The World Health Organization (WHO) has published a paper on how health AI could reshape policy-making, setting out both risks and opportunities.
The paper examines how AI could affect the way health problems are defined, policy options are designed and the impact of decisions is assessed.
It says AI could help policymakers analyse larger datasets, retrieve evidence faster and model possible outcomes more quickly.
However, the paper also warns that poorly governed AI could weaken the evidence base used to make health policy.
Dr Alain Labrique, director of data, digital health, analytics and AI at WHO, said: “The policy conversation on AI has focused on clinical care.
“This paper redirects attention to where the evidence base is actually being shaped: how problems are defined, how options are designed, how impact is assessed.
“Member States need a common framework for governing AI across that entire cycle. This paper provides a starting point.”
The paper was developed jointly by WHO’s Department of Data, Digital Health, Analytics and AI and its Department of Science for Health.
It is intended for policymakers, regulators, health managers and AI developers.
The paper maps AI’s role across the policy cycle, including understanding the problem, designing solutions, and achieving impact through implementation, monitoring and adjustment.
It says AI brings distinct opportunities and risks at each stage.
Data bias could distort how health problems are understood, while over-optimising measurable targets could narrow policy design.
Digital divides and cybersecurity weaknesses could undermine implementation, while subtle bias in monitoring tools could gradually shift policies away from their original goals.
The paper also highlights the risk of epistemic injustice.
Epistemic injustice means some forms of knowledge are treated as less valuable than others.
In health policy, this could mean AI systems favouring data-rich evidence while sidelining lived experience, local expertise, Indigenous knowledge and community-based insight.
WHO said the paper takes a practical approach by identifying where existing evidence-informed policy tools and AI governance frameworks already converge.
These areas include transparency, participatory engagement, rights protection and risk-based oversight.
The paper draws on existing frameworks including WHO AI ethics guidance, the GRADE Evidence-to-Decision framework, FAIR data principles and OECD AI Principles.
Sameer Pujari, who leads AI in WHO’s Department of Data, Digital Health, Analytics and AI, said: “AI is entering health policy work faster than most institutions have built the capacity to govern it.
“This paper offers Member States practical guidance for that gap: it maps AI’s place across the policy cycle and draws on governance frameworks many countries are already using, so the work of adaptation builds on what is in place rather than starting from scratch.”
The paper recommends algorithmic impact assessments and technology readiness reviews before AI tools are deployed.
An algorithmic impact assessment checks how an AI system could affect people, services or decisions before it is used.
Technology readiness reviews assess whether a tool is mature, safe and suitable for the setting in which it will be used.
Once AI tools are in use, WHO calls for living evidence workflows that pair automated retrieval with human verification.
Living evidence workflows are systems that keep evidence up to date as new information becomes available.
The paper also recommends human-in-the-loop decision gateways and multidisciplinary oversight panels combining domain, methods and ethics expertise.
Human-in-the-loop means people remain involved in checking, interpreting and approving decisions supported by AI.
WHO said a central principle of the paper is that AI should augment human judgement, not automate it.
It says humans must remain responsible for framing questions, judging the quality of evidence, interpreting results in context and weighing ethical considerations.
Dr Tanja Kuchenmüller, unit head, research and ethics ecosystem strengthening in WHO’s Department of Science for Health, said: “Evidence-informed policy-making has always depended on judgement, context and a plurality of voices.
“AI can extend our reach into larger datasets, living evidence syntheses, and faster scenario modelling, but it should strengthen human deliberation, not replace it.
“This paper aims to help policy-makers harness that potential while preserving the transparency, inclusiveness and trust that underpin evidence-informed policy-making.”
WHO said the discussion paper is intended as a foundation for continued dialogue with Member States, researchers, developers and civil society as AI capabilities and the contexts in which they are applied continue to evolve.
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