Has the UK’s AI infrastructure buildout been a success?
QTS’s data center in Cambois, North East England
When the UK unveiled its AI Opportunities Action Plan in January, a major plan to spread the technology throughout society, Prime Minister Keir Starmer declared that the strategy would turn the country into an “AI superpower.”
A key pillar of this plan was the rapid creation of data centers that could handle the massive computing requirements for AI rollout. This will be driven by “AI Growth Zones” – designated areas with relaxed planning permission and access to advanced power.
Almost a year has passed and Nvidia, MicrosoftAnd Google all of them have devoted billions of dollars to artificial intelligence infrastructure in the country. Four AI growth regions have been announced, and local startups such as Nscale have emerged as key players in this space.
But critics point to heavily restricted access to energy through the national grid and slow construction as signs that the country risks falling further behind global rivals in the AI race.
“Ambition and delivery are not yet aligned,” Ben Pritchard, CEO of data center power supplier AVK, told CNBC.
“Growth has been held back largely by constraints on energy availability. Grid bottlenecks in particular have slowed the pace of development and mean the UK is not yet able to deploy infrastructure quickly enough to keep up with global rivals.”
Network connection delays
It is still early days in building AI infrastructure in the UK, as AI growth zones are currently in the early stages of their development.
A site in Oxfordshire, due to be first announced in February, has not yet started construction and is still evaluating delivery partner offers. Announced in September, groundbreaking work has begun at a site in the North East of England, with official construction set to begin in early 2026.
Two more sites opened in North and South Wales in November. The former is seeking an investment partner and expects this to be approved in the coming months, the Department of Science, Technology and Innovation (DSIT) told CNBC. The latter consists of a number of sites, some of which are already operational, with additional construction work to be done at others, DSIT said.
The UK government said in July it was targeting a core group of AI growth zones serving at least 500 megawatts of demand by 2030, with at least one of them to scale to more than one gigawatt by then.
But Pritchard said the most serious challenge to meeting these targets was the UK’s limited grid capacity.
“Developers are expecting eight to ten year delays in grid connectivity, and the volume of outstanding connection requests, particularly around London, is unprecedented,” he told CNBC.
Pritchard added that AI workloads are also “significantly increasing energy demand” as businesses and consumers begin to use the technology, putting additional pressure on a strained energy system. “These are no longer isolated risks; they are actively slowing or hindering developments across the country.”
Kao Data’s Spencer Lamb said the open call for applications for the AI growth zone initiative has created a situation where landowners with utility poles or power cables across their property are applying for the designation.
“This has resulted in the national grid being flooded with power grid applications from speculative sources” with no realistic chance of success, he told CNBC.
Laying the foundation
The National Energy System Operator (Neso), the UK’s public authority responsible for managing the national grid, has moved to remedy the situation.
Earlier this month it announced plans to prioritize hundreds of projects for faster access to the grid. Neso declined to comment on whether AI infrastructure projects were among those prioritized by CNBC, but said a significant number were data centers.
There have also been big money commitments from tech giants, many of which were announced by the UK government in September.
Microsoft, Nvidia, Google, OpenAI, CoreWeave and others announced During US President Donald Trump’s state visit, billions of dollars of artificial intelligence investment was made in the country, including plans to deploy the latest chips and open new data centers.
Nscale, a domestic startup that provides access to AI computing and builds data centers, also announced deals to deploy tens of thousands of Nvidia chips at an AI factory just outside London in early 2027.
The Nvidia GB10 Grace Blackwell Superchip was showcased at the company’s GTC conference in San Jose, California, on March 19, 2025.
Max A. Çerney | Reuters
“Investment from major private players has laid a significant foundation,” Puneet Gupta, UK and Ireland managing director of data infrastructure company NetApp, told CNBC. “Momentum is also building around plans for national research supercomputers and new computing capacity, with commitments to build AI ‘gigafactories’ in the UK.”
But Gupta said the “real test” will be how quickly these plans translate into usable computing for organizations in the UK.
Avoiding the ‘sugar rush’ of AI infrastructure
Stuart Abbott, chief executive of VAST Data, the UK and Ireland’s AI infrastructure company, told CNBC that the long-term success of the country’s AI infrastructure buildout will require it to invest in the “full stack,” including data pipelines, storage, energy supply, security, talent and skills.
“If the UK wants this to be permanent rather than a one-year sugar rush, it has to treat AI infrastructure like economic infrastructure.”
Stuart Abbott
Managing director of VAST Data, the UK and Ireland’s AI infrastructure company
This means “developing an operational structure that allows real institutions to securely deploy AI at scale,” he added. “If the UK wants this to be permanent rather than a one-year sugar rush, it has to treat AI infrastructure like economic infrastructure.”
The challenges are important. The value of data center deals in Europe It pales in comparison to the sums being poured into projects in the US The UK now has Europe’s most expensive energy, around 75% higher than before Russia’s invasion of Ukraine, and outdated grid infrastructure that can take many years to connect to new sites.
AVK’s Pritchard said microgrids were one potential solution for projects unable to secure access to the national grid. Microgrids are independent power networks derived from sources such as motors, renewable energy sources and batteries.
AVK is currently designing two microgrids for partners building cloud computing in the UK, but not for AI. These could take about three years to build and cost about 10% more than energy currently generated from the grid, according to Pritchard.
Co-locating computing where the power already exists, rather than “forcing everything to be greenfield” (the term for underdeveloped sites), is also a way to get AI infrastructure up and running faster, VAST Data’s Abbot said.
Kao Data’s Lamb told CNBC that the speed of implementation will be critical. “Unless fundamental issues around energy availability and pricing, AI royalties and funding for AI developments are not resolved quickly, the UK will miss out on one of the most remarkable economic opportunities of our time and ultimately risks AI becoming an international recession.”
