Abstract

Background: Persistent health inequities disproportionately affect marginalized and underserved communities. Public Health Nurses (PHNs) are instrumental in bridging these gaps through localized, community-based interventions. With the advent of Artificial Intelligence (AI), new possibilities have emerged for more accurate identification and resolution of health disparities. Objective: This article examines the evolving role of AI in public health nursing and proposes a structured framework for the equitable integration of AI to address community health disparities. Methods: A narrative review approach was used to synthesize findings from national health datasets, global pilot programs, and current academic literature related to AI in healthcare, public health disparities, and nursing practice. Results: The use of AI in nursing and public health includes applications such as predictive analytics, personalized care planning, health education via chatbots, and wearable health monitoring. However, AI tools often carry risks of bias, lack of transparency, and inequitable deployment, especially in low-resource settings. Conclusion: AI, when ethically and inclusively implemented, can enhance the ability of PHNs to identify, address, and monitor community health disparities. A community focused, PHN-led framework is essential for AI to serve as a tool for equity rather than exclusion.

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