Artificial Intelligence in Health Professions Education: A Bibliometric Analysis of Educational Implementation, Learning Outcomes and Pedagogical Challenges

The rapid proliferation of artificial intelligence in health professions education has generated substantial scholarly interest, yet comprehensive understanding of research patterns and emerging pedagogical frameworks remains limited. This bibliometric analysis examines AI educational research spanning 2023-2025, following PRISMA 2020 guidelines across four major databases. From 916 initial studies, rigorous criteria yielded 156 high-quality articles analyzed using quantitative bibliometric techniques and qualitative content synthesis. Results reveal exponential growth with 67.7% annual increase, totaling 185 publications with 5,257 citations averaging 28.42 per article. Three critical dimensions emerge: pedagogical implementation challenges encompassing technical infrastructure and faculty development barriers; learning outcomes enhancement through intelligent tutoring achieving 90% efficiency improvements; and educational ethics frameworks addressing algorithmic transparency and equity. Exceptional international collaboration (84.3%) and open access rates (89.7%) position AI educational research as mature discipline transforming health professions training through evidence-based pedagogical innovation. Received: 15 October 2025 / Accepted: 27 October 2025 / Published: January 2026