As generative AI tools increasingly influence product discovery and decision-making, subtle cues in user language can shape what consumers are shown—and how options are framed. This research examines how implicit and explicit gender signals affect AI-generated product recommendations, revealing systematic differences in categories, brand repetition, descriptive language and price information. The findings raise important questions for advertisers and researchers about bias, brand visibility and the growing cultural role of AI in shaping consumer norms.
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On January 22, we introduced a fundamentally different paradigm: One-Demand Decision AI powered by Large Causal Models (LCMs) that move enterprises from descriptive insights to prescriptive growth recommendations through counterfactual causal reasoning. Attendees gained a clear understanding of how one-demand causal AI transforms descriptive correlation into prescriptive causation, what it takes to implement unified decision platforms at scale, and why now is the moment to rethink the measurement stack from first principles.
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A new ARF Psych of GenAI experiment reveals that large language models apply a rigid, rule-driven logic when evaluating privacy scenarios—even when humans typically shift their reasoning based on framing, emotion and social context. Unlike consumers, who blend intuition, feeling and social perspective into their judgments, GPT-4o relied on a single internal rule across all testing conditions: data use is acceptable only with explicit consent. This consistency offers value for certain analytic tasks but exposes limits for advertising research that depends on emotional nuance and context-sensitive consumer insight.
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Artificial intelligence is rapidly changing how consumers discover, research and evaluate products, creating a hybrid search ecosystem where traditional engines like Google remain dominant while GenAI tools increasingly shape mid-funnel decision-making. Shoppers turn to AI for clarity, comparison and confidence, yet still validate information before purchase, altering the structure of the journey and the expectations placed on brands. As AI-driven search and shopping become more influential, the implications for marketers and retailers are profound, demanding new approaches to trust, data accuracy, discoverability and optimization for agent-driven environments. This Knowledge at Hand and CMO Brief reports show how AI is reorganizing the consumer path to purchase and what this means for the future of brand visibility and retail marketing.
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