Mind the (widening) gap: why public health must engage with AI now

This commentary aims to highlight the opportunities and challenges that Artificial Intelligence (AI) presents for public health.

Narrative commentary and conceptual analysis.

The commentary draws on material developed for a forthcoming book by the European Observatory on Health Systems and Policies. Sources were selected to highlight both the potential and the limitations of AI integration at population levels, with a focus on equity, governance, and implementation. The analysis is informed by established public health principles: prevention, systems thinking, and the social determinants of health.

AI applications in public health go beyond process automation and operational efficiency. By integrating and processing diverse, multi-modal data sources, its implementation presents opportunities to understand the wider determinants of health at a more nuanced level and identify populations at risk with greater precision. Additionally, AI has the potential to help understand and support behaviour change in sophisticated ways, enhance disease surveillance and modelling, and enable more targeted and responsive public communication and engagement strategies. However, there are several barriers to realise AI's potential in public health, including system fragmentation, data access limitations, resource constraints, implementation challenges, workforce readiness gaps, and technological limitations such as bias and generative AI "hallucinations".

Without deliberate engagement, AI risks reinforcing existing inequities. Practical steps for action include embedding AI training in public health education, building multidisciplinary teams, investing in data infrastructure, and ensuring participatory approaches. AI will continue to shape public health systems, whether or not public health professionals engage. We argue that the public health community is both uniquely positioned and ethically obligated to engage proactively with AI.