AI in Medical Education: Disruption or Enhancement?

Written by Gabriela Benderz, Learna | Diploma MSc - Medical Education Tutor
*This blog post has been authored by one of our tutors. The perspectives and insights shared here are their own. *

Artificial intelligence (AI) is no longer a distant concept in medical education - it is a rapidly expanding tool reshaping how healthcare professionals are trained and assessed. From intelligent tutoring systems and virtual patients to AI-generated feedback and decision support tools, the integration of AI into educational settings offers potential enhancements in teaching efficiency, personalisation, and learner engagement. However, these advances are accompanied by critical ethical, pedagogical, and clinical considerations.

Current Integration and Gaps in Curriculum

A recent scoping review by Chan et al. (2024) published in BMC Medical Education analysed the use of AI in undergraduate medical education. It found that while AI tools such as machine learning and natural language processing are increasingly used to support decision-making and automate assessments, most implementations lack pedagogical grounding and do not adequately address the development of students’ digital literacy or ethical reasoning. This indicates a gap between technological innovation and curriculum readiness.

Institutional Innovations: Harvard’s Case Study

Harvard Medical School has taken a proactive stance by embedding foundational AI concepts into their curriculum through a month-long course for new students. The course emphasises not only technical understanding but also the implications of AI on clinical reasoning, communication, and patient care (Kesselheim, 2024). This approach reflects a growing awareness that AI literacy is becoming as essential as traditional medical knowledge.

Challenges to Effective Integration

Despite its promise, integrating AI into education is not without challenges. A systematic review by Lee et al. (2023) highlighted limitations such as bias in training data, lack of transparency in algorithm design, and concerns about student over-reliance on AI-generated answers. These issues may hinder the development of clinical judgement if not addressed within the learning environment.

Maintaining Humanism in a Digital Era

Clinically, AI can enhance diagnostic accuracy and efficiency, but it should complement - not replace - human expertise. Thus, educators must strike a balance: developing AI-literate graduates who can critically interpret AI outputs while maintaining empathy and ethical sensitivity in clinical care.

Conclusion

To ensure AI enhances rather than disrupts medical education, its implementation must be accompanied by faculty development, robust evaluation, and learner-centred design. As AI continues to evolve, so must the curricula that prepare our future clinicians.

References
Chan, Y., Gupta, S., & Moore, K. (2024). Mapping the use of artificial intelligence in medical education: A scoping review. BMC Medical Education, 24(1), 102. https://doi.org/10.1186/s12909-024-05760-0
Kesselheim, J. (2024). How generative AI is transforming medical education. Harvard Medicine Magazine. Retrieved from https://magazine.hms.harvard.edu/articles/how-generative-ai-transforming-medical-education
Lee, S. H., Noh, S., & Abbas, M. (2023). Artificial intelligence in medical education: Global situation, effects and challenges. Education and Information Technologies, 29, 4561–4579. https://doi.org/10.1007/s10639-023-12009-8
Further Reading
Wartman, S. A., & Combs, C. D. (2023). Medical education must move from the information age to the age of artificial intelligence. Academic Medicine, 98(2), 165–170. https://doi.org/10.1097/ACM.0000000000004811
Paranjape, K., Schinkel, M., Nannan Panday, R. S., Car, J., & Nanayakkara, P. W. B. (2019). Introducing artificial intelligence training in medical education. JMIR Medical Education, 5(2), e16048. https://doi.org/10.2196/16048
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94

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