Key result
Public Health AI Framework enhances equitable practices by enabling personalized interventions and supporting crisis response.
Why the study?
While artificial intelligence is deployed across various public health functions, its application in leadership and management remains evolving.
The paper proposes a Public Health AI Framework to guide the ethical, equitable, and effective integration of AI into public health practice.
Offers a conceptual roadmap for ethical AI in public health; empirical validation required before practice or policy adoption.
Background: The emergence of artificial intelligence (AI) has triggered a global transformation, with the healthcare sector experiencing significant disruption and innovation. In current public health practice, AI is being deployed to power various aspects of public functions, including the assessment and monitoring of health, surveillance and disease control, health promotion and education, policy development and planning, health protection and regulation, prevention services, workforce development, community engagement and partnerships, emergency preparedness and response, and evaluation and research. Nevertheless, its use in leadership and management, such as in change management, process development and integration, problem solving, and decision-making, is still evolving. Aim: This study proposes the adoption of the Public Health AI Framework to ensure that inclusive data are used in AI development, the right policies are deployed, and appropriate partnerships are developed, with human-relevant resources trained to maximize AI potential. Implications: AI holds immense potential to reshape public health by enabling personalized interventions, democratizing access to actionable data, supporting rapid and effective crisis response, advancing equity in health outcomes, promoting ethical and participatory public health practices, and strengthening environmental health and climate resilience. Achieving this goal will require a deliberate and proactive leadership vision, where public health leaders move beyond passive adoption to collaborate with AI specialists to co-create, co-design, co-develop, and co-deploy tools and resources tailored to the unique needs of public health practice. Call to action: Public health professionals can co-innovate in shaping AI evolution to ensure equitable, ethical, and value-based public health.
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Oleribe et al. (2026) conducted a review in Public health practice. Public Health AI Framework was evaluated. Adoption of the Public Health AI Framework is proposed to ensure inclusive data, appropriate policies, and partnerships to maximize AI potential in reshaping public health practice.
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