Over the past few years, the build-out of large-scale data centres and supporting infrastructure in both the United Kingdom and the United States has accelerated significantly. The convergence of cloud computing, artificial intelligence (AI), hyperscale operators, edge computing, sustainability mandates and regulatory recognition has created what many are calling a data-centre boom.
This blog dives into what’s driving the build-out in the UK and US, examines the similarities and differences between the two markets, highlights key challenges, and offers insight into what the future may hold. We’ll also include a top 15 FAQ section to answer common questions that stakeholders—from developers to infrastructure investors—are asking.
Demand for computational capacity has soared with the rise of large-language-model training, AI inference, and growth in cloud services. According to McKinsey & Company, global demand for data-centre capacity could grow at around 19-22 % per year between 2023 and 2030, with a scenario of up to 27 % growth.
In the US, the research arm of Deloitte found that the AI economy demands scaling of data-centres, grid capacity and supply-chains
This means more data-centre build-out to host hyperscale cloud, colocation, edge computing and AI-specific infrastructure.
In the UK, the government has designated data centres as “Critical National Infrastructure (CNI)”, recognising their strategic importance for the digital economy and national security. With that recognition comes streamlined permitting, policy support and prioritised energy/power access.
Similarly, in the US, federal and state-level incentives and the need for domestic digital infrastructure are driving decisions around build-out and location.
Major players such as Amazon Web Services (AWS) in the UK have committed multi-billion-pound investments. For example, AWS pledged roughly £8 billion in UK data-centres over the next five years. These kinds of commitments both reflect and accelerate infrastructure expansion.
In the US, hyperscalers and GPU-cloud providers are scaling up large facilities to meet AI workload demands.
While major data centres remain critical, the build-out of edge data-centres (smaller facilities closer to users) is also growing. The UK-market commentary shows that edge facilities help address latency, data sovereignty, and local demand.
In the US, similar trends apply, as enterprises push compute closer to the point of generation/use (IoT, 5G, real-time applications).
As data-centre demand increases, so does power consumption, cooling demands and environmental scrutiny. UK reports note that data-centre power usage could increase substantially in the coming decade
Site selection, access to renewable power, efficient cooling (dry-cooling, heat capture) and grid connection are now key factors in build-out decisions.
Land availability, building permits, availability of power and telecom connectivity, as well as proximity to talent (for operations, networking, cooling engineering), all factor into where new centres get built
In some UK regions, old industrial sites are being repurposed for large-scale data-centre campuses
In the UK, the data-centre build-out is highly influenced by national policy (e.g., infrastructure designated as CNI) and a concentration of investment in certain regions (London, southeast England, northern “AI growth zones”). For example, planning applications in the UK rose by over 40 % in one year
On the flip side, the UK faces power-cost challenges, land constraints (especially in green-belt/regional zones) and the need to balance expansion with sustainability.
In the US, scale is larger: massive hyperscale campuses, data-centre campuses drawing hundreds of megawatts of power (even gigawatts in some cases). Deloitte notes that the largest US data-centres under planning could require up to 2,000 MW (2 GW) of power.
Also, the US market is more geographically dispersed, with build-out in multiple states, each with differing regulatory/power/tax incentives. Energy costs, water use, sustainability concerns and state-level policy also play major roles.
Both markets face key shared issues: securing power/energy access, cooling and water usage, environmental and planning consent issues, supply-chain for construction (racks, power equipment, network fibre), availability of skilled labour, and managing real-estate and infrastructure risk.
Data-centre growth demands large amounts of power. In the UK, especially, this creates pressure on the national grid and may constrain future build-out if not matched by energy infrastructure. For example, the UK blog noted a potential six-fold increase in power usage for data centres over a decade.
In the US, large data-centres may demand 100s of megawatts; states and utilities must ensure sufficient capacity and resilience. Failure to do so can delay projects.
Cooling, water usage, and carbon footprint are under scrutiny. Some centres must commit to renewable power or low-carbon design. As noted in the UK construction-boom report, if sustainability doesn’t keep up with expansion, the sector could face reputational risk.
