warns industry about transparency challenges with agentic AI adoption
• January 9, 2026: IAB Tech Lab releases Agentic Roadmap outlining approach to prevent AI fragmentation
• January 15, 2026: IAB releases AI Transparency and Disclosure Framework alongside consumer sentiment research

Summary

Who: The Interactive Advertising Bureau released the framework in partnership with Sonata Insights for research. The announcement affects brands, agencies, publishers, platforms, and consumers across the digital advertising ecosystem. David Cohen serves as IAB CEO, Caroline Giegerich leads AI initiatives as VP of AI, and Jack Koch oversees research as SVP of Research & Insights.

What: IAB launched its first AI Transparency and Disclosure Framework establishing risk-based disclosure requirements for AI use in advertising. The framework requires consumer-facing labels for synthetic humans, digital twins, AI-generated voices in false scenarios, and AI chatbots. Companion research reveals a 37-point gap between advertiser perceptions and actual Gen Z/Millennial consumer sentiment toward AI advertising, with only 45% feeling positively despite 82% of executives believing they do.

When: IAB released the framework and research on January 15, 2026. The research surveyed consumers and executives between October 2025 and January 2026, comparing findings to 2024 baseline data collected between August and October 2024. The announcement arrives as EU AI Act obligations began taking effect in August 2025 and multiple platforms launched agentic AI capabilities throughout late 2025.

Where: The framework applies globally across digital advertising platforms including social media, connected television, display advertising, and audio channels. Research focused on U.S. Gen Z and Millennial consumers and advertising executives at companies spending at least $1 million annually on media. Regulatory pressures come from the European Union through the AI Act and various U.S. state-level disclosure requirements.

Why: IAB introduced the framework to address growing consumer skepticism toward AI advertising while providing standardized guidance ahead of fragmented regulatory mandates. Research shows consumer trust challenges intensifying as 39% of Gen Z feels negatively toward AI ads compared to 20% of Millennials. The framework aims to build consumer trust, reduce regulatory risk, and establish industry leadership in responsible AI adoption as transparency issues threaten advertising effectiveness and platform credibility.