Navigating the Trust Paradox: AI-Generated Fake Reviews, Influencer Transparency, and Consumer Purchase Intentions in Digital Markets

Abstract

The marketing industry is increasingly filled with content generated by artificial intelligence (AI), yet the effect of this content on consumer trust remains largely unknown. This study investigated the effects of AI-generated fake reviews, bot engagement, influencer transparency, and perceived authenticity on consumer trust, brand credibility, and purchase intention. Data from a quantitative survey of 402 respondents across age groups and product categories were analyzed with Pearson correlation, mediation analysis, moderation analysis (linear regression), exploratory factor analysis, and chi-square tests. The results point to a “transparency paradox” in influencer marketing: explicit influencer disclosure was weakly but significantly associated with lower trust, and exposure to AI-generated fake engagement had a moderate negative association with purchase intention. Perceived authenticity and consumer skepticism formed the strongest mediating construct and accounted for a large part of the link between transparency and trust. The study extends source credibility theory, dual-process cognition, and heuristic persuasion by showing that consumers recognize inauthenticity and still respond to volume-based social proof. Brands, content platforms, and regulators can draw on these results to design ethical and effective digital marketing ecosystems.