From Trust to Emotion Toward Loyalty A Structural Model of AI-Driven Customer Engagement

This study investigates the antecedents and outcomes of customer engagement in AI-driven digital platforms, focusing on the roles of Digital Trust, Content Engagement, Content Engagement AI, Emotion, and Platform Familiarity. Despite increasing activity on social media, previous findings indicate that user engagement remains largely superficial and unsustainable. Thus, this study aims to explore whether satisfaction derived from AI personalization and emotional connection can lead to long-term digital relationships. Using a purposive sampling method, data were collected from 430 respondents, predominantly young users aged 12–27 years in Jakarta and surrounding areas, during April 2025. Respondents were active users of social media platforms who engaged with influencer-generated content. Structural Equation Modeling using Partial Least Squares (SEM-PLS) was applied to analyze the relationships among variables. The results confirm that Digital Trust significantly drives Content Engagement, Emotion, and Customer Engagement, while Platform Familiarity enhances trust. Moreover, AI-driven personalization and emotional resonance play pivotal mediating roles in shaping deeper, sustainable engagement. This study contributes theoretically by elucidating the multidimensional process of engagement in AI-mediated contexts and practically by guiding marketers and policymakers to design more authentic and trustworthy digital ecosystems. Keywords: Customer Engagement, Digital Trust, Content Engagement AI, Emotion, Platform Familiarity