Data center site selection is the process of identifying and evaluating locations for new data center facilities based on power availability, fiber connectivity, water resources, zoning compatibility, natural disaster risk, labor markets, and tax incentive programs. With the explosion of AI compute demand, data center site selection has become one of the most competitive and time-sensitive activities in commercial real estate.
Data center site selection prioritizes: power capacity and cost (proximity to substations, available megawatts, utility rates), fiber infrastructure (carrier density, latency to major metro areas), water availability (for cooling), zoning and permitting (data center-friendly jurisdictions), natural disaster risk (seismic, flood, hurricane), tax incentives (sales tax exemptions, property tax abatements), and labor market access for construction and operations.
The AI boom has created unprecedented demand for data center capacity. Hyperscale operators and colocation providers are competing for the same limited pool of power-rich, fiber-connected sites. The ability to identify and secure sites faster than competitors is a decisive advantage. AI-powered site selection can screen thousands of parcels against data center criteria in hours — a process that traditionally takes weeks.
Available power capacity is the single most important factor in data center site selection. A hyperscale facility may require 100+ MW of power — equivalent to a small city. AI site selection tools map utility infrastructure, identify substations with available capacity, model interconnection timelines and costs, and flag sites where power can be delivered within the project timeline.
AI data center development refers to the full lifecycle of planning, designing, and constructing data center facilities optimized for artificial intelligence workloads. AI data centers have fundamentally different requirements than traditional facilities — higher power density per rack, more sophisticated cooling systems, and infrastructure designed for GPU clusters rather than conventional servers.
Power analysis for data centers is the process of evaluating electrical infrastructure capacity, utility reliability, interconnection timelines and costs, redundancy options, and energy procurement strategies for current or planned data center facilities. As AI workloads drive power requirements to unprecedented levels, power analysis has become the most critical factor in data center site selection and development feasibility.
AI site selection uses artificial intelligence to identify, evaluate, and rank potential development sites across large geographic areas. By processing thousands of parcels against zoning, environmental, infrastructure, demographic, and financial criteria simultaneously, AI site selection compresses what traditionally takes months of manual research into days.