Mapping National Governance of AI for Health: Protocol for a Global Scoping Review

Area of Science:

• Health Informatics
• Artificial Intelligence Governance
• Public Health Policy

Background:

• Artificial intelligence (AI) is transforming healthcare, from diagnostics to clinical decision support.
• Significant governance challenges exist, including bias, privacy risks, and access inequities.
• National AI strategies are proliferating, but global governance is fragmented, with limited evidence on policy effectiveness.

Purpose of the Study:

• To characterize national approaches to AI governance in health.
• To assess alignment of national policies with established governance frameworks.
• To identify implementation challenges and enabling factors for AI in health.

Main Methods:

• Scoping review following Arksey and O'Malley framework and PRISMA-ScR guidelines.
• Searched 6 databases and gray literature (Jan 2015-Apr 2025) for national policies, empirical analyses, and reports.
• Data extraction guided by WHO AI ethics guidance and Global Initiative on AI for Health priorities (ethics, regulation, implementation, operations).

Main Results:

• Systematic search identified 21,278 records, with 149 sources meeting inclusion criteria after screening.
• Initial screening involved over 20,000 titles and abstracts from diverse databases.
• Full data extraction and quality assessment are ongoing, with finalization by June 2026.

Conclusions:

• This review protocol addresses a critical evidence gap in AI governance for health.
• It provides a comprehensive mapping of national AI governance policies against established frameworks.
• The findings will inform evidence-based, equitable, and context-specific governance for safe AI integration in health systems.