Interview Questions139

    Data Center Capex: Build Costs and Time-to-Power

    Data centers cost about $10-12 million per megawatt to build, double for AI, and the returns come from energizing new capacity at a development spread.

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    Introduction

    Data centers are not a buy-and-hold business; they are a capital-deployment business, and the two numbers that govern them are the cost to build a megawatt of capacity and the time it takes to energize it. Get both right and a developer earns a wide spread between development cost and stabilized value. Get either wrong, by overpaying to build or by stranding capital in a project that cannot get power, and the economics collapse. This is why a credible view of any data center platform starts not with its in-place rents but with its cost stack and its development pipeline. A standard facility runs roughly $10 million to $12 million per megawatt of critical load, and an AI-optimized facility can be double that.

    The Cost Stack Per Megawatt

    The defining feature of the cost stack is that the building is the small part. Most of the capital goes into the electrical and mechanical systems that deliver and condition power, not into the shell. Across recent estimates, electrical systems alone account for roughly 40% to 50% of total cost, mechanical systems another 15% to 20%, and the powered shell, the land and base building, only about 15% to 20%.

    Critical Load (Cost per MW)

    The IT power a facility can actually deliver to computing equipment, measured in megawatts, and the denominator against which development cost is quoted. Stating cost per megawatt of critical load, rather than per square foot, normalizes for the fact that a data center's value is its deliverable power, not its floor area.

    The headline unit is simple: all-in development cost divided by the critical megawatts the facility can deliver. Every cost comparison and pipeline estimate reduces to it, which is why a banker quotes a build in dollars per megawatt before any other metric.

    Cost per MW=Total Development CostCritical MW\text{Cost per MW} = \frac{\text{Total Development Cost}}{\text{Critical MW}}

    A conventional shell-and-core build still lands near $10 million to $12 million per megawatt in most United States markets, but the modern specification has pulled away from it. Cushman & Wakefield's 2026 development cost guide puts all-in greenfield development for the newest United States and Canadian facilities at an average of $17.6 million per megawatt excluding chips and GPUs, a 21% rise per megawatt in under two years, and CBRE's midyear 2026 outlook puts the most demanding high-density builds at $14 million to $16 million. Push into liquid cooling and the highest power densities and the figure reaches $20 million per megawatt or more.

    Cost componentShare of totalNote
    Electrical systems40% to 50%Transformers, switchgear, UPS, generators
    Mechanical / cooling15% to 20%Chillers, air handling, liquid cooling
    Powered shell (land + building)15% to 20%The traditional "real estate" piece
    Other (fit-out, fees, contingency)RemainderRises sharply for AI density

    Land, often assumed to be the main cost in real estate, is a modest line item in the total, but the ground that matters is repricing fast. Cushman & Wakefield put powered land in primary United States markets at an average of $584,000 per megawatt in 2026, roughly 51% above the prior year, because what a buyer is really paying for is an interconnection position that happens to come with dirt attached. The point for a banker is that data center development is an electrical and mechanical engineering project wrapped in a real estate envelope, which is why it behaves so differently from the hyperscale, wholesale, and retail segments' traditional-property comparables.

    Why Costs Have Surged

    Two forces have driven the cost surge. The first is sheer demand for specialized equipment: lead times for transformers, switchgear, and generators have stretched to two years or more, and that scarcity feeds straight into price. The second is the density of AI hardware, which demands far more power distribution and cooling per square foot than any prior generation. Together they explain why the cost of a megawatt has run up more than a fifth in under two years, and why cost discipline has quietly become a real competitive differentiator between platforms.

    The Equipment Bottleneck Behind the Timeline

    The scarcity is most acute in the electrical gear that makes up the largest slice of the budget, and it has become a binding constraint in its own right. Wood Mackenzie's lead-time survey puts large power transformers at roughly 128 weeks, about two and a half years, with generator step-up units near 144 weeks and some orders quoted four years out. Prices moved with the scarcity: unit prices are up about 77% for power transformers since 2019, and some classes of distribution transformer as much as 95%. Because a site cannot energize without this equipment, the supply chain now gates delivery as tightly as the interconnection queue does, and the two delays compound rather than overlap. Industry analysts estimate that 30% to 50% of the capacity planned for 2026 will slip to 2028 as a result, though the scale of that slippage is disputed.

