How Consumers Evaluate Human, AI, and Hybrid Therapists: Psychological Pathways to Expected Service Satisfaction

As generative artificial intelligence becomes prominent in digital therapy, understanding how consumers evaluate human, AI, and hybrid therapists is increasingly important. Drawing on insights from signaling, construal level, stimulus‐organism‐response, and perceived risk research, this paper examines how therapy delivery mode shapes expected service satisfaction through capabilities‐based, relational‐based, and risk‐based pathways. Across two experiments, consumers reported higher expected service satisfaction for human therapists than for AI or hybrid (AI/human) therapists. In Study 1 (N = 200), this effect was partially mediated by perceived therapist competence, perceived therapist expertise, and psychological closeness. In Study 2 (N = 195), the preference for human over hybrid therapists was fully mediated by skepticism of the therapist, while privacy concerns and psychological closeness were not significant mediators. These findings contribute to theory on technology‐mediated service evaluation by showing that consumer responses depend on inferred capability, relational connection, and skepticism, with implications for consumer protection, transparency, and responsible digital therapy design.