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Estimate an AI data center in separate cost layers: site and building, electrical and cooling infrastructure, utility and energy assets, servers and networking, then ongoing operation and equipment refresh. The total depends on which layers you include. A shell-and-core benchmark is not an all-in AI facility budget, and a per-megawatt figure is useful only when its scope, geography, and load basis match your project.
Define what “total cost” means before estimating
There is no single standard boundary for the cost of building an AI data center. One estimate may cover only the shell and core; another may include utility works and a tenant’s servers; a third may include power generation, financing, and years of operation. Treating those numbers as interchangeable can leave major costs out or count them twice.
Start by choosing the estimate you need. For a construction budget, include the site, building, and facility systems in the project boundary. For a complete, ready-to-run facility, also include the tenant’s IT equipment, networking, and any energy infrastructure the project must fund. For a lifecycle ownership estimate, add recurring costs and hardware replacements over a stated period.
- Shell and core: the building and base building infrastructure, as defined by the benchmark being used. Tenant technology fit-out may be excluded.
- Facility development: site development and facility construction, potentially including mechanical, electrical, and cooling systems. Check whether utility works are included.
- Tenant-fitted AI facility: facility development plus servers or accelerators, network equipment, and other tenant technology.
- Lifecycle ownership: initial capital expenditure (capex), recurring operating expenses (opex), and replacements during a defined operating horizon.
Record the estimate boundary in one sentence. For example: “This is a greenfield U.S. estimate for 100 MW of IT load, including tenant servers and networking, but excluding offsite generation, financing, and operating costs.” The example is a format, not a project price. Naming exclusions is as important as naming included costs.
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Establish the project basis and load metric
Before pricing anything, describe the facility that the estimate represents. A cost-per-megawatt figure has little meaning without the load basis: IT load is the power capacity available to computing equipment, while facility power also includes overhead such as cooling and electrical losses. A gigawatt of IT power is therefore not the same capacity as a gigawatt of total facility power.
Write down these assumptions before building the cost schedule:
- Location and market: country, region, and local market. Construction prices, labor, taxes, land, and utility conditions vary by location.
- Capacity: target IT load in MW, or facility power if that is the specified measure. Do not switch between the two when comparing benchmarks.
- Workload and IT design: the intended AI workload and the assumed server or accelerator configuration, network design, and equipment quantities. These choices affect both IT capex and power and cooling requirements.
- Availability and redundancy: the resilience target and design assumptions. Redundant systems can change equipment quantities and facility requirements; obtain project-specific design inputs rather than applying an unsupported generic uplift.
- Cooling and delivery: cooling approach, project stage, and target delivery date. Schedule affects procurement and construction assumptions.
- Project type: greenfield construction or fit-out of an existing building. An existing shell can change the scope, but does not eliminate the need to assess its electrical, mechanical, and cooling capacity.
- Commercial boundary: whether the project bears costs for land, grid upgrades, substations, offsite or onsite generation, storage, financing, taxes, and incentives.
Epoch AI’s modeled 1-GW example is explicitly a stylized U.S. hyperscaler model, not a quote for a specified site. Its authors Amelia Michael and Ben Cottier note that actual costs vary with server choice, facility design, location, financing, and power strategy. That is a useful caution for any project: a benchmark can anchor an estimate, but it cannot substitute for a defined design and local inputs.
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Use separate lines for distinct cost buckets rather than hiding them in one construction allowance. The International Energy Agency (IEA) groups investment as IT capex, non-IT capex, and energy capex. Epoch AI’s modeled upfront cost separately identifies servers, facility, network infrastructure, land, and utility works. These classifications are compatible ways to organize a schedule; choose one structure and make sure every cost is assigned once.
