New study reveals brain processes AI-generated ads differently than traditional content
Research shows consumers' brains detect AI-generated advertising content even when visually convincing, impacting brand perception.
Three days ago, on December 12, 2024, NielsenIQ revealed significant findings about how consumers process AI-generated advertisements at both conscious and subconscious levels. The research, scheduled for presentation at CES 2025, examined brain responses to artificial intelligence-generated advertising content through extensive neurological testing.
According to Ramon Melgarejo, President of Strategic Analytics & Insights at NIQ, brands and agencies need to exercise caution when implementing AI-generated content in their advertising strategies. The study's findings indicate that consumers demonstrate heightened sensitivity to the authenticity of advertising materials at both implicit and explicit cognitive levels.
The research methodology involved more than 2,000 participants viewing various AI-generated advertisements ranging from low to high quality. Scientists measured brain activity using electroencephalogram (EEG) technology for approximately 150 participants, complemented by comprehensive survey feedback from all subjects.
The study identified several critical patterns in consumer responses. Most notably, participants instinctively recognized AI-generated content, describing these advertisements as less engaging compared to traditional approaches. The research documented specific negative associations, with viewers characterizing AI-generated content as "annoying," "boring," and "confusing."
Neurological measurements revealed decreased memory activation in response to AI-generated advertisements, even for content rated as high quality. This reduced memory engagement suggests a fundamental disconnect between AI-generated content and established cognitive processing patterns.
The research team, led by Avgusta Shestyuk, PhD, Global Head of Science and Research, Neuroscience for the NIQ BASES Product Leadership team, discovered that while AI-generated advertisements successfully activated brand associations, they simultaneously triggered negative perceptual effects that could potentially harm brand equity.
Technical analysis of viewer responses demonstrated that low-quality visual elements in AI-generated advertisements increased cognitive processing demands, potentially distracting from intended messaging. The study found that human brains are particularly sensitive to subtle deviations from expected human appearances and movements, a phenomenon known as the Uncanny Valley Effect.
Marta Cyhan-Bowles, Chief Communications Officer and Head of Global Marketing at NIQ, emphasized that while AI technology presents opportunities for early-stage ideation and brand asset testing, poorly executed AI content risks damaging brand perception. The research suggests that current AI technology, despite its rapid advancement, has not yet reached the sophistication level required to fully replace traditional advertising content creation.
The study's implications extend beyond immediate advertising applications. NIQ's research indicates that AI-generated content influences long-term consumer-focused product development and marketing efficiency. The findings suggest that while AI tools can enhance creative processes, they require careful implementation to maintain advertising effectiveness.
NielsenIQ, which combined operations with GfK in 2023, conducted this research across its global network spanning more than 95 countries and covering 97% of global GDP. This extensive reach provided comprehensive insights into consumer behavior patterns and advertising response mechanisms.
The complete findings will be presented at the CES 2025 panel session titled "Adapting to Change: Demographic Shifts in Advertising Strategy" scheduled for January 9, 2025, at 10:00 a.m. PST. The presentation will explore generational considerations in AI-generated advertising perception and implications for future advertising strategies.
NIQ's research methodology incorporated multiple evaluation techniques, including electroencephalogram measurements, eye-tracking technology, implicit response time analysis, and traditional survey methods. This multi-faceted approach provided detailed insights into both conscious and unconscious consumer responses to AI-generated advertising content.
The study represents a significant contribution to understanding the intersection of artificial intelligence and consumer behavior in advertising, offering data-driven insights for brands and agencies navigating the evolving advertising landscape.