UCL Study Finds NHS AI Rollouts Are Slower Than Expected

A new study from University College London reveals that introducing AI diagnostics tools in NHS hospitals has been more complicated than healthcare leaders anticipated. The research focused on a programme begun in 2023 to use AI for diagnosing chest conditions (like lung problems) across many NHS hospital trusts. What they found was that practical issues—governance, contract negotiation, data collection, and training staff—consistently delayed rollout. In fact, projects were taking between four and ten months longer to move from contract to deployment than planners had assumed.

One big bottleneck was how to ensure trustworthy data: sourcing high-quality, properly labelled data and making sure privacy safeguards were in place. Another challenge was ensuring staff both understood how to use the tools and felt confident that the AI could be relied upon. These learning issues meant that even when the technology was promising, hospitals weren’t able to scale as quickly as hoped.

The implications are important beyond just the NHS. If a well-funded, high-priority health system is facing delays, it shows how important organisational readiness is: having not just the AI tools, but the people, processes, data management and checks in place. For those of us thinking about AI in education, it suggests that adopting AI isn’t just about having good software; it’s also about training, governance, clarity and safety. Understanding these challenges now means we can help young learners not only use AI tools, but use them well.