Healthcare systems are racing to adopt artificial intelligence, but they're doing so without a clear map of the rules governing how these tools should work. That's the problem a Cornell University senior set out to solve by building the Health and AI Policy Index (HAPI), a public database that tracks emerging healthcare AI policies, legislation, and governance efforts across jurisdictions.

Why Is Healthcare AI Governance So Fragmented?

As AI rapidly enters clinical care, policymakers and health systems face a fundamental challenge: there is no single comprehensive framework governing how these technologies should be deployed. Instead, stakeholders must navigate what Will Moss, a policy analysis and management major at Cornell's Brooks School, calls "a complex patchwork of policies emerging from a wide range of regulators and institutions". This fragmentation creates confusion about patient safety, provider accountability, and equity considerations.

Moss developed HAPI to address this gap directly. The interactive platform allows users to explore policies by jurisdiction, stakeholder group, and impact level, while also providing summaries, implementation considerations, and trend analyses. "HAPI was designed to make healthcare AI governance more accessible and understandable," Moss explained. "Right now, policymakers, researchers, and health systems are all trying to navigate a rapidly changing regulatory environment. I wanted to create a centralized resource that helps people follow what's happening across states in real time".

What Does HAPI Actually Track?

The database catalogs a broad spectrum of regulatory approaches, including legislation, executive actions, regulatory guidance, and voluntary frameworks related to artificial intelligence in healthcare. This work was recently published in npj Digital Medicine, a peer-reviewed journal, giving the project academic credibility alongside its practical utility.

Moss's background informed the project's design. He gained firsthand exposure to how health AI is evaluated, implemented, and governed through his work at the Windreich Department of Artificial Intelligence and Human Health at Mount Sinai. His previous internships in federal and state government affairs also helped develop the policy analysis and stakeholder engagement skills needed to navigate complex regulatory environments.

How Can Organizations Use HAPI to Navigate AI Governance?

• Track Emerging Policies: Monitor legislation and regulatory guidance across state, federal, and international jurisdictions in real time, rather than discovering new rules after they take effect.
• Compare Regulatory Approaches: Explore how different jurisdictions are addressing transparency, oversight, safety, and accountability in healthcare AI, identifying best practices and divergent strategies.
• Plan Implementation: Access summaries and implementation considerations for each policy, helping health systems understand what compliance will require operationally.
• Identify Trends: Use trend analyses to anticipate where governance is heading, allowing organizations to build toward regulatory requirements before they become mandatory.

The need for this kind of resource is urgent. As AI systems become more integrated into clinical care, Moss noted that "policymakers will need clearer frameworks around transparency, oversight, safety and accountability". Without centralized tracking, health systems risk either falling behind regulatory requirements or duplicating governance efforts across multiple jurisdictions.

Moss

What's the Bigger Picture for Global Healthcare AI Governance?

HAPI addresses a local problem, but the governance challenge is global. The World Health Organization, working with the International Telecommunication Union and the World Intellectual Property Organization, launched the Global Initiative on Artificial Intelligence for Health (GI-AI4H) to support safe, ethical, and equitable AI adoption across all WHO member states.

The GI-AI4H operates on three fundamental pillars: enabling robust governance standards and policies, facilitating a global community of experts and resources, and implementing sustainable models for AI programs at the country level. To make this work across diverse healthcare systems, the initiative introduced the RISE framework, which stands for Robust Capacity Building, Inclusive Research, Smart Infrastructure, and Equitable Data Practices.

"Will's work demonstrates the kind of thoughtful, interdisciplinary policy research that will become increasingly important as AI reshapes healthcare," said Sean Nicholson, a professor at Cornell. "Resources like HAPI can play an important role in helping policymakers, researchers, and health systems navigate an increasingly complex regulatory landscape."

Sean Nicholson, Professor at Cornell University

The RISE framework is intentionally modular, not a fixed sequence. Countries can prioritize and phase its components based on their existing capacities, regulatory maturity, and health system needs. This flexibility matters because healthcare AI governance looks different in Europe, where the EU AI Act establishes a risk-based regulatory approach, than it does in low- and middle-income countries like Zambia and Malawi, which are advancing their own national AI strategies and data protection frameworks.

Moss's vision for HAPI aligns with this global momentum. "The future of healthcare AI won't just be determined by engineers or companies," he stated. "It will also depend on the policies and governance systems we build around these technologies". By making governance information accessible and understandable, HAPI helps ensure that the people designing and implementing these systems have the information they need to do so safely, ethically, and equitably.

The work also reflects a broader recognition that governance is not a brake on AI progress; it's the architecture that makes progress sustainable. As healthcare systems worldwide grapple with how to integrate AI responsibly, tools like HAPI and frameworks like RISE provide the scaffolding needed to move forward with confidence.