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Data centre construction costs range from a shell-and-core benchmark of $11.3 million per MW to an all-in North American greenfield development average of $17.6 million per MW, depending on what is included. Those are not competing quotes: JLL’s 2026 figure is a global forecast for a specified air-cooled building and excludes land and active IT equipment; Cushman & Wakefield’s 2026 figure covers modern greenfield development in the United States and Canada, excluding chips and GPUs. For a useful budget, define the cost scope, location, power and cooling design, site conditions, and tenant fit-out before applying any benchmark.
What does a data centre construction cost estimate include?
A cost-per-megawatt figure is meaningful only when its cost basket and capacity basis are clear. “Construction cost,” “shell and core,” “greenfield development” and “total project cost” can describe different sets of work. Land, utility connections, site preparation, professional services, active IT equipment and tenant fit-out may be included in one estimate and excluded in another.
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- Site and power access: land, site conditions and the work needed to bring power to the project. Some benchmarks exclude land, utility works and site works, while a greenfield development guide may treat a broader set of development costs.
- Shell and core: the main building and its core infrastructure. This is the basis of JLL’s 2026 global forecast of $11.3 million per MW, which excludes land and active IT equipment.
- Mechanical and electrical systems: equipment and systems needed to support the facility. The precise inclusions depend on the source’s methodology and the project specification.
- Project and construction costs: categories such as architectural finishes, M&E fit-out and equipment may appear in construction indices. Turner & Townsend’s index defines its included categories and exclusions rather than claiming to capture every project cost.
- Contingency and project services: the project’s allowance for uncertainty and services. These are not present in every benchmark; professional services, for example, are excluded from Turner & Townsend’s stated methodology.
- Tenant IT fit-out: servers and other active IT infrastructure are a separate layer in many construction comparisons. JLL says tenant technology fit-out for AI infrastructure can cost as much as $25 million per MW, separate from its shell-and-core benchmark.
These layers are a way to reconcile estimates, not a universal bill of quantities. Do not add a second estimate for a category that is already included, or assume an excluded category costs nothing. Ask the estimator to identify inclusions, exclusions and the capacity denominator for each line.
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What do the major 2026 cost benchmarks actually say?
The most useful published figures in the available data illustrate why scope matters. The table compares their stated bases; it does not convert them into like-for-like prices. Figures are reported as published and checked November 2026.
| Source and figure | Scope and geography | Important exclusions or assumptions |
|---|---|---|
| JLL: $11.3 million per MW forecast for 2026 | Global shell and core; representative single-tenant, 50 MW, air-cooled data centre | Excludes land and active IT equipment; a forecast, not a project quotation |
| Cushman & Wakefield: $17.6 million per MW average in 2026 | Modern greenfield development in the United States and Canada | Chips and GPUs excluded; broader development framing than JLL’s shell-and-core figure |
| Turner & Townsend: 2026 index methodology | Typical 60 MW IT-load, air-cooled, build-to-suit hyperscale data centre | Methodology specifies included construction categories and excludes land, utility works, site works, active IT equipment, abnormal groundworks, client-direct costs, office-fit-out fibre and professional services |
The $6.3 million-per-MW difference between the first two figures is not evidence that one source is wrong or that costs changed by that amount. JLL’s number is a global shell-and-core forecast for a defined 50 MW air-cooled facility. Cushman & Wakefield’s average covers modern greenfield development in the US and Canada and excludes chips and GPUs. Their geography, scope and assumptions differ.
JLL also reports a global shell-and-core trend of $7.7 million per MW in 2020 and $10.7 million per MW in 2025, with $11.3 million per MW forecast for 2026. Read that as the trend in its stated construction-cost basis, not as an all-in project-cost series or a forecast for every market.
Turner & Townsend says its index methodology draws on more than 500 live or recent projects across 62 markets. That is the sample behind the index; it is not a claim that every project in those markets has the same cost or that the index includes every item in an owner’s budget. Its exclusions matter just as much as its sample size.
Why are power and location such large budget drivers?
Power availability affects both where a project can be built and when it can be delivered. It can also require significant infrastructure investment. Cushman & Wakefield reports that power infrastructure averages 21% of total greenfield development cost in its 2026 guide, making it the largest cost category in that breakdown.
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JLL identifies speed to power as the primary site-selection criterion and reports that average grid-connection waits in primary markets exceed four years. That wait is a schedule and delivery risk, not simply an electricity operating expense. A site with a lower apparent land price may not be the better budget choice if power access is delayed or requires substantial additional work.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minutePower-ready land can command a premium. Cushman & Wakefield reports an average value of $584,000 per MW for powered land in primary US markets year to date in 2026—35% above its five-year average and 51% higher year over year. This is a reported land-value figure for the stated US-market context, not a universal land price or a line item to add automatically to every benchmark.
When grid capacity is constrained, JLL describes behind-the-meter generation and colocated battery storage as responses developers are considering. These approaches change the project’s infrastructure scope; they do not make power constraints disappear. The estimate should state whether utility works, on-site generation, storage and associated site requirements are included or excluded.
Geography affects more than land. Labour availability, local supply chains, market conditions and project design all shape the result. In JLL’s 2026 chart, shell-and-core costs for the stated 50 MW air-cooled basis range from $7 million per MW in Mumbai to $18 million per MW in Tokyo. Those figures are market-specific benchmarks, not a ranking that predicts a particular site’s final cost.
How do cooling, building form and AI requirements change the budget?
Cooling and building form must be stated alongside any comparison. JLL’s benchmark identifies a 10% premium for liquid-cooled facilities against its air-cooled model and a 20% construction-cost addition for multistorey facilities in the Americas. Turner & Townsend separately reports a 7–10% average liquid-cooling premium in its US data for facilities with similar IT load.
