The NHS Artificial Intelligence (AI) Lab was launched in 2019 by NHS England and the Department of Health and Social Care to accelerate the safe and effective adoption of AI across health and care. With £143.5 million of funding, the Lab represented a world first programme combining infrastructure development, research, regulation, ethics and real world deployment of AI tools.
An independent evaluation led by The University of Edinburgh and supported by Arden & GEM took place over a ten-month period in 2024. The review explored how the Lab was implemented, what it achieved and what lessons could guide future AI programmes. Findings showed that the AI Lab played a pivotal role in coordinating AI development, testing, adoption and regulation, helping position the NHS as a global leader in evidence based, responsible AI innovation.
The challenge
Launched in 2019, the NHS AI Lab was a pioneering national programme created by NHS England with the Department of Health and Social Care to accelerate the safe, effective adoption of AI in health and care. With initial funding set at £250m – later revised to £143.5m following a spending review – identifying and demonstrating the Lab’s contribution and impact was critical for future AI investment and programme design.
An independent evaluation set out to understand and evidence the NHS AI Lab’s processes, outcomes, impacts and value for money to inform national strategy and future AI programmes. Specifically, the objectives were to:
- gather robust evidence on how the Lab was implemented and governed
- assess the impact of funded activities on patient outcomes, operational efficiency and system value
- evaluate short‑ and long‑term value for money using a structured health economics approach
- distil generalisable lessons to support scaling, procurement, regulation and adoption of AI across the NHS.
In parallel, the work aimed to surface the enabling conditions for AI – such as data infrastructure, skills, procurement pathways, ethical and regulatory readiness – and explore how national direction can best balance with local choice to meet frontline needs.
Our approach
Between March and December 2024, senior researchers from The University of Edinburgh delivered a comprehensive assessment of the AI Lab’s achievements and challenges. Arden & GEM provided health economics and project management expertise, supporting the generation of value for money estimates and programme delivery assurance.
Evaluation scope and methods
The evaluation examined the AI Lab’s interlinked workstreams of infrastructure, community building, research and evidence, and governance and ethics. The team conducted a mixed‑methods formative and summative study.
Evidence collection included:
- reviewing 1,021 documents, including business cases, meeting minutes, lessons‑learned reports and technology evaluations
- 85 semi‑structured interviews with current and former AI Lab staff, national and local decision‑makers, technology developers, NHS providers and evaluators
- observing 12 meetings and workshops to understand real‑time governance and decision‑making.
Analysing information and results
Qualitative data was analysed using a Technology, People, Organisations, Macro‑environment (TPOM) framework to explore how these four elements interacted. To assess value and impact, the Triple E Framework was applied, focusing on economy (cost), efficiency (how well resources are used) and effectiveness (how well a programme achieves its goals).
Quantitative analysis focused on exploring higher‑maturity technologies funded through the AI in Health and Care Awards where financial and non‑financial benefits could be estimated with confidence. Examples highlighted included:
- a diagnostic decision-support tool that aided frontline clinicians in making time-critical treatment decisions, delivering an estimated cost saving of over £44 million across a cohort of 150,000 patients, far exceeding the £1.25 million cost of the project
- projects improving alignment with the 2019 NHS Long Term Plan, such as increasing mechanical thrombectomy rates for stroke patients to 10%.
The final report framed findings and recommendations to inform emerging NHS AI strategy and emphasised the need for continued monitoring to capture long run benefits beyond the five year programme window.
The outcomes
The evaluation concluded that the NHS AI Lab made significant progress in advancing AI development and scaling in health and care. Early return‑on‑investment estimates were identified for several mature technologies, particularly where AI deployment was integrated with process changes and pathway redesign.
The team also recognised that many benefits, particularly those linked to regulatory reform and early-stage innovation, are harder to measure and will only materialise over longer timeframes.
Seven key lessons were highlighted to support policymakers and leaders in continuing the journey towards transforming health and care through AI:
- Maintain strong national support and system-wide intervention
- Ensure a long‑term vision and leadership stability
- Root AI development firmly in system and service-user needs
- Prioritise pathway transformation over isolated task automation
- Embed proportionate, longitudinal evaluation
- Balance benefits and risks as technologies evolve
- Systematically build on learning to guide future AI policy and investment.
"The findings from this report will inform the ongoing development of AI strategies and approaches that can help the NHS to make the strategic shift from analogue to digital in health and care. Helping to shape a future where AI will enhance patient care, operational efficiency and overall healthcare outcomes."
Dom Cushnan, Director of AI, Imaging and Deployment at NHS England
Find out more about Arden & GEM's support for evaluation.