Harnessing the potential of AI to bring real benefits for patients

Artificial intelligence has huge potential to improve health and care, but its use must be safe, effective and fair. In this blog, chief executive Jonathan Benger explains how NICE's new AI delivery plan will support responsible adoption in the NHS, ensuring AI brings real benefits for patients.

Artificial intelligence is no longer the preserve of science fiction.

In a matter of years, it has become a part of our everyday lives, helping us to work, communicate and solve problems in new and unexpected ways.

Healthcare is no exception.

Artificial intelligence is moving rapidly from promise to practice.

Around the world, AI is already helping clinicians interpret medical images, supporting earlier diagnosis, identifying people at risk of illness and reducing administrative burdens.

Its potential is enormous.

But the real question is not whether AI will become part of healthcare; it is how we ensure it improves care in ways that are safe, effective and fair.

That is why NICE has published a plan that sets out how we will enable the safe, effective and scalable adoption of AI in the NHS (Word).

The plan presents ways in which NICE will support the responsible adoption of AI across health and care, while helping to create the conditions for innovation and economic growth.

It reflects the government's ambition to harness the opportunities offered by AI. But it also recognises that public confidence must be earned through transparency, evidence and robust standards.

Our work over the next year will focus on 3 key areas.

1. Using AI for evidence generation and evaluating innovation

For 27 years, NICE has led the way in health technology assessment, spearheading new ways of developing healthcare guidance.

We uphold the principle that healthcare decisions should always be guided by evidence. And this principle does not change when AI enters the frame.

One of our priorities is to help developers and innovators use AI appropriately when generating evidence about new treatments, technologies and ways of delivering care.

AI can help analyse large volumes of information far more quickly than traditional approaches. It may identify patterns in data, help researchers review scientific literature more efficiently and support analysis of real-world healthcare information.

But speed alone is not enough.

We need to understand how conclusions have been reached and ensure that methods are robust, transparent and reproducible. In healthcare, decisions affect people's lives. The evidence must therefore be both reliable and explainable.

We will continue to work with experts, researchers and industry partners to develop clear expectations about how AI should be used in evidence generation. By March 2027, we will publish an AI best practice methods framework for the use of AI in evidence generation, synthesis and review. This will build on work that includes:

- Testing and learning about how AI will transform health technology assessment through our HTA Innovation Lab.