Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development

Background: Artificial intelligence (AI) has catalyzed profound shifts in public health education, compelling institutions to explore innovative methods to prepare a digitally competent and resilient workforce. AI has emerged as a transformative tool, enabling adaptive, personalized, and scalable learning experiences. However, the long-term implications and equity considerations of AI integration in education remain underexplored. Aim: This scoping review aimed to map the existing literature on the role of AI in public health education, focusing on its impact on workforce competency development and associated challenges. Methods: Following Arksey and O'Malley's framework with enhancements from Levac et al., a comprehensive literature search was conducted across major databases, including PubMed, Scopus, and IEEE Xplore. Eligible studies, published from January 2015 to May 2025, were screened using PRISMA-ScR guidelines. Data were extracted and thematically analyzed to identify patterns, competencies addressed, and ethical or institutional considerations. Results: A total of 26 studies were included. Key themes included the transformation of pedagogical practices through AI-powered simulations and adaptive platforms, the rise of AI-specific and digital literacy training, institutional disparities in readiness, and significant ethical concerns around algorithmic bias and equitable access. Interdisciplinary collaboration and curriculum reform were identified as pivotal in sustaining AI integration. Conclusion: AI holds great promise in enhancing public health education, but its integration should be approached with attention to equity, institutional capacity, and ethical responsibility. Strategic policy, curriculum reform, and ongoing research are critical to fostering a workforce equipped for future public health challenges.