Topline
A new RAND data center siting rubric helps federal agencies screen and rank potential sites based on energy feasibility.
The U.S. government, spurred by a 2025 executive order, is moving quickly to open federal land for artificial intelligence (AI) data center development and directing agencies to identify suitable sites. But energy availability—not just available acreage—is a binding constraint that will determine which sites can realistically support large-scale AI infrastructure.
RAND researchers evaluated 12 U.S. Department of War sites offered for data center leases, compared them with 17 U.S. Department of Energy sites, and developed a cost model to estimate energy infrastructure expenses across 31 candidate locations. A stakeholder workshop stress-tested these findings and informed public-private partnership guidance.
Key Takeaways
Most sites will require major energy investment.
- Across both departments, nearly every candidate site lacks sufficient existing generation capacity to power a gigawatt-scale data center without significant new infrastructure.
Site rankings shift depending on scale and financing.
- No single site dominates under all conditions. Sites in the southwest perform best for most scenarios, while several northeastern sites consistently rank at the bottom.
Energy costs rival facility construction costs.
- At the gigawatt scale, energy infrastructure expenses are comparable in magnitude to data center construction costs, making energy planning a primary—not secondary—driver of site selection.
Unresolved conflicts can become national security risks.
- A workshop exercise found that community opposition, litigation, and infrastructure disputes at a federally approved data center site could escalate into overlapping legal, political, and security crises that threaten development.
Recommendations
When screening potential sites for development:
- Use a site-screening framework that ranks candidates on energy costs, grid interconnection feasibility, and infrastructure readiness before solicitations are issued.
- Request that bidders describe how they will meet the Ratepayer Protection Pledge—the commitment that data center energy costs will not raise electricity rates for consumers.
When structuring solicitations:
- Treat energy infrastructure as a parallel, coequal workstream alongside civil construction in all requests for lease proposals rather than as a subordinate component to be resolved after a lease has been awarded.
When enabling public-private partnerships:
- Develop formal policy guidelines for data center public-private partnerships covering site-specific engagement, risk allocation, security responsibilities, and decommissioning obligations.
Methodology
RAND researchers applied a previously developed energy suitability framework covering energy supply, energy systems, supporting inputs, environmental conditions, and governance factors to 12 U.S. Department of War sites. They then developed a quantitative energy cost model to estimate the present-value cost of powering a 1-gigawatt data center across 31 candidate sites using four generation scenarios. Sensitivity analyses tested how rankings change under varying assumptions about compute scale, the cost of capital, and cooling requirements. A structured stakeholder workshop with 14 federal and industry participants, including a scenario-based Day After exercise, generated inputs for public-private partnership guidance.
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Citation
RAND Style Manual
Arciniegas Rueda, Ismael E., Kelly Klima, Austin Smidt, Frank Andujar Lugo, Rahim Ali, David Gill, and Jennifer Buckley, AI Data Center Siting on Federal Lands: An Energy View, RAND Corporation, RR-A5050-1, 2026. As of October 2, 2026:
Chicago Manual of Style
Arciniegas Rueda, Ismael E., Kelly Klima, Austin Smidt, Frank Andujar Lugo, Rahim Ali, David Gill, and Jennifer Buckley, AI Data Center Siting on Federal Lands: An Energy View. Santa Monica, CA: RAND Corporation, 2026. .
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