Emerging Perspectives on Consumer–AI Interaction
(A2026-132492)

AUTHORS

Yue Zhang, Erasmus University Rotterdam; Anne-Kathrin Klesse, Erasmus University, Rotterdam School of Management; Alixandra Barasch, University of Colorado Boulder; Anush Sridhar, University of St.Gallen; Ana Valenzuela, Baruch College, CUNY; Melanie Clegg, University of Lausanne

ABSTRACT

Session Abstract This session integrates emerging perspectives on how consumers make sense of AI across time—past, present, and future. Together, the papers trace evolving lay beliefs about AI, from historical media narratives to contemporary cultural forces that guide how people engage with algorithmic systems, to future-oriented expectations that lead consumers to imbue AI with capabilities such as predicting randomness or acting as autonomous agents. Patterns in the Perceived Threat of Artificial Intelligence: A Media Discourse Analysis Anush Sridhar, Tobias Ebert, Emanuel de Bellis, Stefano Puntoni Analyzing New York Times articles, we develop a seven-dimensional framework of AI threat perception. Findings reveal shifting discourse, with autonomy, equity, and psychological concerns rising, offering insights for communication and AI adoption strategies. “We” Listen to Algorithms: How Cultural Values Influence Responses to AI Yuanyuan Zhang, Diogo Hildebrand, Ana Valenzuela The present research identifies an important cultural variable that predicts a difference in consumer receptivity to AI. Evidence across six studies suggests that an interdependent (vs. independent) self-construal consumer is more receptive to AI-based recommendations, and this effect stems from consumers’ lay belief that recommendations generated by AI reflect consensus. When AI Becomes Agentic: Societal Threat and Consumer Resistance Melanie Clegg, Reto Hofstetter, Emanuel de Bellis, Bernd Schmitt This research conceptualizes and examines consumer reactions towards agentic AI assistants that can plan and act independently. Although agentic AI offers new levels of convenience, we theorize and show that consumers react negatively to it because agentic capabilities in AI are perceived as a threat to society. Can AI Predict Randomness? Consumers Use AI For Predicting Gambling Outcomes Yue Zhang, Anne Kathrin Klesse, Alixandra Barasch This research finds that consumers mistakenly believe AI is more likely than themselves to predict purely chance-based outcomes, leading them to bet more on AI predictions and potentially harming their well-being.