Medical students' and faculty members' perceptions and experiences of AI integration in health care practice and in medical curricula: a meta-ethnographic review
Author(s)
Chan, See Chai Carol
Young, Holly
Parekh, Ravi
Type
Journal Article
Abstract
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.
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.
Date Issued
2026-05-01
Date Acceptance
2025-10-02
Citation
Medical Education, 2026, 60 (5), pp.492-504
ISSN
0308-0110
Publisher
Wiley
Start Page
492
End Page
504
Journal / Book Title
Medical Education
Volume
60
Issue
5
Copyright Statement
© 2025 The Author(s). Medical Education published by Association for the Study of Medical Education and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/41194566
Subjects
ARTIFICIAL-INTELLIGENCE
Education & Educational Research
Education, Scientific Disciplines
Health Care Sciences & Services
Life Sciences & Biomedicine
Science & Technology
Social Sciences
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2025-11-05