Launch of UK’s ‘largest AI supercomputer’ delayed by power supply problems
Datacentre hailed by government was supposed to start operating next year but may be held back into mid-2030s A huge datacentre project hailed by the UK government will miss its launch date next year and could be delayed into the mid-2030s. The site in Loughton, Essex, was described as the country’s largest AI supercomputer when it was announced in 2025, but power supply problems mean it now…
The UK government-backed Loughton datacentre project, touted as the nation's largest AI supercomputer, has seen its launch date postponed to the mid-2030s due to power supply issues. Initially announced in 2025, the site in Essex was expected to start operations next year. However, the project's developers, Nscale, face a significant wait as UK Power Networks (UKPN) reports that the local grid will not be able to meet the datacentre's power needs until the early to mid-2030s.
This setback highlights the energy sector's role as a bottleneck in datacentre development. Despite clearing the scaffolding yard site, Nscale is exploring on-site power generation and accelerating the grid connection process. The UK government's AI strategy, unveiled in 2025, highlighted the Loughton project as a "sovereign AI datacentre."
The datacentre industry is under increasing scrutiny, with Ofgem warning of a backlog of 315 datacenters queuing for electricity connections, totaling 73GW of demand. The Loughton site alone requires up to 90MW of capacity, equivalent to the energy consumption of about 315,000 homes. UKPN, the company connecting the site to the national grid, declined to comment on the specific project but noted that large energy demands often necessitate works on the broader national electricity transmission network.
The National Grid emphasized its ongoing collaboration with stakeholders to expedite connections and foster economic growth.
Written by urgent.news from Guardian Technology's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
