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Home Artificial Intelligence

US, Allies Test AI-Enabled Human-Machine Teaming in Coalition Battle Management Sprint

by Kristen Smith
January 6, 2026
in Artificial Intelligence, News
Artificial intelligence. The US, Canada and the UK participated in DASH 3.

The US, Canada and the UK participated in the 2025 Decision Advantage Sprint for Human-Machine Teaming.

The U.S. Air Force has completed a coalition experiment testing how artificial intelligence can support human decision-making in battle management, bringing together operators from the United States, Canada and the United Kingdom. Conducted during the 2025 Decision Advantage Sprint for Human-Machine Teaming, known as DASH, the effort evaluated how AI-generated recommendations could accelerate command and control decisions in simulated combat scenarios, the Air Force said Monday.

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  • How Was AI Used to Support Battle Management Decisions?
  • What Did the Experiment Reveal About Human Trust in AI?
  • Why Was Coalition Participation Central to DASH 3?

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The latest iteration, DASH 3, was led by the Advanced Battle Management System Cross-Functional Team and executed at Shadow Operations Center–Nellis in Las Vegas in partnership with the Air Force Research Laboratory, the U.S. Space Force and allied operators.

US, Allies Test AI-Enabled Human-Machine Teaming in Coalition Battle Management Sprint

The 2026 Defense R&D Summit on Jan. 29, hosted by the Potomac Officers Club, convenes defense leaders, researchers and innovators to examine how emerging technologies—such as artificial intelligence and human-machine teaming—are influencing the future of warfare. Register now to learn from key decision-makers and pioneers shaping the defense landscape.

How Was AI Used to Support Battle Management Decisions?

During DASH 3, six industry teams and an innovation team from the 805th Combat Training Squadron worked alongside coalition operators to test AI-enabled tools designed to generate multiple battle courses of action. The tools were used to explore decision options across long-range strike planning, electromagnetic battle management, space and cyber challenges, and agile combat employment scenarios.

An Air Force official said the systems were able to generate multiple viable courses of action in seconds, compared with minutes using traditional methods. Machine-generated recommendations evaluated factors such as risk, fuel, timing, force composition and routing, while human operators retained decision authority.

What Did the Experiment Reveal About Human Trust in AI?

Participating operators reported increased confidence in AI tools as the sprint progressed. Rather than replacing human judgment, the systems provided starting points that operators could refine, according to U.S. Air Force First Lt. Ashley Nguyen, a DASH 3 participant.

Preserving human control is an approach consistent with broader Air Force guidance that emphasizes human oversight for high-risk operational decisions.

Why Was Coalition Participation Central to DASH 3?

Operators from Canada and the United Kingdom participated directly in the experiment, testing how AI-enabled decision tools could function in coalition command-and-control environments. According to the Air Force, the unclassified structure of DASH lowered barriers to allied participation and allowed interoperability considerations to be tested early.

Lessons from the 2025 DASH event will inform future experiments planned for 2026, as the service continues to refine the integration of AI into command-and-control operations.

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