TL;DR

Chancellor John Healey used the Budget on 28 October to announce an independent look at how AI could make the NHS more productive. It will be led by Mark Bailie, who sits on the NHS England board as a non-executive, and its findings are due in the first months of 2027 so they can feed into the next spending round. The Budget also put £100m behind robotic-assisted surgery, with a national registry that will use AI to track outcomes.

The review

According to the official transcript, Healey told MPs the review, run jointly with the Health Secretary, would mean “staff can spend their time with patients and not on admin”. Digital Health reports that the Budget document gives it a remit to “focus on the practical opportunities presented by AI and technology to transform services for patients and boost NHS productivity”.

Jennifer Dixon, who heads the Health Foundation, said it was a chance to build on that charity’s own NHS Productivity Commission. She wants the first job to be building ways of testing whether AI and other new approaches improve patient care and offer value for money.

The money alongside it

The robotic surgery money is drawn from the Transformation Fund for the NHS. The aim is to raise the number of robot-assisted procedures in England from 70,000 a year to 500,000 by 2035. A new national registry will draw on data and AI to track how operations turn out and where access is uneven.

Other measures with an NHS angle included:

• a £15m AI Challenge Prize announced before the Budget, whose first round targets NHS problems, with £2.5m as the largest single award
• £24m to extend the public sector’s AI cyber defence programme to hospitals, councils and schools
• a commitment that strategic data centres will give the NHS and wider public sector secure computing capacity

Our separate report covers the data centre covenant Healey linked to keeping NHS data in the UK.

Looking Forward

In our view, the review is the measure for suppliers and trusts to watch, and its value will depend on whether it measures what AI tools already in use actually save, rather than restating their potential. Dixon’s call for evaluation infrastructure points at the same gap. With the report due before the next spending review, its findings could shape which AI programmes the NHS funds at scale.