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Before buying land or ordering servers, prove that the proposed workload can be powered, cooled, connected, expanded and permitted at the required site and schedule. AI training and inference create different demand profiles, while electricity delivery, water, fiber, latency, environmental approvals and community constraints interact. A parcel is not viable because it is inexpensive or near a transmission line; it is viable only when every critical dependency has a credible, dated path to operation.
Start with the workload, not the building
The first design document should describe the services the facility must deliver. Training, batch inference and interactive inference have different utilization patterns, tolerance for delay and storage traffic. Those choices determine the number and type of accelerators, memory, storage, network fabric, cooling approach and expansion sequence. They also determine whether the facility needs steady high utilization or must absorb sharp peaks.
Separate training and inference requirements
- Training: large distributed jobs can run for long periods and require high-bandwidth, low-latency connections between servers. Storage must feed checkpoints and datasets without starving the compute fabric.
- Batch inference: scheduled jobs may tolerate queueing, making it easier to shift work to periods when power or cooling capacity is available.
- Interactive inference: user-facing response targets make geographic latency, network redundancy and predictable capacity central site-selection issues.
Document service-level objectives before selecting equipment: response-time targets, job completion windows, availability, data-residency rules, maintenance windows and the expected mix of workloads. Do not use a generic “AI rack” assumption as a substitute for this profile. The available guidance establishes that workload affects power density, cooling, storage, networking and expansion, but it does not establish one universal rack density or facility size.
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Plan a growth path
Define an initial deployment, a next phase and the physical limits of the site. Reserve space for electrical rooms, substations, generators or other backup systems, heat-rejection equipment, water infrastructure, loading areas and security setbacks. Decide which components can be added without shutting down live capacity. Hardware generations change quickly; a design that fits today’s accelerators but cannot accept a different thermal or electrical profile may strand the building.
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State what “full build-out” means in megawatts of IT load, not only in square feet or server count. Keep the initial and ultimate loads separate in utility discussions so the interconnection study reflects the actual expansion plan.
How much power does an AI data center need?
There is no single answer. Required power equals the IT equipment demand plus cooling, power-conversion losses, pumps, lighting, controls and other facility loads. A useful planning relationship is total facility power = IT power × PUE, where PUE (power usage effectiveness) is a measurement of facility overhead relative to IT energy. The result is a planning model, not a utility commitment; engineers must validate it against the selected hardware, operating temperatures and redundancy design.
Make power a feasibility gate
Ask the utility for written answers to four separate questions: how much firm capacity is available, what network upgrades are required, when those upgrades can be energized, and what conditions could change the date or price. A power-purchase agreement or other energy contract does not prove that local substations, transmission lines or distribution equipment can deliver the contracted energy to the site.
The U.S. Department of Energy has warned that data-center loads are growing, vary by region and can affect regional grids. Loads may also be geographically constrained by latency, leaving fewer locations that satisfy both computing and service requirements. Treat the utility study and its schedule as a critical-path item rather than a later procurement task.
Understand the scale of connection requests
A 2024 report from the U.S. Department of Energy Secretary of Energy Advisory Board describes hyperscale connection requests of 300–1,000 MW or larger, with lead times of one to three years. Those figures describe the requests and period examined in that report; they are not a promise for an individual project. A smaller installation can still face a long queue if local transmission, substation or generation work is constrained.
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The International Energy Agency’s 2025 analysis estimates that grid constraints could delay around 20% of global data-center capacity planned for construction by 2030. This is a location-specific analysis estimate, not a prediction that a particular site will be delayed. Obtain a project-specific interconnection milestone schedule, including study completion, equipment orders, construction, testing and permission to energize.
Design resilience and price exposure
Specify the availability target and the failures the facility must ride through: utility outages, a failed transformer, maintenance on a feeder, fuel interruptions, extreme weather and simultaneous equipment faults. Compare the capital and operating effects of redundant electrical paths, on-site generation, storage or other backup options with the required runtime. Model demand charges, time-varying prices, curtailment provisions and fuel logistics using the tariff offered to the actual site. Do not label a system “resilient” without identifying which failure scenarios it covers.
Cooling and water are coupled decisions
Every watt consumed by IT becomes heat that must be removed. Cooling selection therefore changes electrical demand, usable compute capacity, water consumption, maintenance procedures and the building’s response to weather. The DOE design guide treats IT systems, environmental conditions, air management, cooling and electrical systems, heat recovery and efficiency metrics as one design problem.
