Governing the rise of AI in healthcare: A comparative governance document and implementation implications across five...

As AI increasingly reshapes healthcare delivery and innovation, global health systems face urgent imperatives to govern its development, deployment.

Drawing on 43 regulatory and strategic documents in five jurisdictions, the study systematically assessed convergences and divergences in national AI strategies, risk classification schemes, software-as-a-medical-device (SaMD) frameworks, ethical oversight, and cross-border data policies.

Policy and regulatory documents on AI in health (2017-2025) were collected from health authorities, regulatory agencies, and multilateral platforms. A structured 20-item framework covering six domains was applied to enable systematic cross-jurisdictional comparison of strategic vision, regulatory rigor, ethics, implementation support, global alignment, and medical device governance.

Increasing convergence around core principles such as transparency, accountability, and human-centric AI, particularly through the influence of international norms. However, significant divergence remained in regulatory maturity, enforcement mechanisms, reimbursement pathways and implementation capabilities. While jurisdictions like Singapore and China exhibited centralized, state-led coordination, others like the US reflected pluralistic, agency-driven models. Economic incentives, workforce readiness programs, and post-market surveillance systems also varied widely.

The study concluded with five recommendations for advancing AI governance: strengthening interagency coordination, harmonizing regulatory frameworks, embedding equity and transparency in data infrastructure, supporting institutional readiness and fostering international collaboration.