Christine Casimiro
The US Army’s Next Generation Command and Control (NGC2) prototype is putting a new capability powered by artificial intelligence (AI) to the test.
During the 4th Infantry Division’s (4ID) Ivy Sting 2 exercise, the service trained an AI-aided target recognition system to spot hulks, or old vehicles used as targets, Breaking Defense reported.
The goal: teach the AI to identify a tank and automatically trigger a fire mission, shortening the “sensor-to-shooter” loop. That speed could give US forces a decisive edge in multi-domain operations, where milliseconds matter.
For now, the system can identify a single target, but the next step is teaching it to distinguish between multiple objects on the battlefield.
According to 4ID Commander Maj. Gen. Patrick Ellis, much of the effort focuses on refining and training models so they perform reliably in complex environments.
The system still relies on human oversight. When the AI flags a potential target, a human operator reviews the result before action is taken.
Ellis said the army sees strong potential in the technology and is working closely with industry partners to improve the algorithms and expand their capabilities.
The 4ID is leading the army’s effort to test and develop NGC2 through a series of division-level training experiments known as Ivy Sting and Ivy Mass.
Each iteration adds more complexity and equipment.
The first Ivy Sting exercise began in September 2025, when an Artillery Execution Suite — a new fire control software — was integrated into the NGC2 ecosystem and used in a live-fire test.
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