Match cooling architecture to the heat load
Begin with the accelerator and server manufacturer’s allowable inlet temperatures, humidity range and liquid-cooling requirements, then model the heat load at normal, peak and failure conditions. Compare air-based, liquid-assisted and other architectures on pumping power, heat-rejection equipment, controls, service access, leak detection and the ability to isolate a failed loop. A design that appears efficient at average load may lack enough heat-rejection capacity during a hot day or while redundant equipment is offline.
Climate affects the hours when outside conditions can assist heat rejection, but climate alone does not determine the best system. Local water quality, discharge rules, available electrical capacity and staffing capability can outweigh a nominal climate advantage.
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Measure energy and water separately
The IEA reports that cooling accounts for about 7% of consumption at efficient hyperscale data centers and more than 30% at less-efficient enterprise facilities. These are sector-level comparisons, not a guaranteed range for a new AI facility. Use them to justify detailed modeling, not to substitute for it.
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DOE defines water usage effectiveness (WUE) as annual site water use in liters divided by annual IT-equipment energy use in kilowatt-hours. Establish a baseline WUE target, identify the water sources included, and meter make-up, blowdown, treatment and other site uses. DOE guidance points to operating-condition control, water-side economizing where the configuration permits, and cooling-tower cycles-of-concentration management as potential measures. Each measure has local operational and regulatory limits.
Verify water availability and constraints
Obtain a written allocation or service commitment from the water provider, including seasonal limits, pressure, quality, drought restrictions, wastewater capacity and connection costs. Confirm whether a proposed cooling system requires potable water, reclaimed water or on-site treatment. Quantify discharge volumes and chemistry before selecting equipment. If water availability is uncertain, preserve a design option that can operate at reduced water consumption, but do not claim zero-water operation without an engineered and permitted solution.
Connectivity determines where workloads can live
Interactive services may require low latency to users, data sources or other computing sites. Training and storage may require sustained east-west bandwidth inside the facility and diverse connections to external repositories. The DOE has identified latency as a factor that can constrain geography.
Audit the actual site, not a marketing map
- Trace existing and planned fiber routes to the parcel and the building entry points.
- Identify carriers that can serve the address, their available wavelengths or ports, repair obligations and expansion lead times.
- Require physically diverse paths, separate entrances and documented failure behavior; two circuits sharing one duct are not independent.
- Measure latency to the intended user regions and to critical storage, cloud or research locations during representative periods.
- Reserve pathways, meet-me space, optical power budgets and equipment-room capacity for future links.
Networking equipment, including switches and routers, is expressly included among covered components in Executive Order 14318. That policy reference does not validate any particular vendor, model or route. Select throughput, port count, optics, buffering, redundancy and support only after the workload and topology are defined.
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Evaluate land, buildings and expansion room
Screen parcels for more than available floor area. Map the constructible envelope, geotechnical conditions, flood and wildfire exposure, heavy-haul access, security setbacks, noise limits, fuel storage areas, water and wastewater connections, and room for substations and heat-rejection equipment. Confirm that construction traffic and permanent equipment can reach the site without route restrictions.
Consider whether the building can be phased. A shell that supports only the first deployment may force a second site when demand grows. Conversely, oversizing every system on day one can create idle capital and additional maintenance. Tie each expansion phase to a utility milestone, cooling capacity, network path and permit condition.
Permitting and community acceptance
Approvals depend on jurisdiction and site. The applicable set may include land-use, environmental, water, air, building, electrical, fire, utility and construction permits, along with approvals for backup generation, fuel, noise, traffic and wastewater. The exact list and timing must be confirmed with local authorities and qualified professionals; no general checklist can replace that review.
Start permitting discovery while the utility study is underway. Ask each authority what information it needs, which reviews can run in parallel, what public notices or hearings apply, and which design changes would restart a review. Document assumptions about water withdrawals, emissions, sound, visual impact, energy infrastructure and construction traffic. Early, factual engagement with the community can reveal constraints that do not appear in a parcel listing.
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PUE and WUE are facility-level indicators, not design substitutes. Define the meters, boundary, reporting period and operating conditions behind every value. Track IT energy, cooling energy, electrical losses, water intake, discharge and reclaimed-water use at a resolution that exposes drift.
