Perspective: advancing public health education by embedding AI literacy

Abstract

Artificial intelligence (AI) fundamentally reshaping public health practice, yet formal training in AI literacy remains scarce in most public health educational programs. The rapid emergence of large language models and other AI-driven technologies such as computer vision, predictive analytics, and natural language processing tools—used in applications ranging from epidemiological modeling and policy analysis to real-time health communication—highlights the urgent need to bridge a persistent knowledge gap in structured, competency-based AI training for public health students and professionals. This Perspective article introduces the growing role of AI in public health, examines challenges in diverse global settings, outlines current gaps in AI literacy training, and proposes a framework for integrating AI competencies into undergraduate, graduate, and continuing public health curricula. In doing so, it emphasizes the importance of equipping tomorrow's public health workforce with the ethical, technical, and critical-thinking skills needed to harness AI's potential to improve health outcomes and support public health practice across diverse and underserved communities.