As AI chatbots become integrated into various aspects of everyday life, users increasinglyform parasocial relationships with their digital companions. To understand how such relationshipsemerge, we examined how perceived human-likeness fosters parasocial attachment to AIchatbots. We test a relationship process model in which human-likeness—conceptualized as ameta-factor comprising anthropomorphism, authenticity, and social presence—promotesparasocial attachment via user gratifications and interaction behavior. In a preregistered survey of598 chatbot users from 64 countries, structural equation modeling showed that perceived humanlikenesswas a strong predictor of parasocial attachment. As predicted, this effect was partiallymediated by increased gratifications and interaction. Additional qualitative responses illustratedhow chatbots provide emotional support, role-play, and productivity benefits, alongside concernsabout dependence, social withdrawal, inappropriate behavior, and privacy. Together, the findingsidentify human-likeness, gratifications, and interaction as central drivers of parasocial attachmentto AI chatbots.
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