Beyond willingness: unpacking pharmacists’ adoption of AI-driven clinical decision support systems through an extended UTAUT framework

Objective Against the backdrop of the rapid integration of artificial intelligence–based clinical decision support systems (AI-CDSSs) into pharmacy practice, the actual acceptance of these systems by pharmacists and the underlying psychological and organizational mechanisms remain inadequately understood. Grounded in the unified theory of acceptance and use of technology (UTAUT), this study examines the factors influencing hospital pharmacists’ intention to use AI-CDSS and their subsequent usage behavior in China. Methods The UTAUT framework was augmented by incorporating two additional constructs: technology trust and perceived risk. A cross-sectional survey was conducted using a structured questionnaire, and structural equation modeling (SEM) was employed to analyze the hypothesized relationships among variables. Results The results indicated that performance expectancy ( β = 0.308), effort expectancy ( β = 0.274), and technology trust ( β = 0.252) exerted significant positive effects on behavioral intention, whereas perceived risk showed a significant negative influence ( β = −0.164). Social influence was not a significant predictor. Behavioral intention ( β = 0.676) and facilitating conditions ( β = 0.326) were both direct predictors of usage behavior. Conclusion The acceptance of AI-CDSS among hospital pharmacists is primarily driven by perceptions of performance benefits, ease of use, and trust in the technology. These findings underscore the importance of enhancing the clinical value, algorithm transparency, and organizational support for AI-CDSS implementation. This study extends the theoretical applicability of UTAUT in high-stakes AI-mediated clinical environments.