Vol. 2026 No. 1 (2026): 2026 Continuous Issue
Articles

A Historically Informed Developmental Trajectory for Medical Education Reform in the Age of AI

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  • Angellar Manguvo,
  • Benford Mafuvadze
Angellar Manguvo
University of Missouri-Kansas City
Benford Mafuvadze
Unaffiliated
Bio
DOI: https://doi.org/10.46787/ijaipil.v2026i1.6964

Published 2026-03-24

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Keywords

  • Curriculum Transformation, Pedagogical Change, Faculty Preparedness, AI, Medical Education, Cognitive Offloading

How to Cite

Manguvo, A., & Mafuvadze, B. (2026). A Historically Informed Developmental Trajectory for Medical Education Reform in the Age of AI. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2026(1). https://doi.org/10.46787/ijaipil.v2026i1.6964

Copyright (c) 2026 Angellar Manguvo, Benford Mafuvadze

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Artificial intelligence (AI) is reshaping how biomedical knowledge is accessed, synthesized, and applied, raising important questions about the cognitive competencies medical education should cultivate. Although these concerns appear new, educational institutions have previously confronted similar disruptions when emerging technologies altered relationships among knowledge, expertise, and learning. Using a historical-comparative design informed by institutional adaptation theory, this article analyzes recurring patterns in educational responses to technological innovation across six dimensions: institutional resistance, pedagogical positioning, faculty gatekeeping, curricular reform, assessment transformation, and equity of access. The analysis suggests that technological integration in education tends to proceed through identifiable stages, beginning with resistance and concern about skill erosion, followed by supplemental integration, pedagogical reorientation, and eventual curricular adaptation. Based on these patterns, the article proposes a developmental trajectory model for integrating AI into professional education and suggests that medical education currently stands between supplemental integration and early pedagogical reorientation. Meaningful AI integration will require curricular reform, revised assessment models, faculty development, and governance frameworks for responsible use.

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