The U.K. Government’s new “AI Opportunities Action Plan” has been met with optimism, but a closer look reveals glaring flaws. Underfunded and lacking structural reforms, it fails to address Britain’s AI talent drain, insufficient funding and high energy costs. Without urgent action, the U.K. risks falling further behind global AI leaders.
The U.K. Government’s new AI plan was unveiled in mid-January. And, for an administration struggling to lift the mood of British business, it was curious to see the plan meet with such a warm reception.
For when you look closely at the “AI Opportunities Action Plan”, its shortcomings quickly become apparent: namely, it’s grossly underfunded and does little to tackle the structural reasons why Britain is now lagging in the global AI race.
This isn’t just a miss for the U.K.’s AI sector; it’s a blow to the broader economy today and tomorrow.
Britain is struggling to attract and retain top technological talent, to build a robust capital ecosystem for innovation, and to keep a lid on energy costs – all issues that are pivotal to rapid and sustained AI progress.
Prime Minister Keir Starmer had a prime opportunity to stake Britain’s claim to AI leadership. Yet seen from the viewpoint of the global AI community – those shaping the future direction of these technologies – the announcement only underscores that Britain is set to fall even further behind the likes of the U.S., China, Canada and France.
The U.S. stands in a particularly stark contrast given President Trump’s early AI announcements. While Washington is yet to coalesce around a neat, comprehensive AI policy, the nation’s AI output—via OpenAI, Anthropic and others—reflects decades of research, development and funding that Britain has thus far been unable to emulate.
Indeed, the U.K.’s current AI shortcomings are present at every phase of the company development cycle. We’ve seen in our data the brain drain that Wall Street has executed, where only one third of banking AI talent actually works for a U.K. bank. This is true across the many sectors and industries AI is now disrupting and transforming.
The AI talent that the U.K. retains lacks access to the massive risk capital available to U.S. startups. Our convoluted investment landscape is flanked by a waning national commitment to R&D. Few AI companies stay in the U.K. long enough to hit the public markets; those that do are greeted by a London Stock Exchange that has been knocked off its perch by other more attractive financial centres.
From an energy perspective, while this AI framework seeks to build better – and much needed – energy infrastructure inside AI Growth Zones, reducing planning requirements for data centres is highly unlikely to be an AI game-changer given how high the U.K.’s energy prices are compared to its AI rivals. Even if the tenants of the policy function as planned, the national grid appears woefully unprepared for demand that experts say would require the capacity of a large nuclear facility.
Even where the AI plan outlines good ideas, the timing is off. For example, setting up a National Data Laboratory could have long-term research benefits, but targeting Summer 2025 for the first deliverables puts the U.K. well behind France, which has set up concrete systems to improve access to open data since 2018 and invested €2.5 billion towards AI development as a part of the France 2030 plan.
It’s indicative of a broader problem: lack of implementation. While other countries are sharing specific AI use cases, the 50 recommendations included in the U.K. policy are still largely centred on exploring the impacts of AI policy changes rather than implementing it.
Look again to the U.S., where the government recently laid out more than 1,600 AI use cases in play across federal agencies – something it’s done since 2022. By Autumn 2023, the government had just 74 AI use cases actively deployed.
The U.K.’s plan for sectoral AI Champions, who will “help identify” spots where AI “could be a solution,” may be a small step towards changing that, but the U.K. Government’s talent push still trails the U.S., where more than 200 of the 500 planned public-sector AI hires were already in place as of last summer and agency appointments of Chief AI Officers are underway.
Lagging AI implementation is hardly limited to the public sector. In our own data benchmarking AI adoption in the world’s most prominent banks, HSBC is the only British institution that ranks among the top 10, and all of the evidence points to the U.S. banks extending their lead over the City of London.
To show serious intent about incentivising AI growth, Keir Starmer and his Government needed to answer critical questions around talent, energy and funding. As it stands, the AI Opportunities Action Plan has arrived five years too late and without any meaningful response to the biggest AI challenges facing the country. Having an AI strategy is certainly better than not having one, but the fact remains, without urgent action – and investment – to address its structural shortcomings, there’s no hope of Britain becoming an AI superpower.
About the Author
Alexandra Mousavizadeh is Co-Founder of Evident Insights, an intelligence platform tracking AI adoption in financial services, helping leaders make informed AI-related investments and strategic choices. A former economist for Moody’s and Morgan Stanley, Alexandra was the architect of the groundbreaking Global AI Index, benchmarking the strength of national AI ecosystems.
