The emerging autonomous battlefield necessitates a new evolution in geospatial intelligence (GEOINT), termed autonomous GEOINT, to support warfighting effectively. Current conflicts in Ukraine, Gaza, and Iran, alongside the contest in low Earth orbit, demonstrate increased battlefield transparency, compressed time and geographic space, and the impact of low-cost mass systems.
Autonomous systems, increasingly organized into military formations, require machine-readable geographic knowledge to execute missions disconnected from human control. This encoded knowledge, encompassing microterrain, obstacles, routes, and no-strike areas, will enable autonomous formations to predict, solve problems, and adjust behavior. GEOINT professionals must transition from solely providing analysis to encoding geospatial logic for autonomous forces, producing training datasets, geofences, and route-risk models instead of traditional maps. The GEOINT community must develop new concepts and doctrine, accelerate feedback loops, widen its analytical aperture to include LEO and electromagnetic terrain, and adapt training to integrate autonomy, AI, and electronic warfare.
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