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| Cost line | What to identify and price | Scope questions to resolve |
|---|---|---|
| Land and site | Land acquisition or lease assumptions, site preparation, and access to a powered site. | Is the land included in the construction benchmark? Is a powered-site premium reflected? Are enabling works included? |
| Shell and core | Building and base facility construction, priced against local market and design assumptions. | Is this shell-only, shell and core, or a wider development figure? Does it cover fit-out or only the base building? |
| Mechanical and electrical systems | Facility systems needed to supply and manage the IT environment, including the design’s cooling requirements. | Which systems and redundancies are in the construction scope? Are equipment, installation, and commissioning treated consistently? |
| Grid connection and utility works | Interconnection, substations, and other utility work assigned to the project. | Does the utility or developer pay for each item, or does the data-center project? Is the benchmark inclusive? |
| Energy assets | Generation, batteries or other storage, and transmission or distribution investments if the project bears them. | Are assets onsite, behind the meter, or offsite? Is energy procurement being confused with capital investment? |
| Servers and accelerators | Tenant IT equipment quantities and configuration, priced from project-specific quotations. | What server design and refresh schedule are assumed? Does the facility benchmark exclude tenant technology? |
| Network and connectivity | Network equipment and external connectivity needed for the project. | Is network infrastructure included in the IT estimate or priced separately? Is external connectivity in scope? |
| Operating costs | Electricity, maintenance, labor, taxes, and water over the selected analysis period. | Are these recurring costs being reported separately from upfront capex? What utilization and rates apply? |
For each line, record the quantity, unit rate, source, date, geographic match, and whether the value is a quote, forecast, modeled figure, or benchmark. Flag unquoted items instead of silently assigning them a zero. Add contingency and inflation only after the underlying scope and estimate date are clear, and state their basis in the final estimate.
Use published benchmarks without mixing their scopes
Published figures are useful for checking whether an estimate is in a plausible range, but the figures below describe different boundaries and markets. None is a universal cost per MW for an unspecified AI data center.
| Source and date | Published figure | What it covers—and what it does not establish |
|---|---|---|
| Epoch AI, 2026 modeled example | $37.883 billion upfront capex for a modeled 1-GW-IT-power AI data center: $21.188 billion for servers, $11.433 billion for facility, $4.925 billion for network infrastructure, $0.172 billion for land, and $0.164 billion for utility works. | A stylized U.S. hyperscaler model with specified assumptions, not a site-specific price. It separates major components but does not make the model a universal per-MW quote. |
| Epoch AI, methodology page reviewed in 2026 | $38 billion per GW of IT power: $26 billion for compute and $12 billion for construction. Cost per GW of total facility power is described as typically lower, around $30 billion, because overhead reduces server capacity. | A modeled methodology estimate. Do not substitute the facility-power basis for the IT-power basis or combine this rounded figure with the separate modeled example as though they were one quote. |
| International Energy Agency (IEA), 2025, citing Turner & Townsend (2024) | $6,000 per kW of IT load in some emerging market and developing economies to over $10,000 per kW in many advanced economies. | Combined construction and installations benchmark. It is not a complete AI fit-out price and should not be read as including a full tenant server and network configuration. |
| Cushman & Wakefield (C&W), 2026 | $17.6 million per MW average greenfield development cost for modern U.S. facilities. | A U.S. development average; the guide notes variation by market and workload type. The figure is not a project-specific bid or an all-in lifecycle total. |
| JLL Research, 2026 | $11.3 million per MW average global shell-and-core cost forecast for 2026. | Shell and core only. JLL excludes tenant technology fit-out and says AI infrastructure fit-out can cost as much as $25 million per MW; that upper value is not a standard quote and should not automatically be added to the shell-and-core average. |
| Epoch AI, 2026 modeled example | Approximately $0.907 billion annual operating expenses for its modeled 1-GW facility. | Annual opex in the model, not upfront construction capex. The related annualized ownership result changes with asset-life assumptions. |
Do not resolve the apparent differences by averaging the figures. The IEA construction-and-installations range, C&W U.S. greenfield development average, JLL global shell-and-core forecast, and Epoch modeled AI facility do not cover the same items. They also differ in geography, date, and capacity basis. Normalize only when the definitions match, and preserve the source’s wording and qualifications beside any converted figure.
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Make power access and schedule visible
Power is not just an operating bill; it can affect whether a location is feasible and which capital costs belong in the project. The IEA separates energy capex—generation, batteries, and transmission or distribution—from non-IT facility investment. Keep these energy assets distinct from the building’s electrical systems and from recurring electricity purchases.
JLL Research reports that average grid-connection waits in primary data-center markets exceed four years in 2026. It also describes increased interest in behind-the-meter arrangements and colocated storage. This is schedule context, not a cost-per-MW input: it does not tell you what a particular interconnection, battery, or generation project will cost. C&W notes that powered land can carry a premium over non-powered land, so do not assume two sites with similar acreage have equivalent cost or readiness.
For each candidate site, show the assumed connection path and who pays for each component:
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- Grid connection, utility upgrades, and substation work;
- Transmission or distribution work assigned to the project;
- Onsite or colocated generation and storage, if planned;
- Offsite energy infrastructure or power arrangements included in the project boundary;
- Land premium or other site costs associated with power availability.
