The U.S. Air Force has completed its second Decision Advantage Sprint for Human-Machine Teaming (DASH 2), an experiment designed to test how artificial intelligence (AI) can improve decision-making in fast-moving combat environments.
Held at the Shadow Operations Center-Nellis in downtown Las Vegas, the two-week exercise brought together operational warfighters, industry partners, and Air Force software developers. The goal: to evaluate AI-enabled microservices that support the “match effectors” function, where commanders determine the best available weapon system to strike a target.
Early results showed AI dramatically increased speed and capacity. Machines generated recommendations in less than 10 seconds and produced 30 times more options than human-only teams. Two vendors delivered over 6,000 solutions for 20 problems in just one hour. Accuracy was comparable to human performance, and in some cases could reach over 90% with minor algorithm adjustments.
“DASH 2 proved human-machine teaming is no longer theoretical,” said Col. Jonathan Zall, head of the Advanced Battle Management System (ABMS) Capability Integration team. “By fusing operator judgment with AI speed, the Air Force is shaping the future of decision advantage in joint and coalition operations.”
The event also demonstrated how co-development with industry accelerates innovation. Companies retained intellectual property rights while the Air Force gained insights into integration requirements for future command and control software.
“This level of output gives commanders options to execute multiple kill chains simultaneously,” said Col. John Ohlund, ABMS director. “It helps illuminate risk, opportunity, and material outcomes in real time.”
The DASH series is part of a broader effort to modernize command and control under the Pentagon’s Combined Joint All-Domain Command and Control initiative. Officials say the findings confirm AI can enhance battlefield performance while keeping human judgment at the center.
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