Consumer AI skepticism in marketing: an integrative review and conceptual framework

Abstract

Despite growing adoption of artificial intelligence in marketing, consumers frequently resist or avoid AI-driven interactions, a phenomenon that remains theoretically fragmented across disciplines. This paper presents an integrative review of 43 peer-reviewed studies published between 2023 and 2025, employing thematic synthesis to identify and organize the antecedents of consumer AI skepticism in marketing contexts. Five analytical themes emerge from the corpus. First, consumers reject AI because it fails to approximate human understanding, authenticity, and agency, a pattern termed the humanity deficit. Second, systemic opacity, unfairness, and privacy violations compound individual resistance through what is identified as governance failure. Third, marketing task type, relationship norms, and product category determine whether skepticism is activated or suppressed. Fourth, consumer experience does not simply reduce skepticism but reconfigures its dominant concerns from distrust-based to authenticity-based to governance-based over time. Fifth, unresolved skepticism consistently suppresses purchase and adoption intention, impairs brand credibility, and reduces consumer engagement. These themes are integrated into the Consumer AI Skepticism Framework (CASF), which positions humanity deficit and governance failure as direct antecedents, marketing context as a moderator, consumer learning as a temporal dimension, and behavioral consequences as downstream outcomes. Theoretical contributions and managerial implications are discussed.