Is the UK ready for the AI revolution?

The UK stands at a crucial juncture, poised to either lead or lag in the burgeoning era of artificial intelligence. 

Acknowledged as a significant player on the global stage, boasting the third-largest AI market, the UK faces a pressing need to translate its potential into tangible progress.

The Labour government’s AI Opportunities Action Plan explicitly recognises the urgency of accelerating AI adoption to fuel economic growth and societal advancement — or face the possibility of the nation falling behind the rapid strides made by global powerhouses like the USA and China.               

The UK’s AI readiness challenge

Dark Matter, in association with HPE, is investigating the UK’s preparedness to embrace the AI era and addresses the challenges — and considerable opportunities — that UK businesses and government bodies face as they navigate this largely uncharted AI territory.

From digital sovereignty, environmental sustainability, to infrastructure and talent pipelines, Dark Matter’s initiative focuses on deeper structural questions that need answers.

The stakes are high and the answers, as outlined by experts from across UK PLC, are not straightforward.

Building the UK’s AI backbone at home

One of the most pressing concerns raised by industry experts is the concept of sovereign AI. This encompasses not only data residency within the UK but also the development of domestic AI capabilities to reduce reliance on foreign providers and ensure national resiliency.

The UK Government has promised to expand the country’s sovereign AI computing capacity by at least 20 times by 2030 and establish dedicated AI Growth Zones to accelerate the build-out of AI infrastructure. Benedict Macon-Cooney, Chief Policy Strategist at the Tony Blair Institute, emphasises that the UK needs to “build very, very strong AI capabilities at home” to exercise its own power in the modern economy.

Karl Havard, CCO at Nscale, shared his view on the UK’s ambitions: “Assuming the UK goes forward in building a sovereign AI platform, call it a national grid of AI that makes it accessible for all, then that would be great.”     

UK AI sovereignty challenge  

However, experts point to the challenge that much of the country’s data infrastructure still sits with foreign providers like AWS, Azure and Google Cloud — a juxtaposition to the sovereign ambition. As Professor Gopal Ramchurn, CEO of Responsible AI UK notes: “The UK’s approach to adopting AI and deploying it at scale has largely been dictated by views from the US.”

“The traditional hyperscalers, because they’re US-based, cannot be UK sovereign. Sovereignty means the infrastructure, the data and the economic benefit stay in the UK. We need to build the belief that we can do this ourselves,” says Havard.    

While the concept of sovereign AI was once a fringe concern, it’s fast becoming mainstream. Amid rising cyber threats and geopolitical instability, there’s growing awareness about the importance of maintaining control over public data when training AI models. There are valid concerns about data confidentiality, training practices and the potential misuse of proprietary information.  

Industry experts emphasise that without a resilient, hybrid infrastructure rooted in UK soil, ambitions for long-term AI leadership may fall short.

The UK’s approach to adopting AI
and deploying it at scale has largely
been dictated by views from the US.

Skills, trust and public confidence

The investigation also highlights the skills gap that continues to challenge the UK’s AI ambitions. While AI Engineering and Data Science roles are growing in demand, there remains a shortage of skilled professionals to meet current and future needs. Lifelong learning initiatives are still limited, and public trust in AI remains a work in progress.

On the issue of skills, Matt Harris, SVP & Managing Director UKIMEA at HPE, highlights the importance of developing UK AI skills and the potential this provides the nation: “I actually think about national competitiveness when it comes to sovereignty. I think about the skills that are going to be potentially built on our shores, which means that we become an AI exporter.”

However, to grow skills, you need trust. The trust deficit isn’t abstract, as it affects real decisions from health to finance to national security, where the deployment of AI could reshape lives and institutions. “I think, right now, we have a trust crisis,” Professor Ramchurn says. “It’s very hard to know who’s a real expert, who we can trust to give us the right expectations about AI, to give us the right predictions about the impact of AI.”

Havard adds: “We need a common purpose and an orchestrating layer to be able to help everybody come together and collaborate and then show the rest of the UK the results and be proud of them. We need to say to the public, we can lead the world and here’s a set of results to prove it.”

Experts suggest that only through responsible education, transparent frameworks and skilled oversight can trust be earned and maintained.

Learning from the past

The investigation draws a sharp line between AI and the last technological transformation the UK embraced wholesale: cloud computing and history serve as a cautionary tale. Not all migrations delivered on the public cloud’s promise of efficiency and flexibility. For some, the lack of planning led to spiralling costs, security issues, and a difficult path to repatriation.

Abdi Goodarzi, Head of GENAI Products at Deloitte, cautions, unlike the mistakes made during the cloud boom, “there’s more at stake” with AI. “AI has gone through a different curve. The reason being is AI needs a lot of foundational elements to be in place, data and computing.”

AI must be purposeful and value-driven

Goodarzi further suggests that without the right data, computing and governance in place, there could be mistakes, but on a much larger scale. AI-driven technological transformation needs forethought, considered infrastructure and a roadmap that accounts for unintended consequences.

AI implementation must provide genuine value and avoid becoming an exercise in simply adopting AI for AI’s sake. It’s easy to get caught up in the hype surrounding AI, but organisations must define and fund use cases based on a clear understanding of the potential impact on citizens, return on investment and outcomes.

As Goodarzi goes on to say, many companies are engaging in proof of concepts and pilots, highlighting the need to first figure out viable applications. The ultimate goal should be tangible benefits, not just the deployment of AI itself.

Unlocking AI responsibly

HPE is committed to unlocking AI for the UK in a responsible and purposeful way, backing infrastructure, strategy and skills development that can scale sustainably and serve the public good.

They are supporting Dark Matter in asking the critical questions and highlighting to the public that AI is not a switch to be flipped without careful consideration and thought-through strategies. If the UK is serious about leading in AI, that journey needs to begin with truth, not hype.

Matt Harris

SVP & Managing Director UKIMEA, HPE

Karl Harvard

Chief Commercial Officer, Nscale

Abdi Goodarzi

Head of GenAI Products, Innovations and New Businesses, Deloitte

Professor Sarvapali (Gopal) Ramchurn

Chief Executive Officer, Responsible AI

Benedict Macon-Cooney

Chief Policy Strategist, Tony Blair Institute