UK AI Data Centres Driven Out of Cities by Power and Land Scarcity
Executive summary
European AI data centre developers are increasingly building facilities away from major cities to secure cheaper land, quicker energy connections, and sufficient power. This shift is seeing a rise in greenfield projects in less traditional locations, although it carries risks of local opposition.
Reporting based on reuters.com
Why it matters
For the UK, this trend highlights the growing pressure on existing urban infrastructure, particularly electricity grids, from AI's vast energy demands. It suggests future AI compute capacity may be sited in regions currently less developed for digital infrastructure, potentially bringing investment but also creating new demands on local energy supplies and potentially impacting environmental considerations.
Sector impact
Analysis by AI Energy Intelligence UK
AI training campuses require vast amounts of electricity, driving the shift towards locations where sufficient power can be secured rather than where demand historically exists. This indicates a significant increase in demand for grid connections in new, potentially less established areas as data centres chase available power.
The pursuit of 'where the power is' for AI data centres could lead to increased pressure on regional grids. While the article doesn't directly address energy security in the UK, the focus on securing large power supplies for AI infrastructure implies a need for robust and reliable energy generation and transmission capacity, which could influence national energy planning.
Commercial real estate firms like JLL and Savills report that core European markets, including London, face land shortages, planning restrictions, and lengthy waits for grid connections. This pushes AI data centre investment towards secondary or tertiary locations where powered land costs are significantly lower, impacting development strategies for major tech companies and infrastructure providers.
Key statistics
Figures as reported by reuters.com. See original source for context.
Quotations
"The determining factor is increasingly where sufficient power can be secured, rather than simply where demand exists."
"Data centres are being brought to where the power is, not the other way around."
"Europe's core markets will remain critical because enterprise demand isn't going anywhere."
"Hyperscale AI infrastructure requires a completely different scale of power and land."
"London has already seen significant digital infrastructure development driven by cloud and has other asset classes competing for space leading to high land prices. Power is now constrained in the key cloud locations across the market."
Long-term implications
The long-term implication is a decentralisation of AI data centre infrastructure across Europe, including potentially the UK, away from traditional tech hubs. This could lead to a more distributed energy load, but also necessitates significant investment in grid upgrades and new power generation in these outlying areas to support the massive energy requirements of future AI workloads.
Frequently asked questions
Why are AI data centres moving away from major European cities?
AI data centres are moving from major cities like London due to scarcity of power and land, seeking cheaper energy, land, and quicker grid connection times in less traditional locations.
How far are new AI data centres from major hubs compared to older ones?
Between 2026 and 2028, the average distance of new sites from a major hub will be 175 kilometres, compared to 46 kilometres for projects delivered between 2022 and 2025.
What is the primary driver for these location changes?
The primary driver is the need to secure sufficient power, as AI training campuses require vast amounts of electricity and water for cooling.
How much does powered land cost in London for data centres?
Powered land in London costs approximately €2.6 million per megawatt of IT load.
Explore related tools
Original source
This story summarises reporting from reuters.com. Read the original for full context.
Read on reuters.comRecommended reports
Independent UK research that expands on the themes in this story.
The environmental cost of AI-generated answers versus conventional search, benchmarked for UK decision-makers. An independent, evidence-based comparison of electricity, water and carbon per query across Google, Gemini, ChatGPT, Copilot, Perplexity and Claude — with forecasts to 2035.
Read the reportThe definitive UK view of AI's electricity, grid and infrastructure impact in 2026. An independent, evidence-based report on demand growth, data centre build-out, AI Growth Zones and the trajectory to 2035 — for UK policymakers, operators and investors.
Read the report
A structured briefing on how artificial intelligence infrastructure is reshaping Britain's power network — from substation bottlenecks to regional investment opportunities and long-term grid risk.
Read the reportGet the UK AI Energy briefing
Analysis on AI, electricity and the UK grid, straight to your inbox.
The measured evidence behind this story
Our reporting sits on top of the UK AI Energy Index — a sourced, dated record of AI and data-centre electricity demand, data-centre development and grid pressure.
View the full index