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

Year: 2025

Type: article

Abstract: 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.

Source: Journal of the Association for Information Systems

Authors: Ringeval, Mickael, Raymond, Louis, Paré, Guy, Wagner, Gerit

Institutions: HEC Montréal, Université du Québec à Trois-Rivières, University of Bamberg

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Quality education

Open Access status: green

OpenAlex ID: W6982358540

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