Human Involvement in AI-Assisted Research
Does “Human in the Loop” in AI-assisted research indicate that GenAI was used effectively and responsibly? Not necessarily—it depends on how human researchers interact with AI. Read more »
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Psychology of Gen AI
- Future States & AI
- Article
Beyond the Recommendation: How Prompt Language Changes How AI Frames Your Brand
Generative AI tools are not just recommending products—they are shaping how consumers perceive them. This latest issue in the Psychology of Gen AI series, the third phase of the seventh study on AI product recommendations, examines how small changes in prompt wording alter the explanations AI systems generate around the same brand. Using ChatGPT descriptions of Arm & Hammer Advance White toothpaste across multiple, shopping-related prompts, the study reveals how AI recommendations construct different product narratives, emphasize different benefits and even introduce different caveats depending on the consumer’s wording of their question.
Member Only AccessThe Psychology of Gen AI (7c): When AI Recommends Your Brand, What Does It Say? How Prompts Shape the Stories AI Tells About Products: Deep Dive
This full report of the third phase of the seventh study on AI product recommendations in the Psychology of Gen AI series reveals how AI recommendations construct different product narratives, emphasize different benefits and even introduce different caveats depending on the consumer’s wording of their question.
Member Only AccessThe Psychology of Gen AI (7c): When AI Recommends Your Brand, What Does It Say? How Prompts Shape the Stories AI Tells About Products
This abridged version of the third phase of the seventh study on AI product recommendations in the Psychology of Gen AI series reveals how AI recommendations construct different product narratives, emphasize different benefits and even introduce different caveats depending on the consumer’s wording of their question.
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- Future States & AI
- Article
Finding Your Brand’s AI Niche: How Prompt Nuance Shapes Product Recommendations
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.
Member Only AccessIs AI a Neutral Proxy for Real People?
Comparing “real” people’s opinions with those generated by AI finds that models often mistake salience for truth. Read more »
Member Only AccessThe Psychology of Gen AI: How AI Decides What's Best: The Psychology Behind LLM Product Recommendations
As generative AI tools increasingly shape how consumers search, shop, compare and evaluate products, understanding how they make recommendations has become critical for marketers. This eighth abridged report in our ongoing Psych of Gen AI series examines how large language models (LLMs), like ChatGPT and Claude, determine what qualifies as the “best” product—and reveals that their recommendations are far from neutral. Instead, they tend to rely on narrow, repetitive sets of familiar brands and structured response patterns that may reinforce existing market leaders. The findings highlight important implications for brand visibility, competitive dynamics and how marketers should position their products in AI-driven environments.
Member Only AccessThe Psychology of Gen AI: How AI Decides What's Best: The Psychology Behind LLM Product Recommendations: Deep Dive
As generative AI tools increasingly shape how consumers search, shop, compare and evaluate products, understanding how they make recommendations has become critical for marketers. This eighth deep dive report in our ongoing Psych of Gen AI series examines how large language models (LLMs), like ChatGPT and Claude, determine what qualifies as the “best” product—and reveals that their recommendations are far from neutral. Instead, they tend to rely on narrow, repetitive sets of familiar brands and structured response patterns that may reinforce existing market leaders. The findings highlight important implications for brand visibility, competitive dynamics and how marketers should position their products in AI-driven environments.
Member Only Access