Choose an AI data-center location by proving that the site can receive the required power on a credible schedule, then checking that its cooling, water, connectivity, land, permits and resilience fit the workload. A nearby power line or a cool climate is not enough: feasibility depends on what the utility can deliver to the specific site, when it can deliver it, and what the project will require to operate and expand.
What should you decide before comparing locations?
Start with the facility you intend to build, not a list of supposedly ideal regions. A training campus with high-density racks and a phased buildout has different power, cooling, network and land needs from an inference facility serving users who need low latency.
- Workload: training, inference, or a mix; where users and data sources are located; and how sensitive the workload is to network delay.
- Capacity and ramp: expected IT load, when each phase must be operational, and the expansion horizon.
- Rack density and cooling: expected density, intended cooling approach, and flexibility for future hardware.
- Availability and resilience: uptime objectives, redundancy, backup arrangements and disaster-recovery needs.
Use these assumptions consistently for every candidate. ASHRAE’s AI Data Center Energy Performance Framework recommends matching site planning to workload requirements and future density.
Can the site actually get enough power, on time?
Power delivery and schedule are the first hard tests. ASHRAE advises prioritizing power availability and grid capacity early because utility constraints and interconnection timelines can determine feasibility and schedule risk. The key evidence is site-specific confirmation from the utility or transmission operator—not the apparent closeness of a substation or transmission line.
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Ask for written power and schedule evidence
- How many megawatts are available at the required location, and how much is committed to other customers?
- What is the interconnection study status, and what delivery date is supported by the current process?
- Which network upgrades are required, when will they be completed, and who is responsible for their cost?
- Are transformers and switchgear available on the construction schedule?
- What are the expected energy cost and emissions profile, and how might either change over the project’s operating life?
Distinguish indicative capacity from a firm allocation and a planned date from a deliverable date. Include utility expansion plans and grid constraints in the assessment. If considering on-site generation or storage, assess its permits, fuel or other resource needs, cost, emissions, operating model and connection requirements; do not treat it as an automatic substitute for a workable grid plan.
Will cooling work with local climate and water conditions?
Cooling is a local energy-and-water decision. Temperature and humidity affect cooling demand and design, while water supply and wastewater rules constrain which systems are practical. USGS explains that water-based cooling can reduce electricity use while increasing water use, and that hotter conditions can increase cooling demand. Compare both resource effects for the proposed workload and design rather than using “cool climate” as a stand-alone location rule.
Check the site’s operating conditions
- Model expected ambient temperature and humidity against the intended IT load, rack density and cooling design.
- Ask the water supplier to confirm available volumes, delivery timing, infrastructure requirements and any constraints.
- Establish water-stress and sustainability considerations for the source, not just whether a connection exists.
- Confirm wastewater discharge capacity, applicable requirements and the permits needed.
- Compare cooling alternatives on both electricity consumption and water use.
ASHRAE identifies thermal guidance, including material from TC 9.9 and its Datacom resources, as relevant to cooling design. The applicable design envelope should be established for the equipment and operating plan rather than inferred from a regional average.
How close does the site need to be to users and network hubs?
Connectivity requirements depend on the workload. A facility serving latency-sensitive inference may need different proximity and network characteristics from a large training site whose primary demands are power and data movement. Set a project-specific latency tolerance, then ask network operators to document available fiber and mobile coverage, route diversity, planned upgrades and delivery commitments.
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Do not assume that a nearby fiber route means the site has capacity, diverse paths or a committed connection. Verify the end-to-end network design and confirm that separate routes are genuinely independent where redundancy is required. The UK AI Growth Zone criteria ask applicants for operator letters documenting current coverage and planned extensions; they do not establish a general latency threshold for data centers.
Is the land buildable, expandable and approvable?
Land is technically useful only if it can be controlled, developed and connected on the project’s schedule. Confirm contiguous developable area, title or other site control, zoning compatibility, construction access and logistics, and room for the intended expansion. Check environmental constraints and the likely path through planning, environmental review, water and discharge permits, and other local approvals.
Identify the responsible agencies, decision points and schedule dependencies early. Engage local authorities and residents on likely concerns such as power demand, water use, noise, visual effects and land use; document local benefits and workforce considerations alongside impacts. Local acceptance is not a substitute for permits, but unresolved community concerns can affect the project’s delivery path.
What hazards and resilience risks should you screen?
Screen the actual parcel for flood, wildfire, seismic and other relevant local hazards. These can affect continuity, insurance, facility design, approvals and schedule. Regional maps are useful for initial screening, but they are not a parcel-level environmental or regulatory assessment.
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For each candidate, assess independent power, cooling and network paths; backup systems; disaster-recovery arrangements; and whether staff and emergency services can reach the site under adverse conditions. Resilience should be evaluated against the project’s availability target rather than treated as a generic feature.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you compare candidate sites?
First apply pass/fail tests for deliverable power and timing, and for workable cooling, water and permitting. Only then score the remaining trade-offs. Use the same workload and schedule assumptions for each candidate, and record the evidence and confidence behind each score.
| Comparison area | Evidence to compare |
|---|---|
| Power | Confirmed megawatts, firmness of allocation, interconnection date, required upgrades, equipment lead times, energy cost and emissions profile. |
| Cooling and water | Fit with temperature and humidity, water source and sustainable volume, water stress, discharge capacity and approvals, and expected electricity–water trade-off. |
| Connectivity | Fiber providers, route diversity, upgrade commitments, and latency to users and network hubs. |
| Land and delivery | Developable acreage, site control, zoning, construction logistics, expansion space and schedule confidence. |
| Risk and resilience | Flood, wildfire, seismic and other hazards; redundant power, cooling and network paths; and emergency access. |
| Regulatory and community | Permit path, environmental review, local support, noise and visual effects, water and grid impacts, workforce and local benefits. |
| Economics and flexibility | Land and infrastructure costs, incentives and their conditions, phased growth, and adaptability to changing AI hardware density. |
Do not let attractive land costs or incentives compensate for a failed hard constraint. State what is confirmed, what remains conditional and what depends on an upgrade, permit or future commitment.
Which published thresholds apply only to particular programs?
Some published numbers are requirements for defined policies or programs, not universal engineering minimums:
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- The UK Department for Science, Innovation and Technology’s AI Growth Zone application criteria, accessed October 4, 2026, require evidence of at least 500 MW of power access by 2030, sufficient water for 500 MW of AI infrastructure, at least 100 acres available by 2028, and planning consent or a deliverable route by 2028. These thresholds and dates apply to that program.
- U.S. Executive Order 14318, dated July 23, 2025, defines a “Data Center Project” for its stated purposes as a facility requiring greater than 100 MW of new load for specified AI activities. That is the order’s definition, not a general design threshold.
Check current program criteria, incentives, legal status and location-specific utility, water and permitting conditions before relying on them for a project decision. USGS’s 2026 synthesis discusses energy and cooling considerations and includes a spatial analysis covering Western U.S. states and Alaska; it does not rank optimal locations, and its page cautions that reporting varies and some statistics may be outdated.
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