Geospatial AI processes satellite, aerial, and sensor-based spatial data to extract actionable intelligence at global scale. The data volume problem is distinctive: commercial satellite constellations (Planet Labs, Maxar, Sentinel) generate petabytes of imagery per day, far beyond human analyst capacity to review. ML models provide the first-pass classification layer that makes this data operationally useful. Applications span agriculture (crop monitoring), defense and intelligence (change detection), climate (emissions monitoring, deforestation), infrastructure (asset mapping), and disaster response (damage assessment).