Obtain a utility or interconnection study and site-specific power strategy before treating these lines as priced. If those inputs are not available, identify them as open assumptions and create scenarios rather than presenting a single precise total.
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Separate capex from lifecycle ownership cost
Upfront capex answers how much capital is needed to build and equip the facility within the chosen scope. Total cost of ownership (TCO) answers a different question: what the project costs over a defined operating period. State the horizon, discount rate, utilization, electricity price, tax assumptions, and replacement schedule when presenting TCO. Otherwise, two totals can differ simply because they cover different periods or use different operating assumptions.
Epoch AI’s modeled annual expenses include energy, taxes, maintenance, labor, and water. Its example assumes five years for IT equipment and fourteen years for facility assets. Changing the assumed IT lifespan to three years raises the model’s annualized ownership estimate; extending it to seven years lowers it. These are model inputs, not guaranteed replacement cycles or service lives for every installation.
Replacement schedules should follow asset type. The IEA notes that IT equipment can become obsolete four to six years after installation, while transformers typically last 30 years. That contrast is a reason to model separate refresh schedules for computing equipment and long-lived infrastructure, not to apply one blanket lifespan to every asset. Include replacement capex in the year it is expected, and avoid counting it both in an annualized cost and as a separate full replacement allowance.
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Turn the estimate into a usable range
A single point estimate can conceal uncertainty in site access, power delivery, construction pricing, and the IT design. Present low, base, and high cases, with a short explanation of what changes between them. The scenario labels are not substitutes for evidence: each case needs a stated assumption and a corresponding price source or quotation.
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- Set the base case. Use the defined load, design, location, delivery schedule, and cost boundary. Price each schedule line with local construction data, current vendor quotations, site assumptions, and utility inputs where available.
- Set the low and high cases. Vary only material uncertainties, such as powered-site access, local construction conditions, IT configuration, or grid versus onsite power strategy. Do not apply a blanket percentage without a basis.
- Label each number. State currency, estimate date, market, load basis, whether values are actual quotations or benchmarks, and whether taxes, financing, contingency, and inflation are included.
- Show exclusions and unresolved inputs. Identify items not priced, including any uncertain utility works or energy assets. An unquoted item is an uncertainty, not a zero-cost item.
- Keep capex and TCO distinct. Report upfront investment separately from annual operating costs and any lifecycle total, giving the TCO horizon and assumptions.
Public figures can help challenge a draft estimate, but an actual project budget requires local site and utility data, design-level quantities, vendor quotations, and a defined schedule. No benchmark in the table provides all of those inputs for a facility whose location, accelerator configuration, power arrangement, financing, and design have not been specified.
Common estimating mistakes
- Calling shell and core “the cost of an AI data center.” Check whether tenant technology is excluded and add it only from an appropriate project estimate or quotation.
- Comparing IT MW with facility MW. Preserve the denominator used by the source; facility overhead means the measures are not interchangeable.
- Adding unlike benchmarks together. A construction average and a separate fit-out upper bound may differ in market, basis, or scope. Add values only when the items are compatible and non-overlapping.
- Treating an annual operating expense as build capex. Keep recurring costs, upfront capital, and lifecycle replacements in separate lines.
- Hiding power infrastructure inside a generic construction line. Identify whether the project pays for grid upgrades, substations, generation, storage, or transmission.
- Using a global or national average as a local quote. Local land, labor, equipment availability, taxes, incentives, and utility conditions need local evidence.
- Presenting a modeled facility as a universal price. Epoch AI’s example is explicitly stylized; its detailed values are useful as a scope illustration, not as a guaranteed budget for another design.
What a credible estimate should contain
A reader, investor, or project team should be able to understand both the total and how it was assembled. The final estimate should include:
- Project location, currency, estimate date, capacity and whether it means IT load or facility power;
- Workload and assumed server, accelerator, network, cooling, and redundancy design;
- A bottom-up cost schedule for site, facility, utility, energy, IT, and connectivity costs;
- Source and evidence type for every major rate or allowance, including local quotations where obtained;
- Included costs, exclusions, taxes, incentives, financing, contingency, and inflation treatment;
- Low, base, and high cases with the assumptions that drive the range;
- Separate annual operating costs and, if requested, a lifecycle horizon and asset refresh schedule.
When those details are unavailable, present the result as an early-stage range with explicit unknowns. That is more useful and honest than giving a precise per-MW total whose scope cannot be checked.
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