The US Air Force has tested an AI system designed to help warfighters make faster decisions on which threats to engage first in active combat zones.
The four-day evaluation brought together teams from the 805th Combat Training Squadron (CTS), who utilized sophisticated software offering a “novel planning and execution methodology,” one never before executed.
The tool is built on the Maven Smart System, an AI-powered battlefield platform assembled by Palantir for the US Department of Defense. It pulls in data from multi-domain sensor feeds, packaging it into a common, searchable app for commanders and support groups.
During the event, the new air force tech was used for high-stress simulations involving command and control, intelligence, surveillance, reconnaissance, and targeting.
The goal? To see how the platform could reduce cognitive burden in a “Find, Fix, Track, Target, Engage, Assess” (F2T2EA) process, while showing how AI inputs and human decisions can work hand in hand.
The trials concluded with the military confirming the AI’s function to “accelerate decision advantage through the development of a resilient, data-driven, and automated kill chain.”
Observers also tracked how the system performed for future tweaks and upgrades aimed at modernizing command and control approaches.
AI Assists, Humans Decide
Commenting on the test, 805th CTS lead experiment planner Capt. Abby Brown said the event aimed “to measure how the machine could support, not replace, the human in the decision loop.”
“We scaled the scenario to focus less on quantity and more on the accuracy of recommendations. This proved that future operations can rely on distributed nodes while maintaining a common operational picture,” Brown explained.
“These demonstrations exposed operators to new capabilities for future implementation and integration into the warfighting community.”
