Why strategy will make or break the UK’s AI healthcare future

AI is already transforming healthcare around the world, cutting admin time, helping doctors diagnose more accurately, and connecting patient data in ways that were impossible just a few years ago.

In the Middle East, this isn’t a future aspiration. It’s the present. Governments and private providers are working together to roll out AI that predicts patient risk, connects health records across regions, and brings specialist care to places that previously went without. In the UAE, AI-powered diagnostics have halved some diagnosis times. Saudi Arabia is using predictive tools to reduce hospital admissions. Qatar has integrated precision medicine into its national healthcare vision.

It’s not just the technology making the difference. It’s the strategy. These nations have clearly defined the role of AI in healthcare, set shared goals between the public and private sectors, and removed unnecessary roadblocks for innovators. The result is faster rollouts, measurable patient benefits, and a tangible reduction in clinician burnout.

The UK is not ignoring AI. Far from it. The government’s 10-Year Health Plan includes ambitious commitments to digitise services and push innovation across the NHS. But progress is inconsistent, and without a coordinated, long-term approach, even the most promising initiatives risk losing momentum before they can deliver real change.

The appetite for innovation is there. Surveys show that a large majority of NHS staff support the use of AI in both patient care and administrative tasks. But adoption is slowed by complex approval processes, a lack of clinician involvement in the design of new tools, and a cautious regulatory culture that often delays implementation.

I have seen this up close. At Rhazes AI, we built a solution to take repetitive administrative work off doctors’ plates, something I knew was urgently needed from my time in the NHS. Yet, despite the clear demand, the process of getting our technology approved and integrated was slow, expensive, and bureaucratic. In contrast, when we looked to other markets, the path to adoption was faster and more collaborative.

This doesn’t mean the UK is destined to lag behind. It has the talent, infrastructure, and ambition to be a global leader in AI healthcare. But success will require a clear national strategy that aligns vision with execution, accelerates the approval process, brings clinicians into the conversation from the very start, and builds confidence through targeted training and real-world results.

AI is no longer a nice-to-have for modern healthcare. It is essential to improving patient outcomes, reducing pressure on staff, and creating a more resilient system for the future. The question is not whether to embrace AI, but how to do so quickly, effectively, and in a way that works for both patients and clinicians. The UK has every reason to seize this opportunity, and every capability to make it happen.