From compliance to competence: a multi-level model for AI governance in undergraduate medical education
AI's fast-paced irruption in medicine and education has challenged undergraduate medical colleges, with institutions documenting policies emphasizing immediate conduct restrictions, while strategic oversight, infrastructure and evaluation remain less consistently developed. We propose a multi-level framework for AI governance in undergraduate medical education based on accountability, competence and co-responsibility across institutions, educators and students, designed to turn a fast-evolving technology from a threat into an opportunity for collective progress.
Authors
- Lourdes Estefanía Barón-Miras (ORCID: https://orcid.org/0000-0003-2574-1780)
- Isabel Torá‐Rocamora (ORCID: https://orcid.org/0000-0002-5946-4569)
- Juan José Gualda-Gea (ORCID: https://orcid.org/0009-0008-4927-616X)
- Marta Aldea (ORCID: https://orcid.org/0000-0001-7389-8075)
- Gemina Santana
- Alberto L. García‐Basteiro (ORCID: https://orcid.org/0000-0002-2038-5505)
- Jaume Grau
- Andrés Prat Marín
- Guillermo Mena
- Maria Jesús Bertran
- Antoni Trilla
Institutions
- Maresme Health Consortium (ES)
- Manhiça Health Research Centre (MZ)
- Barcelona Institute for Global Health (ES)
- Universitat de Barcelona (ES)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-10-14
- DOI
- https://doi.org/10.1038/s41746-026-03390-y
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00