Air Force Tests AI for Battlefield Target Recommendations
Revolutionary Exercise Accelerates Decision-Making in Simulated Combat
The U.S. Air Force is pushing the boundaries of modern warfare by integrating artificial intelligence into critical combat planning. A recent four-day exercise, dubbed “Experiment 3,” showcased AI’s capability to recommend targets during high-pressure scenarios, aiming to significantly speed up military decision-making.
Pioneering AI in Command and Control
The 805th Combat Training Squadron, operating as the Shadow Operations Center — Nellis battle lab, spearheaded the novel exercise. Participants leveraged AI software to enhance their targeting processes within a simulated battle environment. This initiative represents a significant step in developing a more agile and automated “kill chain.”
“We’re not just testing software, we’re challenging assumptions, validating tactics and shaping the operational architecture the Air Force and our allies will rely on in future conflicts,” stated Lt. Col. Shawn Finney, commander of the 805th. “This was a proving ground for the kill chain of tomorrow.”
The exercise focused on creating a resilient, data-driven command-and-control pipeline. The AI system provided real-time recommendations to dynamic targeting teams, a move designed to reduce the cognitive burden on human operators.
Maven Smart System Powers AI Targeting
The artificial intelligence software employed during the experiment was the Maven Smart System. Developed to ingest vast amounts of data and produce rapid analyses, it prioritizes targets effectively. This technology is crucial for modern military operations, where rapid situational assessment is paramount.
In 2023, the U.S. military spent an estimated $1.8 billion on artificial intelligence research and development, highlighting the growing investment in AI capabilities for national security (CSIS, 2023).
Human and AI Collaboration Proves Complementary
Observer teams noted the synergy between human judgment and AI-generated recommendations. While AI provided efficient data processing, human insights, including intuition and situational awareness, were found to be complementary. This feedback was instrumental in refining the AI algorithms for greater accuracy.
Lt. Col. Shawn Finney emphasized the strategic value of such trials. “The [battle lab] enables a ‘drive-before-you-buy’ approach, ensuring the tools we field are effective, intuitive and ready for the fight,” he commented. “This experiment brought us one step closer to the future of command and control.”