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Do not average the two liquid-cooling premiums or present one as a correction to the other. They come from different methodologies and comparison bases. For an actual estimate, the design team needs the cooling approach, capacity and building form defined; the published premiums are context, not a substitute for a project-specific scope.
AI infrastructure can make the distinction between building cost and tenant fit-out especially important. JLL’s shell-and-core forecast does not include active IT equipment, while its stated upper cost for tenant technology fit-out of AI infrastructure is as much as $25 million per MW. That separate figure is not an automatic addition to every data centre budget: it describes a possible tenant fit-out layer, not the price of a standard building or a guaranteed cost for an AI project.
A clean comparison therefore identifies whether the headline covers the building only, the facility’s mechanical and electrical fit-out, or also the IT systems that occupy it. It also records cooling type and whether the facility is single- or multistorey. Without those details, an apparently precise per-MW number can conceal a materially different design.
How do labour, equipment and schedule affect the final cost?
Cost pressure can come from labour and supply constraints as well as from the design itself. Cushman & Wakefield attributes increases to skilled-trade shortages, rising wages, supply constraints, land fundamentals and critical component costs. It reports that skilled MEP wages rose by an average of 5% annually from 2021 to 2024.
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JLL reports an average global equipment lead time of 33 weeks and says developers may preorder some materials up to 24 months ahead. It also reports that 57% of data centre projects experienced construction delays of at least three months in 2025. These figures indicate schedule exposure; they do not establish the delay or cost impact for a specific project.
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Long lead times can create decisions earlier in design and procurement, while delays can affect the project’s sequence and delivery plan. A budget review should therefore ask which critical equipment has been specified, whether its procurement timing is reflected in the schedule, and what assumptions sit behind the cost and contingency. No source here supports a single contingency percentage for all facilities.
Cushman & Wakefield says average per-MW construction costs rose 21% since its previous guide, published in the fourth quarter of 2024. This is the change reported within its guide’s basis, not a universal 21% escalation factor to apply to every historical estimate, market or project scope.
How should you compare two data centre cost estimates?
Put the estimates on the same basis before judging which is lower. A short scope check can reveal whether a gap reflects an actual cost difference or simply different assumptions.
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- Define the scope. Label each figure shell and core, construction, greenfield development or total project cost. List the inclusions and exclusions rather than relying on a headline label.
- Check the capacity denominator. Confirm what the “MW” measures and the facility size assumed. Turner & Townsend’s methodology, for example, describes a 60 MW IT-load model; JLL’s cited figure uses a representative 50 MW facility. Do not assume every source defines capacity identically.
- Match geography and date. Keep global forecasts distinct from a North American average or a specific city benchmark, and note the publication year and whether a figure is historical, current or forecast.
- Match the technical design. Record air or liquid cooling, building form, IT load and any other design assumptions the estimates disclose. Apply a published premium only to the basis it describes.
- Check power and site allowances. Ask whether land, powered-land premium, utility connection, utility works, site works and abnormal ground conditions are included. Do not treat these as interchangeable categories.
- Separate building from tenant fit-out. Identify whether active IT equipment, AI tenant technology and related fit-out are included. If they are not, keep them as a separate budget layer.
- Review services and contingency. Confirm whether project services, client-direct costs and contingency are included, and how schedule and procurement assumptions affect them. The sources do not provide one percentage that can safely fill gaps in every estimate.
This comparison is useful for an early feasibility check, but published benchmarks are not project quotations. A project-specific estimate needs a defined site, design, power strategy, procurement plan and scope of work. Where those are not yet fixed, show uncertainty explicitly instead of presenting a benchmark as a precise forecast.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is driving data centre costs in 2026?
In broad terms, the current cost pressure comes from the combined effect of power access and infrastructure, land and market conditions, labour availability, critical equipment and project schedules. Cushman & Wakefield’s 2026 guide reports a 21% rise in per-MW construction costs since its previous guide and identifies skilled-trade shortages, wage increases, supply constraints, land fundamentals and critical components among the drivers.
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John McWilliams, Head of Data Center Insights at Cushman & Wakefield, described the shift this way: “The data center industry is entering a new phase where access to power, land, and skilled labor are increasingly determining where growth can occur.” The practical implication for a budget is that the building specification alone may not explain the cost or feasibility of a site. Power readiness, location and delivery constraints belong in the first round of estimating decisions.
There is no single universal price per MW because data centres differ in location, capacity, cooling design, power readiness and what the published estimate counts. Use the benchmarks as context, keep their scope attached, and compare estimates only after bringing their cost layers and assumptions onto a common basis.
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Does MW in a data centre cost estimate always mean the same thing?
No. A source may state a facility size or an IT-load basis, and the denominator matters when interpreting a per-MW figure. Ask the estimator to define the capacity measure in writing before using a benchmark to compare budgets.
Can a construction cost benchmark tell me the data centre’s annual electricity bill?
No. The figures discussed here are construction or development cost benchmarks, not forecasts of operating expenses. Electricity consumption and its annual cost require separate operating assumptions and are not established by these construction figures.
Should I use an announced project’s MW figure to estimate its construction budget?
Treat it as a starting clue, not a reliable multiplier. Announcements may not disclose whether capacity refers to IT load or another facility measure, and they usually do not provide the land, utility, cooling, fit-out and cost-scope details needed to match a benchmark.
How should a project budget handle schedule uncertainty when lead times are long?
Ask the project estimator and delivery team to identify critical procurement assumptions and explain how schedule risk is reflected in the estimate and contingency. The cited industry data shows meaningful delays and long equipment lead times, but it does not support a universal contingency percentage.
