In 2025, the United States Air Force made a significant DASH to AI. The Decision Advantage Sprint for Human-Machine Teaming (DASH) events marked a significant step in integrating artificial intelligence and machine learning into battle management operations, the service announced.
Among the events was DASH 3, which was held at the “unclassified location” of the Shadow Operations Center-Nellis in downtown Las Vegas. It included a series of “groundbreaking experiments” between the U.S. Air Force and coalition partners from Canada and the United Kingdom to test and refine AI’s potential to enhance decision-making, improve operational efficiency, and strengthen interoperability among the partners.
It was led by the U.S. Air Force’s Advanced Battle Management System Cross-Functional Team, and executed in partnership with the Air Force Research Lab’s 711th Human Performance Wing, U.S. Space Force, and the 805th Combat Training Squadron, also known as the ShOC-N.
Rise of Machine Learning
A total of seven teams, six from industry and one from ShOC-N, participated in the exercise to underscore their commitment to advancing future battle management capabilities. The teams tested a range of decision-advantage tools to provide human planners with information and recommendations, including battle courses of action (COAs) with multiple paths.
“The goal of a Battle COA is to map sequences of actions that align with the commander’s intent while overcoming the complexities of modern warfare, including the fog and friction of battle. Examples of Battle COAs include recommended solutions for long-range kill chains, electromagnetic battle management problems, space and cyber challenges, or agile combat employment such as re-basing aircraft,” the Air Force explained.
AI has already been shown to generate solutions faster than human counterparts and with fewer errors. The COAs can also adapt more quickly to unforeseen challenges and provide human operators with diverse strategies that can be acted upon as the situation develops. Beyond accelerating the decision-making cycle, AI can improve the quality of generated solutions, according to the team.
“For example, a bomber may be able to attack from multiple avenues of approach, each presenting unique risks and requires different supporting assets such as cyber, ISR [intelligence, surveillance, and reconnaissance], refueling, and air defense suppression,” explained Col. John Ohlund, U.S. Air Force, ABMS Cross Functional Team lead, noting the flexibility provided by the COA.
“Machines can generate multiple paths, supporting assets, compounding uncertainties, timing, and more,” added Ohlund. “Machines provide a rich solution space where many COAs are explored, but only some are executed, ensuring options remain open as the situation develops.”
The Fast DASH
The speed at which AI can deliver actionable recommendations to humans during critical decision-making moments is especially noteworthy, as the manual creation of COAs, which once took minutes to craft, has been reduced to just seconds.
Such “quick thinking” would provide a “radical advantage in combat scenarios,” the team added.
“I systems demonstrated the ability to generate multi-domain COAs considering risk, fuel, time constraints, force packaging, and geospatial routing in under one minute,” said Ohlund. “These machine-generated recommendations were up to 90% faster than traditional methods, with the best in machine-class solutions showing 97% viability and tactical validity.”
Many battles were lost not because of poor planning – although that has certainly been the case – but as much because of a failure to adapt. AI could help determine the COA in real time.
The exercises indicated that humans could generate COAs in approximately 19 minutes, but only 48% of the options generated were considered viable and valid. Generating multiple COAs could improve decision-making speed.
“We understand that the next conflict cannot be won alone without the help of machine teammates and supported by our allies. DASH 3 demonstrated the value of these partnerships through our work together in a coalition-led simulated combat scenario. The tools we tested are vital for maintaining a decision advantage, and we look forward to expanding this collaboration in future DASH events,” explained Royal Canadian Air Force Capt. Dennis Williams, RCAF DASH 3 participant.
More Factors to Integrate
The AI tools will still need further refinement, particularly in accounting for real-world conditions such as weather. The recent exercises included weather-related challenges manually simulated by human operators, but as the technology is refined, weather will become another variable that AI can consider in its COAs.
The team will also continue to deal with so-called AI hallucinations, “where AI produces incorrect or irrelevant outputs.” Efforts are being made to minimize its risk.
“The 2025 Dash series has established a strong foundation for future experiments, with the potential to expand AI’s role in battle management further,” said Ohlund.
It was just the beginning, added Williams, who stated, “The more we can integrate AI into the decision-making process, the more time we can free up to focus on the human aspects of warfare. These tools are key to staying ahead of our adversaries and maintaining peace and stability on a global scale.”
AI Assistants
In simplest terms, DASH is a digital assistant specialized in warfare, much like Siri or Alexia.
“The idea of human-machine teaming in battle management is essentially about using machines as extremely fast, tireless assistants,” said geopolitical analyst Irina Tsukerman, president of threat assessment firm Scarab Rising. “These systems are being asked to take massive streams of information and quickly turn them into possible courses of action. Not one plan, but many plans.”
Each plan presented could show how a mission might unfold, the support it would need, the risks it carries, and where it might fail.
Humans then judge those options, choose among them, and take responsibility for the decision. The machine does not command. It helps humans think faster and more broadly under pressure,” Tsukerman told ClearanceJobs. “What DASH 3 shows is that the Air Force is moving past theory and actually testing this under realistic conditions. These were not classroom demos. They were simulated combat scenarios where time pressure, uncertainty, and competing priorities were deliberately built in. The goal was to see whether AI tools could genuinely reduce the time it takes to move from confusion to action, without overwhelming operators or producing nonsense outputs that no one trusts.”
She added that a crucial point is that this was coalition-focused.
“The U.S. is openly acknowledging that it does not expect to fight major conflicts alone,” added Tsukerman. “Canada and the UK were not observers. They were active participants. That matters because coalition warfare breaks down when systems do not communicate or when partners do not trust the same decision-making tools. By testing AI-driven battle management in a shared environment, they are trying to make sure future wars do not stall because allies cannot align fast enough.”
