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.
AI site selection systems ingest data from dozens of sources — GIS databases, zoning maps, environmental records, utility infrastructure data, demographic datasets, and market comparables. They apply configurable screening criteria to filter thousands of parcels down to a ranked shortlist, then produce detailed profiles for top candidates including preliminary financial analysis.
Traditional site selection relies on broker networks, manual parcel research, and sequential analysis. An analyst might review 20-50 parcels per week. AI systems can screen 10,000+ parcels in hours, applying consistent criteria that human analysts might miss under time pressure. This doesn't replace human judgment — it gives decision-makers better data to judge.
Effective AI site selection integrates parcel geometry, zoning and entitlement data, environmental risk layers (flood zones, wetlands, contamination), utility infrastructure (power, water, fiber), transportation access, labor market data, tax incentive zones, and comparable transaction history. The quality of outputs depends on the breadth and freshness of input data.
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.
AI due diligence in commercial real estate uses artificial intelligence to automate and accelerate the research, analysis, and reporting that precedes a real estate investment or development decision. AI systems can process environmental records, zoning codes, title documents, financial data, and market comparables simultaneously — producing comprehensive due diligence packages in hours instead of weeks.
Zoning analysis is the process of evaluating a property's zoning designation, permitted uses, development standards (height, density, setbacks, parking), overlay districts, and entitlement requirements to determine what can be built and what approvals are needed. AI-powered zoning analysis automates the review of complex municipal codes and identifies development constraints and opportunities faster than manual research.