A mediated investigation into the impact of personalised content recommendations on experiential outcomes with Snapchat's [My AI] chatbot

Abstract

This study investigates the associative pathways between Personalised Content Recommendations (PCR) and two critical experiential outcomes: user satisfaction and engagement. By adopting an extended Unified Theory of Acceptance and Use of Technology (UTAUT2) as a mediating framework, we examine how algorithmic individualisation translates into psychological value within Snapchat’s [My AI] chatbot. Data from a survey of 698 active users of Snapchat’s My AI reveal that while PCR associates positively with both satisfaction and engagement, the underlying mechanisms are non-linear and context-dependent. The findings uncover a theoretical paradox, noting that although hedonic motivation and habit consistently drive positive outcomes, utilitarian factors such as effort expectancy and facilitating conditions exhibit complex, and at times negative, associations with the user experience. These results suggest that in social-conversational AI contexts, traditional frictionless design may inadvertently diminish active user engagement. By identifying these divergent pathways, the study challenges conventional adoption models and provides an empirical baseline for understanding the social-logic of artificial humans in social media. These insights offer platform architects a strategic roadmap for balancing algorithmic precision with the psychological nuances of AI-human companionship.

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