- DAF has concluded its latest DASH human-machine teaming exercise
- The event tested joint Air Force and Space Force battle management integration
- The exercise validated a government-owned, agile acquisitions model for C2 tools
The Department of the Air Force has wrapped up its latest Decision Advantage Sprint for Human-Machine Teaming, or DASH, exercise, examining how artificial intelligence can process large volumes of data to help operators make faster command-and-control, or C2, decisions.
DAF said Tuesday the two-week event took place at the 805th Combat Training Squadron’s Shadow Operations Center-Nellis in Las Vegas and was jointly led by the Air Force Research Laboratory and the Advanced Battle Management System Cross-Functional Team, or ABMS CFT.
An operational crew headed by a U.S. Space Force Guardian worked with Air Force battle managers and industry software developers to test an agile acquisitions approach intended to quickly transition new tools to warfighters.
How Does DASH Support Multidomain Integration?
DASH placed a U.S. Space Force Guardian in charge of an integrated operational crew working alongside Air Force battle managers, testing whether C2 challenges are consistent across domains.
Space Force Maj. Erik Murdock, 57th Space Aggressor Squadron operations division chief, said the joint force operates toward a single objective rather than separate service approaches.
“Because while our domains are different, our decision-making challenges are identical,” Murdock said. “This experiment demonstrated that when you give a joint team common objectives and a shared set of tools, the integration happens naturally.”
Elizabeth Frost, the AFRL DASH lead, said workload data collected during the exercise, drawn in part from analysis by the 711th Human Performance Wing, supported that finding.
“Both Airmen and Guardians are tasked with synthesizing vast amounts of complex data and prioritizing actions under intense time pressure,” Frost said, adding that a well-designed human-machine team can free up an operator’s cognitive resources regardless of domain.
What Is the Rapid Acquisitions Model Behind DASH?
DASH is structured to validate an agile acquisitions model intended to move new capabilities to the warfighter at speed. The approach relies on direct user-producer co-creation, pairing operators with industry developers on the same floor so that requirements and feedback shape tools in real time.
Jeffrey Palumbo, AFRL C3BM Capability Area lead, said the DASH series reflects that model directly.
“This approach of user-producer co-creation allows for proof of concept, energizes the industrial base, and allows for early operator feedback to shape development,” Palumbo said, adding that it “sets us up to deliver chunks of warfighting capability to the operational force in a rapid and repeatable cycle.”
A government-owned “orchestrator,” built by AFRL, underpins the model by letting multiple competing industry applications run within a single testing environment. Kevin McFarland, AFRL Advanced Capabilities Directorate project management lead, said government ownership of that software interface “significantly decreases integration bottlenecks” and moves the department away from being locked into a single vendor’s architecture.
Air Force Lt. Col. Corey Ellsworth, ABMS CFT integration lead, said the DASH framework was built so that capabilities validated during the exercise can securely transition to classified networks where Airmen and Guardians will use them operationally.
How Has DASH Evolved Since Its First Experiment?
The Air Force first piloted the concept in mid-2025, when the inaugural DASH experiment tested prototype C2 capabilities designed to speed up battle management decisions. A follow-on effort later that year built on those findings, as the 805th Combat Training Squadron’s Experiment 3 integrated AI-generated targeting recommendations into a data-driven kill chain. By early 2026, the sprint had grown further still, with the third iteration of DASH bringing in coalition partners from Canada and the U.K. to test AI-enabled decision tools in a joint C2 environment.
