AI Opportunities Action Plan: Thoughts from the Genomics AI Network Team
This week it was great to see the publication of the ‘AI Opportunities Action Plan’, confirming that the UK government firmly believes in an action-oriented response to the potential afforded by AI. But what of the opportunities in the NHS, specifically genomics, and how do these align to the direction set out in the Action Plan?
It should be no surprise that, with a name like the Genomics AI Network, GAIN has been exploring the potential from AI. The core of our approach neatly aligns with the public sector adoption mission stated in the plan (we went for ‘identify, evaluate, scale’ whereas the Action Plan opts for ‘scan, pilot, scale’). But what does this mean in practice?
At its most basic, we believe there’s a need to rapidly find potential solutions to problems, understand if these solutions truly work and where they do, to roll them out as efficiently as possible. This sounds almost trivially simple, but the size and complexity of the NHS means that while the potential for scaling is enormous, there are often numerous barriers. Just because something works well in Devon doesn’t mean it’s going to work in Newcastle. And it’s often difficult to share best practice, meaning that deploying the same tool across different bits of the NHS takes just as much effort the 8th time as it did the first time.
For GAIN, that’s meant we’ve put as much focus on the ‘scaling’ phase of the work as the ‘identify/evaluate’. As well as running our own series of AI pilots we’re then attempting to deliver a series of national AI ‘blueprints’ that enable the rapid deployment of specific AI capabilities across the whole NHS genomics ecosystem. By re-using expertise learned elsewhere and placing rails on AI deployment, we hope to lessen the resource burden and massively decrease the time to value.
It’s early days, but throughout 2025 we’ll be developing these capabilities and working with partners from across the NHS, industry and beyond to prove the transformational impact of AI in healthcare.
We’ll be sharing more of our experience as we go, but for now if you’d like to find out more or get involved, please to get in touch!