A new AI research screening platform dubbed AIR-SP - backed by nearly £6m in government funding - is being built by NHS England to enable trusts across the country to join trials of AI in screening. It will offer NHS staff access to AI tools in trials to help analyse screening images and pinpoint abnormalities.

Currently, 90% of AI tools remain stuck in pilot phases due to over-reliance on temporary IT setups in trusts. Even if one tool is deemed effective by a trust, every other trust in the NHS must start the process of testing the tool from scratch and set up new databases to access images generated by the AI.

The new NHS-wide cloud will hold multiple AI tools in a single environment that will have secure connections to all NHS trusts. It will dramatically cut down the time and costs associated with rolling out AI research studies.

The platform, which will take approximately two years to build, means AI tools could in future be tested and trialled at the same time, in any trust across the health service, with a view to rolling them out to the NHS frontline if they are proved effective.

It will first be used to support nearly 700,000 women across the country taking part in an NIHR-funded trial, identifying changes in breast tissue that show possible signs of cancer and referring them for further investigations if required.

As it stands, costly IT solutions across multiple trusts - up to £3.5m per study - are required for each research study involving several projects to ensure AI access to images. The new unified platform will simplify this process, reducing costs by millions of pounds per study, and enabling multiple AI products to be tested in one secure environment. It is expected to save £2-3m for every multi-site study.

Wes Streeting, secretary of state for health and social care, said: ‘The AI revolution is here, and we are arming staff with the latest ground-breaking technology, so patients get faster and smarter care.

‘As our world-leading scientists develop new lifesaving AI tools, this new cloud platform will see them rolled out to patients in research trials right across the country - so staff can treat patients quicker with cutting-edge tech.

‘This government is reinstating the UK's position as a technology superpower - driving vital investment and economic growth as we build an NHS fit for the 21st century.'

The building of the digital platform is being funded by NIHR and is expected to be rolled out for research purposes in 2027.

Reaction

Dr Layla McCay, director of policy at the NHS Confederation, said: ‘Health leaders will welcome the announcement that artificial intelligence tools will be tested in NHS screening services, allowing staff access to state-of-the-art programmes for research purposes. Our members tell us about the challenges of rolling out AI tools at scale, and the impact of duplication of testing across sites, which hopefully this platform can help to address.

‘Investing in digital technologies like AI and the high-tech IT infrastructure the NHS needs to provide patients with a service fit for the 21st century is crucial to the government's ambitions of moving from an analogue system to one that is fully digitised.'

Dr Kevin Dunbar, NHS deputy director of the public health, vaccination and screening directorate, said: ‘This innovative cloud platform will help vastly accelerate research into the use of AI to enhance vital NHS screening programmes.

‘By enabling trusts and patients across the country to participate in landmark AI trials in the coming years, it will combine cutting-edge technology with clinical expertise to improve care for patients as well as NHS productivity.'

Professor Lucy Chappell, chief scientific adviser at the DHSC and chief executive of the NIHR, said: ‘In order to unlock the potential of AI in healthcare, we need digital infrastructure that enables researchers to rigorously evaluate these tools in real-world NHS settings, at speed and scale.

‘This unified AI research screening platform will help us to understand how AI can safely and effectively improve patient care, while speeding up the time it takes to set up AI research studies and reducing costs.'