Medical students' and faculty members' perceptions and experiences of AI integration in health care practice and in medical curricula

A meta‐ethnographic review

Bibliographic Data

ID21517614
AuthorsSee Chai Carol Chan (0000-0003-1804-4741, Department of Primary Care and Public Health, School of Public Health Imperial College London London UK, corresponding author), Holly Young (0000-0002-3016-3893, Department of Primary Care and Public Health, School of Public Health Imperial College London London UK), Ravi Parekh (0000-0003-3610-6117, Department of Primary Care and Public Health, School of Public Health Imperial College London London UK)
Year2026
Volume60
Issue5
Pages492-504
Publication date2026-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueMedical Education (JOURNAL)
Journal identifiersISSN: 0308-0110 • E-ISSN: 1365-2923
PublisherWiley (PUBLISHER • GB)
DOI10.1111/medu.70071
PMID41194566
OpenAlexW4415950303
LanguageEN
References cited53

With the increasing adoption of artificial intelligence (AI), health care systems and medical education are undergoing significant changes. This review examines how medical students and faculty members perceive the opportunities and challenges of AI integration in both health care practice and medical curricula. A meta‐ethnographic approach, following the eMERGe guidelines, was used to synthesise qualitative research that focuses on perceptions and experiences among students and faculty members. Systematic searches were conducted across ERIC, Embase, PsycINFO, Web of Science and Medline databases, resulting in 1087 articles. Following an assessment of methodological robustness, 26 articles that met the inclusion criteria were included. The synthesis incorporated insights from 4380 students and 75 faculty members from at least 48 countries. There were differing experiences and perceptions of AI in health care and its integration in medical curricula. Four third‐order constructs were developed. “Implications on clinical practice” demonstrates how these participants view AI as a decision support tool and its impact on humanistic relationships and efficiency. “AI integrity” considers their perspectives on trust, accountability, inequity and the ethical use of AI technologies. “Educational implications and preparedness” examines preparation for the future workforce and approaches and barriers to integration in medical curricula. “Future workforce” considers participants' perspectives related to the evolving roles of health care professionals in an AI‐driven landscape. This review discusses the complex interactions between AI integration in health care practice and in medical curricula, revealing challenges and opportunities as perceived by students and faculty members. Although AI has the potential to revolutionise health care practices, significant educational gaps still hinder its effective implementation. This review advocates for curricula to better tailor to the specific needs of students and faculty members. It also emphasises the importance of incorporating ethical considerations and cross‐disciplinary collaboration to ensure readiness for an AI‐driven future in health care

Health care · MEDLINE · Perception · Qualitative research · Workforce · Artificial Intelligence in Healthcare and Education · Innovations in Medical Education · Simulation-Based Education in Healthcare

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