Artificial intelligence (AI) is increasingly shaping evidence-informed policy-making (EIP) in health by enabling faster analysis, synthesis and use of large and diverse data sources across the policy cycle. This discussion paper examines the intersection of AI and EIP, outlining how AI can support problem identification, policy design and implementation through enhanced data integration, predictive modelling, scenario simulation and adaptive feedback. It emphasizes that AI augments rather than replaces human judgement, while highlighting its potential to expand the evidence base and support more timely, responsive and iterative decision-making in complex health contexts.