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DOE’s efficiency scope also includes air management, electrical-system performance, heat-recovery opportunities and operating controls. Commission sensors and control sequences before accepting the facility, then trend performance through seasonal conditions. If waste heat can serve a nearby use, evaluate temperature, distance, reliability and permitting; treat recovery as an opportunity, not an assumed credit.
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Use the same evidence standard for every parcel. A suggested comparison framework is below; “not stated” means the value has not been established and must not be filled with an assumption.
| Decision area | Evidence to collect | Red flag |
|---|---|---|
| Power | Firm capacity, interconnection scope, energization date, tariff, upgrade cost and backup plan | Only a nonbinding energy contract or a verbal capacity claim |
| Cooling and water | Peak heat load, architecture, climate model, water source, allocation, discharge limits, PUE and WUE method | Cooling selected before heat-load and water studies |
| Connectivity | Carrier list, diverse routes, latency measurements, bandwidth, repair terms and expansion path | One visible fiber route with no physical-diversity proof |
| Land and growth | Constructible area, geotechnical report, equipment yards, security, heavy-haul access and phased capacity | No room for substations, heat rejection or later modules |
| Permitting | Authority-by-authority approval list, dependencies, review durations and public-process requirements | Schedule based on generic national averages |
| Operations | Staffing, maintenance access, spares, monitoring, fuel or water logistics and emergency procedures | Efficiency target without a metering and commissioning plan |
A practical due-diligence sequence
- Freeze the service brief: record workloads, latency, availability, data location, initial IT load and ultimate expansion load.
- Build an hourly load model: include IT, cooling, conversion losses, pumps, controls and backup operating modes; document assumptions.
- Pre-screen geography: remove parcels that fail latency, climate, hazard, access or land-use requirements before paying for detailed studies.
- Open utility studies: request written interconnection scope, milestones, upgrade responsibilities, tariffs and conditions for both initial and ultimate loads.
- Commission water and cooling studies: confirm source, quality, allocation, discharge, drought exposure and peak heat rejection under failure conditions.
- Verify network service: obtain carrier letters, route diversity evidence, latency measurements and expansion commitments for the actual address.
- Map approvals: have local counsel, engineers and permitting specialists identify every jurisdictional review and its dependencies.
- Design a phased concept: reserve physical, electrical, cooling and network capacity for the next deployment without overstating day-one requirements.
- Set go/no-go gates: require credible power delivery, water rights, connectivity, permits and budget contingencies before committing to construction.
What the 2025 federal examples do—and do not—mean
Executive Order 14318, dated July 23, 2025, defines a “Data Center Project” for its purposes as a facility requiring more than 100 MW of new load dedicated to specified AI and related activities. The order also identifies energy infrastructure, backup power, semiconductors, networking equipment such as switches and routers, and data storage among covered components. The 100 MW figure is the order’s policy definition, not a general minimum size for an AI data center.
On July 24, 2025, the Department of Energy announced that Idaho National Laboratory, Oak Ridge Reservation, Paducah Gaseous Diffusion Plant and Savannah River Site were selected to move forward with plans to invite private-sector partners for data-center and energy-infrastructure development. Energy Secretary Chris Wright said, “These sites are uniquely positioned to host data centers as well as power generation to bolster grid reliability, strengthen our national security, and reduce energy costs.” The announcement is a dated federal siting initiative; it does not guarantee power, approvals, economics or project success at those locations, and it does not replace local due diligence.
Common failure modes to catch early
- Buying land before confirming delivery power: a nearby line may lack transformer or transmission capacity, and upgrade timing may exceed the construction schedule.
- Using a PPA as an interconnection guarantee: contracted generation and physical delivery to the parcel are separate questions.
- Choosing cooling by climate label: water rights, discharge, humidity, peak conditions and maintenance may reverse the apparent advantage.
- Counting redundant circuits as diverse: shared ducts, poles, substations or building entrances can create one failure domain.
- Ignoring expansion heat and power: a first phase can consume the reserve needed for the next hardware generation.
- Quoting sector averages as promises: IEA cooling percentages and grid-delay estimates describe broad analyses, not an individual facility.
- Leaving permits until construction: environmental, water, air, land-use and utility reviews can have different dependencies and public processes.
The final decision should be a traceable set of commitments: a workload model tied to equipment, a utility path with dates and conditions, a cooling-and-water design with measured efficiency targets, verified network routes and latency, a buildable expansion plan, and a jurisdiction-specific approval schedule. If any one of those remains an unsupported assumption, the site is not ready for an irreversible construction commitment.
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