A study of medical students’ perception of the risk of future job displacement and adaptive behaviors in the context of artificial intelligence

Abstract Against the backdrop of rapid advances in artificial intelligence (AI) technology, an increasing number of jobs are facing significant challenges, particularly in the healthcare sector. The development of AI not only puts forward new career requirements for healthcare practitioners, but also has an impact on the career perception of medical students. This study aims to investigate medical students’ perceptions of the risk of occupational substitution by AI and to examine the adaptive behaviors they employ in response to this perceived risk.A total of 682 valid responses were obtained through random sampling. Descriptive and correlation analyses were conducted using SPSS 27.0, while the structural model was tested through path analysis in AMOS 29. The results show that social support significantly enhances perceived usefulness ( P < 0.001), and both social support and self-efficacy positively influence perceived ease of use (β = 0.459, β = 0.425, P < 0.001). Perceived ease of use strongly predicts perceived usefulness (β = 0.662, P < 0.001). Response cost exerts a small but significant negative effect on behavioral intention (β =−0.081, P = 0.034), whereas perceived usefulness, perceived ease of use, perceived severity, perceived vulnerability, and response efficacy all positively contribute to behavioral intention ( P < 0.001). Behavioral intention was significantly positively associated with actual adaptive behavior (β = 0.875, P < 0.001). The findings identify key determinants of medical students’ adaptive behaviors amid AI-driven professional uncertainty. The study underscores the need for medical schools to strengthen digital literacy training, cultivate human-AI collaboration skills, and provide psychological support to help students navigate technological transformation in healthcare.