Consumer Behavior Theory in the Era of Generative AI

Jincheng Zhang

MPRA Paper from University Library of Munich, Germany

Abstract: With the rapid development of generative AI, traditional consumer behavior theories centered on "information search-rational decision-making" are undergoing structural changes. Consumers no longer rely solely on static information platforms but engage in interactive dialogue with generative AI, completing needs identification, solution generation, and decision optimization with the support of dynamically generated content. This paper proposes a "Generative AI-Driven Interactive Consumer Behavior Model" (GAIBB) based on the integration of classic consumer behavior theories (such as the Theory of Rational Behavior, the Theory of Planned Behavior, and the Theory of Experiential Consumption). This model emphasizes three mechanisms: "co-creation decision-making," "generative recommendation," and "instant feedback loop," explaining how AI reshapes consumers' cognitive paths and purchasing behavior. The research further indicates that generative AI is driving a shift in consumer behavior from "information acquisition" to "co-creation of cognition," and reconstructing the power structure between platforms, brands, and users.

Keywords: Generative Artificial Intelligence (Generative AI); Consumer Behavior Theory; Human–AI Interaction; Consumer Decision-Making; Interactive Consumer Behavior Model (GAICB). (search for similar items in EconPapers)
JEL-codes: B4 B41 O3 O35 (search for similar items in EconPapers)
Date: 2026-01-07
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