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Cited by 11Artificial Intelligence in Healthcare and EducationArtificial Intelligence in EducationInnovations in Medical Education

Impact of generative AI in medical education in India: a systematic review

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Mateen, Azfar, Kumar, Visesh, Singh, Ajay Kumar, Yadav, Berendra, Mahto, Mala, Hassan, Atiq, Nasir, Nazim·2025·Frontiers in Artificial Intelligence
DOI 10.3389/frai.2025.1704785PMC PMC12753906
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Abstract

Background: The advent of generative Artificial Intelligence (AI) has presented a fundamental change in the approach to medical education across the world. In India, where the medical education is facing a shortage in faculties and resources, generative AI (GenAI) has the potential of transforming this. This systematic review summarizes the current evidence on the impact, student readiness, and various ethical challenges and barriers of integration of AI into the medical curriculum. Methods: We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and searched published articles in PubMed and Google Scholar from 2020 to 2025. The search yielded 19,777 articles, from which 11 studies focusing on Indian medical students were selected. The findings of these studies were analyzed using Laurillard’s six learning modes to gain a comprehensive pedagogical understanding. Result: Our study revealed a significant finding: while high awareness and positive perception towards AI have been shown by Indian medical students, most of the students lack formal training. These selected studies show that the students mostly use generative AI for clearing doubts, making assignments, and self-directed learning, shifting from the ‘Acquisition’ to ‘Inquiry’ and ‘Production’ modes of Laurillard’s learning. Comparative Analysis showed that GenAI tools outperform students on standard exams, thus showing their potential. However, certain challenges also exist, including the risk of misinformation, over-reliance, potential decrease in critical thinking, and ethical concerns of data privacy. Conclusion: Indian medical students are enthusiastically adopting GenAI, but their engagement is mostly unstructured and informal. A significant gap exists between the readiness of the students and the medical institutions. To maximize the potential use of GenAI, our institutions have to develop a structured curriculum, invest in faculty training, and establish ethical guidelines. Teamwork between policymakers, educators, and researchers is the need of the hour so that our future physicians will be ready to integrate AI-enabled healthcare. Syestematic review registration: https://doi.org/10.17605/OSF.IO/2MJVK .

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  • Explicit instruction regarding AI use is ethically effective in enhancing professional ethics and critical thinking of students using AI-generated information.

    “Conversely, the studies indicate that explicit instruction regarding AI use is ethically effective in enhancing the professional ethics and critical thinking of the students using AI generated information [20,21].”

    From HOW AI TOOLS (LIKE CHATGPT/GEMINI) AFFECT CRITICAL THINKING IN NURSING STUDENTS. A SYSTEMATIC REVIEW (2026) · cites this paper as [20]

    In “Challenges and barriers to implementation” (page not provided), the review reports that students could not critically evaluate AI-generated output without basic AI training. In “Ethical considerations and concerns” (page not provided), it recommends embedding AI ethics in the curriculum. These passages support instruction as a need, but do not show that explicit instruction effectively improves students’ professional ethics or critical thinking. (LLM, conf=0.84)

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Research works printed but not linked: 4

  1. Breil B Fritz F Thiemann V Dugas M. Multidisciplinary education in medical informatics–a course for medical and informatics students MEDINFO 2010 2010 (pp. 581– 584). Amsterdam: IOS Press 20841753
  2. Moola S. Z. Munn Z. Tufanaru C. Aromataris E. Sears K. Sfetcu R.. (2020). “ Systematic reviews of etiology and risk” in JBI manual for evidence synthesis, Adelaide, Australia: The Joanna Briggs Institute. vol. 1, 217– 269.
  3. Rasouli S. Alkurdi D. Jia B. (2024). The role of artificial intelligence in modern medical education and practice: a systematic literature review. medrxiv. 26: 2024– 07.
  4. Sun L. Yin C. Xu Q. Zhao W. (2023). Artificial intelligence for healthcare and medical education: a systematic review. Am. J. Transl. Res. 15: 4820. 37560249 PMC10408516

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Authors
Mateen, A., Kumar, V., Singh, A. K., Yadav, B., Mahto, M., Hassan, A., & Nasir, N.
Affiliations
  • All India Institute of Medical Sciences, Patna (IN)
  • King Khalid University (SA)
Corresponding author
Nasir, Nazim
ORCID
Venue
Frontiers in Artificial Intelligence
Publisher
Frontiers Media SA
Published
2025-12-17
Volume
8
Pages
1704785-1704785
ISSN
2624-8212 (ISSN-L)
DOI
10.3389/frai.2025.1704785
PMC
PMC12753906
OpenAlex
W4417416460
Cited by
8
References
43
Citations by year
2026: 8
FWCI
0.47
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Artificial Intelligence (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
King Khalid University
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
Keywords
generative AI, medical education, Indian medical students, AI readiness, AI in curriculum, student perceptions of AI, exam performance, misinformation risk, overreliance on AI, critical thinking, data privacy, AI ethics, faculty training, artificial intelligence in healthcare

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