AI Data Center Capacity Forecasting
The Problem
“Forecast data center capacity to guide real estate”
Organizations face these key challenges:
1
Power and interconnection uncertainty makes it hard to align land acquisition, entitlements, and commissioning with real demand
2
Leasing demand is lumpy (hyperscaler step-changes), causing manual models to miss inflection points and mis-time speculative builds
3
Fragmented data (brokers, utilities, permits, construction, tenant signals) leads to stale, inconsistent forecasts and slow investment decisions
Impact When Solved
Shorten planning cycles from quarterly to weekly with automated, market-level capacity forecasts and confidence intervalsReduce stranded land/power and idle capacity by 5–10% through earlier detection of demand slowdowns or supply surgesImprove site selection and capital allocation by ranking submarkets on forecasted absorption, power deliverability, and time-to-revenue