Accepted for/Published in: JMIR Medical Education
Date Submitted: May 20, 2025
Date Accepted: Oct 28, 2025
What are the opportunities and challenges of using AI in medical education in Vietnam?
ABSTRACT
Artificial intelligence (AI) is reshaping medical education globally through personalized learning platforms, virtual simulations, automated assessments, and data-driven decision-making. However, the integration of AI into medical education remains uneven, particularly in low- and middle-income countries. In Vietnam, despite increasing interest, AI implementation in medical training is hindered by structural, technological, and cultural challenges. This viewpoint aims to explore the current landscape of AI in Vietnamese medical education, assess its opportunities and limitations, and offer actionable recommendations for future integration. Our work highlights areas of potential innovation and examines contextual barriers through thematic analysis. AI has the potential to address critical issues in Vietnamese medical education, including high student-to-faculty ratios, limited clinical exposure, and uneven digital resources. Opportunities include adaptive learning, clinical simulations, automated assessment, and institutional analytics. However, widespread implementation is challenged by limited AI literacy among students and educators, inadequate infrastructure, particularly in rural institutions, unclear regulatory frameworks on ethics and data privacy, and resistance to pedagogical change. The absence of national strategies and standardized curricula further exacerbates these gaps. To harness the benefits of AI in medical education, Vietnam must adopt a strategic and inclusive approach. Key priorities include integrating AI literacy into medical curricula, investing in digital infrastructure, training faculty, developing ethical guidelines, and fostering cross-sector collaboration. Strengthening these foundations will support equitable, future-ready medical education aligned with global trends in digital health.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.