Everyone’s talking about AI, let’s make it count 

Over the past year, AI has surfaced in nearly every conversation I have been a part of. From strategy launches and media headlines to health tech expos and start-up showcases, AI is everywhere in our lives. In our sector, AI has become shorthand for the future of healthcare: transformative, disruptive, revolutionary. 

And it does have a huge potential; I have seen how the right AI tools can strengthen prevention strategies, enable personalised care, and support clinicians to focus on what matters most: people. But I have also seen how promising pilots stall and lose momentum before wider adoption, good ideas struggle to fit into everyday practice, and ‘solutions’ are introduced without a clear understanding of the problems they are trying to solve! 

If we want to be serious about making AI work for the NHS, it must be connected to the system’s real problems and designed with patients, clinicians, and communities at its heart. We must also be open to rethink and challenge our current processes and approaches to truly reshape the future of healthcare.  

Therefore, we created a new animation to inspire system leaders reimagine the desired role and successful application of AI in the NHS. This practical, visual tool is designed to help leaders step back, see the bigger picture, and cut through the noise. It prompts the right questions about AI and shows how it can work with, not against, the realities of healthcare while bringing people at the centre of the design. 

Four principles for AI in healthcare 

We have grounded the animation around four principles that align with the three key shifts and ambitions outlined in the NHS 10-Year Health Plan and the Life Sciences Sector Plan, both of which place innovation at the heart of their ambitions. 

These aren’t theoretical, they are already happening across the country and with focus, we can deliver more and transform faster: 

• Predictive – Identifying risk at a population level to shift care from reactive to proactive. For example, AI risk models are enabling earlier intervention for conditions like cardiovascular disease up to ten years in advance. 

• Preventative – Using real-time monitoring to manage people in the community and reduce avoidable admissions. AI-driven alerts takes a new approach to healthcare by using advanced AI screening to identify patients at high or rising risk of unplanned emergency care. 

• Personalised – Tailoring treatment to individual needs. For example, using genomics, digital pathological images, and other data to support clinicians in selecting appropriate targeted therapies in oncology. 

• Participatory – Supporting shared decision-making and self-management. Smart tools are helping people with diabetes adjust care plans in partnership with clinicians. 

Building on what’s working 

Our recent report, AI in London Healthcare: The Reality Behind the Hype, captures early examples of AI adoption across London providers, and highlights that without a clear strategy for system-wide transformation, these efforts risk remaining fragmented and their impact limited. That’s why it is imperative to leverage best practices and collaborate with purpose to accelerate these shifts with clarity, ambition and a shared vision.