Identifying Necessary Conditions for AI Adoption: Medical Students’ Perspectives Across the COVID-19 Timeline

The integration of artificial intelligence health technologies (AIHTs) into medical practice depends on the readiness of future physicians. This study examines medical students’ behavioral intentions to adopt AIHTs across three timeframes – pre-, peri-, and post-COVID-19 – using Necessary Condition Analysis (NCA). Unlike traditional methods, NCA identifies essential, non-compensable factors influencing adoption. Findings reveal that belief in AIHTs’ role in medicine is a persistent necessary condition, while the perceived importance of AIHTs in the curriculum emerges as critical post-COVID-19. Despite increased familiarity and experimentation with AIHTs, these alone are insufficient to drive adoption. These insights underscore the need for medical curricula to emphasize AI literacy, hands-on training, and interdisciplinary collaboration. By identifying key conditions for AI adoption, this study informs educators and policymakers on preparing medical students for a technology-driven healthcare landscape.