The Impact of AI Personalization on Customer Engagement on TikTok: The Role of Trust, Perceived Usefulness, and Usage Intention - Britney Marchsyela Alchotib; Grace Vernanda; Muhammad Izzas Ferdiansyah; Kevin Suryaatmaja (Dinasti Review Publisher, 2026)
Amid the rapid integration of artificial intelligence (AI) in social media, this study examines the effect of AI-driven personalization on customer engagement on TikTok, with trust, perceived usefulness, and usage intention as mediating variables. Using the Stimulus–Organism–Response (SOR) framework, data were collected from 238 Indonesian users aged 18–34 and analyzed using Structural Equation Modeling (SEM). The results show that AI personalization has significant positive effects on trust, perceived usefulness, and usage intention. These variables, in turn, significantly influence customer engagement. Mediation analysis indicates that trust and usage intention fully mediate the relationship between AI personalization and engagement, while perceived usefulness acts as a partial mediator. Furthermore, Multi-Group Analysis (MGA) reveals no significant differences across gender and education, indicating model consistency across demographic groups. This study highlights that in fast-paced platforms like TikTok, trust and behavioral intention play a more critical role than functional value in driving engagement. Practically, the findings emphasize the need for platforms to enhance transparency and user control alongside algorithmic sophistication.