After conducting eight studies over the past year, what has the ARF learned about the psychology of generative AI? Across experiments examining bias, identity cues, product recommendations, executive decision-making and AI-assisted research, four patterns repeatedly emerged: GenAI tends to compress human variability into dominant responses, subtle differences in prompting can meaningfully change outputs, different models bring their own constraints and tendencies and AI can imitate the language of expertise more readily than it can exercise expert judgment. Taken together, the studies suggest that GenAI’s greatest strength and its greatest risk may be the same: its ability to produce coherent, convincing answers can make compression, instability and missing judgment difficult to see.
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Differentiation has been proven to be an important driver of brand equity and sales. Biases in AI models could undermine these goals. Read more »
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The discrepancy between what people say they do and what they actually do has been a research problem for decades. Here is a fresh look.
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As generative AI becomes a key part of how consumers discover and evaluate products, a new question emerges for marketers: how can they ensure their brands show up in AI-driven recommendations? This ARF and MSI experiment, the second phase of the seventh study in the Psychology of Gen AI series, reveals that even small changes in prompt wording can significantly influence which brands appear—helping non-market dominant brands carve out visibility by aligning with specific product attributes rather than competing broadly for “best” status.
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