BACKGROUND:
Advances in analytics, artificial intelligence (AI), and decision support systems are reshaping how public health systems generate insight, allocate resources, and support individual clinical decisions. When effectively governed and implemented, these tools can improve surveillance, policy decision-making and service delivery, particularly in complex and resource-constrained settings. However, without explicit attention to equity, inclusion, ethics, and cybersecurity, digital innovations risk exacerbating existing health and data inequities. There is a growing need to equip public health professionals with practical, context-aware approaches to responsible analytics and AI adoption.

METHODS:
This organized session will be delivered as a one-hour interactive workshop combining brief expert presentations and participatory exercises. The session will draw on real-world public health use cases and examples to explore how analytics and AI are being translated into operational decision support. Key methodological components include a guided reflection on the current context, practical in-person demonstration of use cases, and structured dialogue on governance, ethics, and cybersecurity. Emphasis will be placed on equity-by-design principles, inclusive data practices, and sustainability across diverse health information ecosystems.

RESULTS:
Participants will develop a shared understanding of how analytics and AI can support equitable public health decision-making across local, national, and cross-border contexts. The session will surface practical enablers and barriers to implementation, including data quality, institutional capacity, governance frameworks, and trust. Attendees will leave with concrete considerations and frameworks for applying decision support tools responsibly within their own systems, informed by lessons from diverse public health settings.

CONCLUSIONS:
Analytics, AI, and decision support hold significant potential to advance public health outcome, but only if implemented with deliberate attention to equity, inclusion, and sustainability. This session contributes to building the skills, shared language, and cross-disciplinary understanding required to ensure digital and AI-driven public health innovations strengthen, not fragment, health systems globally.