The third is people and skills. Most of the research workforce doesn’t need to become AI specialists, but they do need enough grounding to use these tools well and to know where they fall short. Beyond that, we need more of the rare researchers who are genuinely fluent in both data science and biology, the people who can make the two worlds talk to each other. They are hard to find and easy to lose, so we also need a system that lets people move between universities, the NHS and industry without it being a one-way door.
The fourth is computing power, where the trap is to assume the answer is simply more of it. How it is shared out matters just as much. Life sciences has needs that general-purpose compute planning could potentially overlook, and an impressive national headline figure means little if researchers can’t get time on the machines.
The harder problem is that data and compute often sit in different places, when the sensible thing, for security as much as speed, is to bring the analysis to the data rather than shuttling sensitive data around. Get that right, and capacity that exists only on paper becomes something researchers can really use.
Foundations first
Get these four things right, and the rest follows. The technology and ambition are here. The task now is to step back and strengthen the foundations beneath them. CRUK is playing its part: investing in AI-ready data, building skills across the research community, and pressing government to move faster because we are moving too.
Do make sure to take a look at the Rewiring the Life Sciences report in full. If you are a researcher working at this intersection, the foundations get built faster when the people who run into them every day help shape the fix, and we would value your perspective. The point, in the end, is people living longer, better lives, free from the fear of cancer, reached sooner because the foundations were finally there to carry the research that serves them.
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