AI is changing how data center sites are found, screened, and designed. More data layers are available than ever, from grid and fiber to zoning, water, and community signals, and AI can now read, analyze, and structure information from planning documents, regulations, and local context for a site in hours instead of weeks. This also opens new possibilities in regions where data has traditionally been scarce, fragmented, or hard to access. As a result, site selection workflows are being rebuilt from the first screening of incoming land to the due diligence decision.

In this session, we will share what is new in AI-driven site selection: which data layers matter most today and where gaps remain, how teams can build a reliable view of a site even where local data is limited, and how to keep findings specific to each site, traceable to their sources, and reviewed by the people who know the market.