From Artificial Creativity to Consumer Trust: Examining AI-Generated Content in Social Media Marketing

Abstract

This study examines the relationship between the disclosure of AI-generated content, perceived content authenticity, and consumer trust in social media marketing, while also evaluating the moderating role of consumer skepticism toward AI. Grounded in Signaling Theory and the Persuasion Knowledge Model, the study conceptualizes consumer trust as an outcome of transparency regarding technological origins and the assessment of content authenticity, wherein skepticism shapes how consumers interpret disclosure signals. Employing a quantitative cross-sectional research design, data were collected via a 5-point Likert scale questionnaire from 385 active social media users in Vietnam who had encountered AI-generated or AI-assisted marketing content. Data were analyzed using IBM SPSS version 26 for reliability assessment, exploratory factor analysis, and multiple linear regression, while Model 1 of the PROCESS Macro (developed by Hayes) was applied to test the moderating effect. The results indicate that both the disclosure of AI-generated content (β = 0.625) and perceived content authenticity (β = 0.576) significantly contribute to strengthening consumer trust in social media marketing. Disclosure exerts a slightly stronger direct impact, highlighting the importance of clearly communicating AI's involvement in the content creation process. Furthermore, consumer skepticism toward AI significantly weakens the positive relationship between AI content disclosure and consumer trust, as evidenced by a negative interaction coefficient of -0.499. These findings confirm that mere disclosure is insufficient to build trust among highly skeptical consumers. Brands must combine genuine transparency with authentic content, information verification, clear accountability, and human oversight to maintain trust in social media marketing that utilizes AI-generated content.