The spectre of last week’s bond market sell-off continues to loom large over the UK government's ambitious artificial intelligence strategy. Investors and voters alike are keen to uncover the next source of economic growth, and both Keir Starmer and Chancellor Rachel Reeves see AI as a pivotal component of the answer.

The United Kingdom boasts formidable strengths in AI—loosely defined as computer systems capable of performing tasks that usually require human intelligence, from summarising a document to assessing a medical patient’s symptoms or drafting emails. These assets include a wealth of high-quality research and engineering talent emerging from British universities, as well as the presence of leading AI companies such as the UK-founded Google DeepMind.
Nonetheless, significant challenges persist, which the government recognises and aims to address through its strategy. Constructing data centres—the central nervous system of AI systems—is notoriously laborious in the UK, compounded by issues surrounding access to and the cost of vast amounts of energy. Additionally, there is the risk that AI talent and companies might relocate if conditions deteriorate, alongside the complex task of striking the right balance in regulation, from safety to copyright.
“AI is not a panacea. It’s not magic,” cautions Theo Bertram, director of the Social Market Foundation thinktank. “But if you are going to place your bets on a chance for economic growth, then this would be the best place to put it.”
Why is the government pinning so much hope on this plan, crafted by tech investor Matthew Clifford? Much of the rationale lies in productivity, defined as the output a worker can generate in an hour. The International Monetary Fund predicts that AI could boost UK productivity by up to 1.5% a year. For a country long plagued by low productivity—exacerbated by insufficient investment in cutting-edge technology—AI is viewed as a means to empower British workers, raise wages, and free up capital for other ventures. This is particularly crucial given the anticipated decline in the working-age population due to demographic shifts.
“If we see the working-age population shrinking you need to see productivity increase dramatically in order to see any sort of economic growth,” explains James Knightley, chief international economist at ING.
This logic extends to the public sector as well, with the plan urging state bodies to pilot AI-driven services. Beneath the drive for efficiency lies the potential for job redundancies, as AI automates certain tasks. The Tony Blair Institute (TBI) suggests that over 40% of tasks performed by public sector workers could be partly automated by AI, enabling the government to “reduce the size of the public-sector workforce accordingly” to capitalise on efficiency gains.
The TBI also estimates that AI might displace between 1 million and 3 million private-sector jobs in the UK. However, it emphasises that the net rise in unemployment would likely remain in the low hundreds of thousands, as the technology is expected to create new roles. Sectors such as law, finance, coding, graphic design, and copywriting—where workers may face transformation—will need to adapt and trust in the long-term benefits of improved productivity.
Securing the UK's pivotal role in developing transformative AI technology and its effective deployment across both private and public sectors demands a coordinated industrial strategy. Long-term industrial plans are intricate, requiring collaboration across diverse fields—from skills to energy infrastructure and regulatory frameworks—which is why the report lays out 50 recommendations for the government. These include establishing “AI growth zones” with fast-track planning privileges, launching a body to support leading domestic AI firms, and enhancing AI-related work skills.
Of course, some aspects of the government’s AI policy are bound to raise concerns. The proposal to create national datasets composed of public data must overcome hurdles related to privacy, ethics, and data protection, while a recent move to allow AI firms to train their models on copyrighted work was rejected by creative industries and publishers.
Yet for Starmer and Reeves, economic growth is paramount. As Dame Wendy Hall, a professor of computer science at the University of Southampton and a member of the UN’s advisory body on AI, emphasises, “It’s not a question of ‘can they deliver it.’ They have to deliver it.”
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