THE IMPACT OF ARTIFICIAL INTELLIGENCE GENERATED CONTENT ATTRIBUTES ON PERCEIVED AUTHENTICITY IN SOCIAL MEDIA ADVERTISING

Abstract

The rapid growth of artificial intelligence-generated content is reshaping how users perceive advertising on social media and raises the question of whether machine-generated messages can be viewed as “authentic.” Based on the Cue Utilization Theory, this study examines the effects of three content attributes informative, creativity, and clarity on perceived authenticity in artificial intelligence-generated advertising. Survey data from 1,069 social media users in Vietnam were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that informative and creativity have positive effects on perceived authenticity, whereas clarity is not statistically significant. The model explains 18.8% of the variance in perceived authenticity (R² = 0.188). The study provides empirical evidence for the Cue Utilization Theory in the context of artificial intelligence, and suggests that artificial intelligence-generated advertising should prioritize informative and creatively enriched content to enhance perceived authenticity on social media platforms.