ARF Presentation: How Marketers Are Adopting AI
Tracy Adams, PhD, presented findings from two waves of ARF research conducted six months apart among 203 U.S. advertisers and agencies at organizations spending at least $1 million annually on advertising. The study examined where AI is being used, confidence in its outputs, and whether training, testing, validation and governance are keeping pace with adoption.
Average use across measured marketing activities increased from 58% in November 2025 to 76% in May 2026. Confidence among marketers using AI-generated outputs rose from 82% to 93%, while formal AI training increased from 50% to 70%. Text generation remains the most common application at 87%, followed by image generation at 71%, but AI is also being used across customer engagement, media buying, optimization, analytics, measurement and attribution.
Synthetic data and AI personas remain less common, at 36% each, but are strategically important because they bring AI closer to representing consumers. Among synthetic data users, 70% use it for research simulation, 68% for forecasting or analytics and 66% for testing campaign or creative variations. At this stage, these tools are primarily being used to support decisions rather than replace human research.
The findings also revealed a gap between confidence and governance. Although 64% reported extensive testing, 75% had a dedicated role or team involved in validation and 70% offered formal training, only 52% had formal internal AI policies. This suggests that confidence is developing faster than the shared standards and evidence systems needed to support it.
Humantel Presentation: What Consumers Think
Justin Fromm, Samsung Ads, presented Humantel Media research based on more than 4,000 U.S. consumers ages 16 to 74, surveyed in March 2026. The findings showed that consumer attitudes toward AI are marked by tension: curiosity coexists with skepticism, while excitement sits alongside fear.
Consumers see clear value in AI’s ability to explain complicated topics, help them find information and make product comparisons more efficiently. Their largest concerns, however, center on truth and authenticity. More than half said they worry about not knowing whether images, videos or news stories are real, and related research found that 55% of Americans assume they often or always encounter AI-generated content in news and informational environments.
In advertising, consumers appear to want restraint more than hyper-personalization. They are especially interested in AI being used to reduce repetitive ads, manage frequency, limit clutter and help them discover products or services that are genuinely relevant.
Panel Discussion: Value, Trust and Control
Tracy, Justin, Molly Austin of Uber Advertising and Sarah Holley of Nordic Naturals emphasized that marketer benefits such as efficiency, speed and lower costs do not automatically translate into consumer value. AI becomes useful to consumers when it reduces friction, solves a problem in the moment, simplifies decisions or helps them feel more in control.
Control emerged as a central condition of trust. Consumers are more comfortable when they understand how AI is being used, can influence the amount of AI content they encounter and can correct signals that do not reflect their actual preferences. Intentional behaviors such as purchases or orders may feel more acceptable as inputs than opaque inferences about health, finances, family circumstances or personal values.
The panel also discussed the complexity of disclosure. Transparency may build trust, but it can also increase skepticism or reduce liking when consumers become more conscious that something was AI-generated. Because AI may be involved in targeting, optimization, analytics or creative production, the industry still needs clearer standards for what should be disclosed and when.
Finally, the panelists cautioned against treating “human in the loop” as a simple review step. Meaningful human involvement requires strategic judgment, originality, empathy and accountability. The most promising uses of AI are those that improve frequency management, reduce consumer friction and help marketers understand why something worked. Greater caution is needed around synthetic data, fully automated personalization and sensitive behavioral inference.
Key Takeaways
- Consumers see value in AI when it simplifies information, improves comparison shopping and reduces friction.
- Consumers want AI to reduce repetitive advertising and clutter more than they want greater personalization.
- Truth, authenticity and manipulation remain major concerns, particularly around AI-generated media.
- Trust depends heavily on giving consumers greater transparency and control.
- Consumers are more accepting of intentional behavioral signals than sensitive or inferred personal information.
- Disclosure can support transparency but may also heighten skepticism.
- Human involvement should center on judgment, empathy and strategy rather than simple approval of AI outputs.
- Brands should scale uses that improve the consumer experience and proceed cautiously with synthetic data, hyper-personalization and behavioral inference.