Artificial intelligence (AI) systems are increasingly integrated into daily life, not only as tools but also as social partners that people may turn to for interaction and support. This raises important questions about whether, how, and why individuals form attachment-like bonds with AI, and what psychological implications such attachments may carry. Across five studies involving 1259 participants from Singapore and the US, the current work developed and validated the AI Attachment Scale and investigated the dispositional and motivational factors that predict attachment to AI, as well as its emotional and social outcomes. The AI Attachment Scale displayed strong psychometrics properties, including a reliable three-factor structure comprising of emotional closeness, social substitution, and normative regard subscales, strong convergent validity and discriminant validity, and high test–retest reliability. Examination of correlates revealed that time spent on AI, particularly for socioemotional purposes, was a strong predictor of AI attachment. Individuals higher in social anxiety, loneliness, and anxious attachment were also more likely to turn to AI as a compensatory surrogate when human connections were lacking. These tendencies were further linked to dispositional needs that AI fulfils, including closure through predictability, relatedness through socioemotional presence, and competence through affirming feedback. At the same time, stronger AI attachment is associated with heightened positive affect and life satisfaction, suggesting that AI attachment may satisfy the psychological needs and provide meaningful emotional benefits. These findings provide the first validated measure of attachment to AI and offer a foundation for future research on its psychological and societal implications.
Kasturiratna et al. (Wed,) studied this question.
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