Dr Angus Ramsey, principal research fellow at the UCL Department of Behavioural Sciences and Health
A study led by University College London (UCL) researchers found that implementing AI into NHS hospitals is more difficult than initially anticipated by healthcare leaders, with complications around governance, contracts, data collection and staff training.
The study, published in The Lancet eClinicalMedicine on 10 September 2025, examined a £21 million NHS England programme which launched in 2023 to introduce AI for the diagnosis of chest conditions, including lung cancer, across 66 NHS hospital trusts.
Researchers conducted interviews with hospital staff and AI suppliers to review how the diagnostic tools were procured and set up, and identify any pitfalls or factors that helped smooth the process.
They found that contracting took between four and 10 months longer than anticipated and by June 2025, 18 months after contracting was meant to be completed, a third (23 out of 66) of the hospital trusts were not yet using the tools in clinical practice.
First author Dr Angus Ramsey, principal research fellow at the UCL Department of Behavioural Sciences and Health, said: “Our study provides important lessons that should help strengthen future approaches to implementing AI in the NHS.
“We found it took longer to introduce the new AI tools in this programme than those leading the programme had expected.
“A key problem was that clinical staff were already very busy – finding time to go through the selection process was a challenge, as was supporting integration of AI with local IT systems and obtaining local governance approvals.
“Services that used dedicated project managers found their support very helpful in implementing changes, but only some services were able to do this.
“Also, a common issue was the novelty of AI, suggesting a need for more guidance and education on AI and its implementation.”
Challenges identified by the research included engaging clinical staff with high workloads in the project, embedding the technology in ageing and varied NHS IT systems across dozens of hospitals and a general lack of understanding and scepticism among staff about using AI in healthcare.
The researchers concluded that while “AI tools may offer valuable support for diagnostic services, they may not address current healthcare service pressures as straightforwardly as policymakers may hope”.
They recommend that NHS staff are trained in how AI can be used effectively and safely, and that dedicated project management is used to implement schemes like this in the future.
Senior author Professor Naomi Fulop at UCL, said: “The NHS is made up of hundreds of organisations with different clinical requirements and different IT systems and introducing any diagnostic tools that suit multiple hospitals is highly complex.”
The research, funded by the National Institute for Health and Care Research, was conducted by a team from UCL, the Nuffield Trust, and the University of Cambridge.
They are now studying the use of AI tools following early deployment when they have had a chance to become more embedded.
Researchers say that the findings should provide useful learnings on implementing the government’s 10 year health plan, published on 3 July 2025, which identifies AI as key to improving the NHS.