Artificial Intelligence (AI) might revolutionise healthcare—but without robust legal frameworks, and without people trained to work alongside the technology, progress could stutter or even cause harm. AI already diagnoses illnesses, recommends treatments, and manages patient data. The law must evolve to govern not just isolated moments but the entire lifecycle of AI in healthcare–and medical education must evolve to prepare healthcare professionals for this change.
From my work on the Research Handbook on Health, AI and the Law and developing national guidelines in Qatar , one truth stands out: piecemeal regulation is no longer sufficient. We need comprehensive governance frameworks as we suggested in our recent npj Digital Medicine paper — and we need a workforce with the knowledge and skills to apply them.
The Lifecycle Problem and the Human Gap
Current regulatory models, such as the EU’s AI Act or the FDA’s frameworks, tend to intervene only when AI systems are market—ready. By then, issues—bias in datasets, unclear liability, or opaque algorithms—are already embedded.
There’s also the challenge of who is equipped with the knowledge and skills to navigate these issues. AI in healthcare isn’t static. It evolves, learns, and adapts. Yet most legal systems treat it like a traditional medical device—something fixed and predictable. At the same time, medical education is not giving students the resources to deal with this complexity. This mismatch creates risk, not only for patients but also for clinicians, policymakers, and educators who are left without the skills to respond.
This is where human capacity is critical. The best legal frameworks will promise much but deliver little if education systems that train medical professionals, lawyers, engineers, and regulators do not work together to resolve these problems.
Why this matters for Educators
I have argued elsewhere that a “True Lifecycle Approach” towards governance is needed—one that embeds legal oversight across three phases: research and development (R&D), approval, and post-implementation monitoring.[1] But what does this mean for educators who are on the frontline of transformation? We must prepare students for jobs that don’t yet exist. The healthcare workforce needs reskilling to adapt to that AI lifecycle to understand data ethics, legal accountability, and AI oversight. Legal professionals must also learn to evaluate algorithmic decisions or recommendations. And policymakers in government need to translate complicated technical questions into sound public policy – perhaps through capacity building programs. Teaching people how to navigate this landscape is as important as the governance of AI itself.
Practical Momentum
I propose three steps for connecting law, healthcare, and education to navigate this evolving world.
- Teach Governance from Day One
I have argued that guidelines should begin at the R&D stage of AI. But education systems also have a responsibility to introduce cross—disciplinary training early that embeds law, ethics, data literacy, and more into health and engineering curricula. - Educate about ‘Non—Clinical’ AI
Did you know that not all healthcare AI is a “medical device”. AI is found in wellness apps on app stores, and it has many administrative uses. It’s used for triage, staff scheduling, bed management, and more. These still impact patient care, and educators should prepare professionals to spot these ‘grey zone’ uses and address any issues that may arise. - Build Systems for Continuous Oversight
AI does not stand still. It evolves, learns, and changes the more it is used in practice. Educators should be equipped for this fluid world with continuous learning that helps them adapt and reskill as the technology evolves.
A Call to Action
If we fail to establish both governance and human capacity throughout the AI lifecycle, we risk undermining innovation and trust. The goal isn’t to slow progress but to steer it responsibly. From my experience, most developers are seeking clear rules — and they also need people trained to implement them.
Healthcare stakeholders, policymakers, and educators must champion frameworks that evolve alongside technology, while education systems ensure people are prepared to apply them.
As AI reshapes healthcare, let us ensure that it is guided not only by law and guidelines – but by human capacity, reskilling, and education for this new world.
