Consumer Responses to Generative AI in Marketing: A Systematic Literature Review and Causal-Chain Framework

Abstract

Generative artificial intelligence (GenAI) is increasingly embedded in consumer-facing marketing activities, yet research on consumer responses remains fragmented across theoretical perspectives, marketing contexts, and constructs. This study systematically reviews and synthesizes the emerging literature to develop an integrative causal-chain framework of consumer responses to GenAI in marketing. Following a structured search and screening process using Scopus and Web of Science, 143 core studies were retained for analysis. The review maps their theoretical foundations, methodological characteristics, marketing contexts, and constructs, organizing the latter according to their roles as antecedents, mediators, moderators, and outcomes. The findings reveal substantial theoretical diversity but also recurring patterns across the literature. Consumer responses originate from characteristics of GenAI sources and production, content and messages, AI agents and systems, consumers, and marketing contexts, and operate through cognitive-functional, affective-experiential, social-relational, legitimacyrelated, and attitudinal mechanisms. Trust, authenticity, and credibility emerge as particularly prominent legitimacy-related mechanisms across the reviewed literature. The evidence further indicates that GenAI effects are highly contingent on factors including disclosure, human involvement, content and product characteristics, modality, and consumer differences. Finally, the literature remains substantially more developed in explaining consumer evaluations, relationships, and behavioral intentions than actual and sustained marketplace behavior. By integrating these fragmented relationships into a common causal architecture, the study provides a structured foundation for cumulative research and more context-sensitive managerial decision-making regarding GenAI in marketing.