Work

Challenges and barriers to integrating artificial intelligence in medical education and healthcare: a qualitative exploration

Year: 2026

Type: article

Abstract: Background & Objective: Artificial Intelligence (AI) is reshaping healthcare delivery and medical education.Understanding faculty experiences with the challenges of AI implementation is essential for developing effective solutions.This study therefore aims to identify barriers to AI utilization from the perspective of medical sciences university faculty. Materials & Methods:This qualitative study employed conventional content analysis, conducted from November 17, 2024, to January 25, 2025, in Fars Province, southern Iran.Participants were selected through purposeful sampling.Semi-structured, in-depth individual interviews were carried out with 21 faculty members who held either hands-on experience with AI or theoretical knowledge of its applications in educational and clinical settings.Data analysis followed the framework proposed by Graneheim and Lundman.Results: Three main themes emerged.The first, individual challenges, encompassed limited knowledge and skills alongside negative attitudes and resistance toward AI.The second, organizational challenges, was reflected in inadequate facilities and infrastructure, further compounded by the absence of clear, comprehensive guidelines for AI implementation.The third, ethical challenges, surfaced concerns spanning both medical education and research. Conclusion:The findings underscore that fully realizing AI's transformative potential in medical sciences demands the simultaneous and coordinated strengthening of individual competencies, institutional capacities, and ethical governance.Only through an integrated, systems-oriented approach can existing barriers be effectively dismantled and broader institutional acceptance of AI within healthcare settings meaningfully advanced.

Source: Journal of Medical Education Development

DOI: 10.66224/edcj.19.3.30