Too Caring to Be Real? Autonomy‐Supportive AI, Intimacy Gains, and Authenticity Loss
Thanh Tiep Le, Duy Khanh Phan, Bao Quoc Truong-Dinh · Psychology and Marketing · 2026
ABSTRACT Artificial intelligence‐mediated communication increasingly incorporates autonomy‐supportive and empathic language to foster emotionally meaningful consumer relationships, yet relational outcomes are not uniformly positive. This research introduces Perceived Autonomy Support in AI Communication (PAS‐AI) to explain why empathically framed AI simultaneously enhances perceived intimacy and, beyond a threshold, undermines perceived authenticity. Across a staggered field rollout, a longitudinal user‐level panel, and a between‐subjects experiment ( N = 207), we estimate causal and dynamic effects of PAS‐AI using event‐study Difference‐in‐Differences, System GMM, and experimental manipulation. Results show that moderate PAS‐AI reliably increases relational intimacy, reflected in greater conversational elaboration and voluntary re‐engagement. Yet when autonomy‐supportive cues become overly consistent or fluent, users report authenticity decline, describing AI responses as scripted or “too caring to be real.” Human‐in‐the‐loop escalation and transparent AI disclosure attenuate this decline, indicating that relational trust can be preserved through calibrated design. The findings reframe empathic AI as a matter of relational calibration rather than imitation. We distinguish throughout between PAS‐AI attr (message‐level linguistic features measured via NLP classifier) and PAS‐AI perceived (the user‐side psychological experience of autonomy support).