Positive Effects of Negative Disclosure: The Persuasive Power of Negative AI-Generated Content in Shaping Consumer Product Attitude

Artificial intelligence-generated content (AIGC) holds significant potential and diverse applications in e-commerce. Although existing research has largely focused on AI’s role in personalized recommendations and product advertising, few studies have examined AI-generated reviews. Drawing on source credibility theory (SCT), this study develops a research model to explore how displaying AI-generated negative reviews influences consumers’ product attitudes. Using data from a Chinese e-commerce platform that employs AI to generate product reviews, we test our hypotheses through ordinary least squares (OLS) analysis. Our results indicate that displaying AI-generated negative reviews can enhance perceived review credibility and reduce perceived risk, ultimately improving consumers’ product attitudes. Moreover, the impact of such reviews varies depending on product and influencer-related factors. By investigating the effects of AI-generated negative reviews on product attitudes, this study contributes to the AIGC and online review literature while offering practical governance insights. For platforms and retailers, these findings underscore the strategic value of negative reviews in fostering consumer trust and engagement.