    For a developer, this turns procurement into a strategic function: ordering long-lead equipment years ahead, sometimes before a site is permitted, and treating a secured transformer slot much as it treats a secured megawatt of power. That advantage does not show up in a rent roll, but it is worth as much as a queue position.

    Capex at Platform Scale

    Because returns come from continuously building, the leading platforms run enormous, sustained capital programs, and those programs keep getting larger. Equinix spent roughly $3.4 billion of total capital expenditure in 2024 and about $4.3 billion in 2025. Reporting second-quarter 2026 results, it guided 2026 capex to $5.0 billion to $6.0 billion and set an annual range of $5 billion to $7 billion for 2027 through 2029, roughly double what it spent two years earlier. That is not a one-time build; it is a treadmill, and the platforms that can fund it cheaply win.

    Cost by Platform and Geography

    The cleanest read on what a platform actually pays is its own pipeline disclosure. Digital Realty entered the second half of 2026 with roughly 1.4 gigawatts under construction, a pipeline it sized on its second-quarter earnings call at about $20 billion of total cost, around 63% pre-leased, at an expected stabilized yield near 11.5%. Divide cost by capacity and the implied build cost is close to $14 million per megawatt, far above a conventional shell-and-core build and a direct reflection of how far AI density now dominates the pipeline. That cost, and the pace at which each platform can deploy it, is what the market is really valuing when it prices the data center REITs.

    Time-to-Power and the Development Spread

    Cost is only half the equation. The other half is time-to-power, the years it takes to actually energize a site, which the power constraint article covers in depth. The reason time matters so much is that the entire return thesis is a development spread: build at a cost, lease at a rent, and capture the gap between the development yield and the cap rate at which the stabilized asset trades.

    Development Yield=Stabilized NOITotal Development Cost\text{Development Yield} = \frac{\text{Stabilized NOI}}{\text{Total Development Cost}}

    If a developer builds at an 8% development yield, at the conservative end of what the large platforms are currently underwriting, and the stabilized asset trades at a 6% cap rate, the spread between them is the value created, and it can be substantial on a multi-hundred-million-dollar facility.

    Every year of delay in securing power pushes out the rent, raises the carrying cost of the capital already sunk, and erodes the spread. Time-to-power is therefore not a side issue; it is the variable that determines whether the development spread is real or theoretical, and it feeds directly into the valuation of any data center.

    The other side of that risk is absorption: whether the capacity is spoken for before it energizes. The single best signal is the pre-lease rate, the share of a new build's capacity already committed under signed leases at the point of delivery.

    Pre-Lease %=Committed Capacity (Signed Leases)Total Capacity\text{Pre-Lease \%} = \frac{\text{Committed Capacity (Signed Leases)}}{\text{Total Capacity}}

    A facility delivering fully pre-leased earns its development yield from day one, while a speculative build that energizes empty carries its cost basis with no income until tenants sign, which is why lenders and equity partners watch the pre-lease rate as closely as the cost per megawatt.

    The Question the Capex Math Reframes

    The capex math reframes the central question. It is no longer "what does this asset yield" but "how much capital can this platform deploy, at what cost per megawatt, how fast can it energize, and what spread does that create."

    Development Yield

    A project's stabilized net operating income divided by its total development cost, expressed as a percentage. It is the developer's return on the cost to build, and the gap between it and the cap rate at which the finished asset trades (the development spread) is the value a developer creates by building rather than buying. Its relationship to the prevailing cap rate environment is the lens through which the whole sector should be read.

    Strip the sector down to its economics and a data center is a capital-deployment machine, not a building: power and cooling systems, not the shell, consume the budget; AI roughly doubles the cost per megawatt; and the leading platforms spend billions a year because the return comes from building at a development yield and capturing the spread to the cap rate, not from collecting rent on what already exists. The variable that decides whether that spread is real or theoretical is time, both the years to energize and the years to procure the equipment, which is why a platform's edge ultimately rests on three things the income statement does not show: a low cost basis, secured power, and a cheap cost of capital to fund the treadmill.

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