Cooling, water usage, and carbon footprint are under scrutiny. Some centres must commit to renewable power or low-carbon design. As noted in the UK construction-boom report, if sustainability doesn’t keep up with expansion, the sector could face reputational risk.
The pace of change (AI hardware, cooling technology, power density) means that facilities risk becoming obsolete or requiring retrofit. Data-centres designed today must anticipate future workloads, including AI/GPU clusters, edge computing, and high-density racks.
Although demand is high, overbuilding in certain regions could risk excess capacity or under-utilisation. Proper demand forecasting, tenant commitments (hyperscalers, cloud providers) and flexible design are key.
Secure grid connection, evaluate renewable power options, plan for efficient cooling (air-, water-, dry-cooling), design for high-density racks.
Use modular facility construction, room for expansion, and future-proofing for higher power densities (e.g., GPU clusters, rack densities).
Balance low-cost land/power with proximity to network fibre and latency-sensitive users (for edge). Consider the regulatory environment, permitting speed, and local incentives.
Design for renewable power, energy efficiency (PUE optimisation), waste heat capture, and water-conservation measures. These reduce risk and enhance investor/tenant appeal.
Secure anchor tenants (hyperscale cloud, AI model-trainers) to de-risk build-out. Collaborate with local utilities, governments and real-estate partners.
Implement real-time monitoring for power, cooling, network, and security. Use analytics to optimise efficiency and detect issues early.
Stay aware of changing regulations (data-sovereignty, critical-infrastructure designations, sustainability mandates) and align build-out accordingly.
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The surge in data-centre and infrastructure build-out in the UK and US is driven by an unprecedented convergence of demand (AI, cloud, edge), strategic policy support, major capital investment and evolving technology. While the opportunity is massive, so too are the challenges: power, cooling, land, sustainability, technological change and operational complexity.
For investors, operators, governments and infrastructure planners, the path forward involves aligning design, location and operations with future-proof demand, ESG requirements and regulatory realities. Done well, the boom in data-centres can underpin the next phase of the digital economy.
Because the UK government has formally designated data centres as Critical National Infrastructure (CNI), recognising their role in powering the digital economy and safeguarding data.
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Extremely significant: large new facilities may require hundreds of megawatts of power, and advanced cooling systems (even dry-cooling) to manage heat and efficiency.
They must manage high energy consumption, water usage, heat waste, carbon footprints, and align with renewable power sources — failure to do so poses regulatory and reputational risk.
The UK market is tighter geographically, policy-driven (CNI), more constrained in land/energy, and heavily influenced by European/international players. The US market is larger, more dispersed, with greater scale and diversity, but also greater regional variation in cost/incentives.
Because they require huge capacities (AI, cloud), anchor investments, and set the pace for facility scale, design and technology. McKinsey identifies hyperscalers as dominating AI-ready capacity demand.
Edge data-centres bring compute and storage closer to end-users/devices, reduce latency, support IoT/5G/real-time applications, and relieve pressure from centralised mega-centres.
Critical factors include availability of power/fibre, land cost, permitting speed, environmental constraints (green-belt, water usage), and proximity to major network hubs/users.
Yes — if demand forecasts are overly optimistic or new centres lack tenants, the risk exists of under-utilisation, which can impact returns.
Very important — securing anchor tenants (cloud providers, colocation customers) reduces vacancy risk, helps justify build-out and financing.
Higher rack densities, specialised cooling (liquid cooling, immersion cooling), more efficient power usage, modular designs, and automated operations (AI/ML in DCIM).
They include zoning/land-use consent, environmental impact (noise, water, heat), planning on green-belt land (in the UK), grid connection approvals and data-sovereignty/data-localisation rules.
They can place large new loads on the grid, require dedicated substations or power lines, may require renewable or battery backup, and can affect local utility planning and rates.
In the UK, regions with power and planning support, AI growth zones, and repurposed industrial sites. In the US, states with low power costs, tax incentives, hyperscale clusters, and strong fibre connectivity.
Focus on location/power availability, tenant demand/commitment, scalability and modularity, sustainability (renewables/efficiency), regulatory environment and operational excellence.
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