The Air Force recently experimented with several artificial intelligence tools designed to improve battle management, expanding and validating the service’s previous work to test the technology for future operations.
The Department of the Air Force Advanced Battle Management System (ABMS) cross-functional team hosted its first Multi-Decision Advantage Sprint for Human-Machine Teaming (MASH) experiment in May. The two-week event took place in Las Vegas, Nevada, and was the latest in a series of war games aimed at developing and testing the industry’s AI-powered battle management tools.
According to the service, MASH marked an evolution in the Air Force’s experimental campaign by successfully integrating diverse capabilities and actively engaging Space Force Guardians alongside the pilots.
“Data analysis is ongoing, but early trends strongly reflect our previous successes and show a significant acceleration in decision speed,” Col. John Ohlund, director of the ABMS CFT, told DefenseScoop. “Ultimately, this validates the human-machine team’s potential to significantly expand the volume of viable options available to commanders during high-tempo operations.”
In 2024, the Air Force’s 805th Combat Training Squadron – also referred to as Shadow Operations Center-Nellis (ShOC-N) – launched a multi-pronged experimentation campaign designed to support the development of AI tools and operational concepts for the DAF Battle Network, the service’s contribution to the Pentagon’s Combined Joint All-Domain Command and Control (CJADC2).
One such experiment is known as the Decision Advantage Sprint for Human-Machine Teaming (DASH), in which industry software teams are tasked with building AI “microservices” that focus on a small section – called sub-functions – of the broader command and control process.
However, MASH introduced new complexities by evaluating multiple sub-functions and converting them into a single, coherent workflow, Ohlund said.
During the war game, six industrial teams and the 805th’s own software engineers were tasked with developing customized AI tools that would automate and accelerate parts of the air combat management mission, according to the Air Force. These AI capabilities were repeatedly stress tested in a simulated operational scenario conducted by combat managers.
“The AI tools are designed to automate three key decision-making functions and accelerate the way operators process and respond to complex data streams,” Ohlund explained. “Specifically, they analyzed incoming information to identify and categorize potential entities, aligned the best available joint capabilities to address these situations, and then generated multiple, optimized courses of action.”
The design of the experiment meant that each simulation tested three separate microservices, developed by different industry teams specifically for individual sub-functions. A significant breakthrough during MASH was the Air Force’s ability to integrate disparate software applications without impacting operations using an orchestration tool developed by the Air Force Research Laboratory.
“AFRL has done an incredible job building an orchestrator that ensures these different companies can seamlessly exchange data, ontologies and metadata,” said Ohlund. “We prove that a true plug-and-play modular approach not only works, but also promotes continued competition and allows the government to select the best software services as they mature.”
In addition, MASH was the first ShOC-N experiment in which members of another military service actively participated. Space Force Guardians served alongside Airmen on the battle management teams while testing the AI tools through simulations and providing developers with immediate feedback on the decision-making logic and limitations of the technology.
Ohlund noted that the Guardians brought expertise in the space domain while demonstrating that both air and space forces face similar challenges in managing combat despite operating in completely different environments.
“Their participation highlighted that even though the aerospace domains operate on different schedules and at different distances, the basic requirements for rapid, synchronized decision-making are identical,” he said. “Their unique perspectives have helped develop the battle management software from the ground up to support a truly integrated, cross-domain force.”
Overall, the AI used at MASH helped battle managers by automating time-consuming tasks and consolidating large amounts of incoming data. This allowed soldiers to process situations much more quickly and focus on strategic decisions.
“A week ago, it took my team and I 50 minutes to an hour to complete one task. Using the tool, we were able to complete five or six tasks,” Capt. Adam Sochia, an air combat manager with the 552nd Operations Support Squadron, said in a statement. “Essentially, in the time it takes us to complete one task, this tool gives us the data and precise options to complete five or more additional tasks.”
The ABMS CFT and 805th will continue to conduct war games using AI tools throughout the remainder of the year. The Air Force hopes to invite members of all military services to participate in future experiments so it can continue to create an operational blueprint for modern, cross-domain C2 operations.
“The reason we challenge software to solve multi-domain problems is because this is the reality of the future fight,” Ohlund said. “An Air Force air combat manager does not have the authority to execute a space or cyber effect, but like any good staff officer, his job is to prepare the information and summarize the options for the general. We want the computers to do that work and think about every possible multi-domain effect. That way we can present a menu of the highest quality decisions to the right commander faster than ever before.”
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Written by Mikayla Easley
Mikayla Easley reports on the Pentagon’s acquisition and deployment of new technologies. Before joining DefenseScoop, she covered national security and the defense industry for National Defense Magazine. She received a BA in Russian Language and Literature from the University of Michigan and an MA in Journalism from the University of Missouri. You can follow her on Twitter @MikaylaEasley
https://defensescoop.com/2026/07/02/air-force-space-force-combine-ai-tools-in-battle-management-experiment/
