Advancing Decision-Making in Military Operations: The Role of AI in the Air Force’s Battle Network

Introduction

The U.S. Air Force is at the forefront of integrating artificial intelligence (AI) into its operational frameworks, particularly through its efforts to enhance the Distributed Air Force Battle Network (DAF Battle Network). This network aims to optimize command and control (C2) capabilities, enabling more effective and informed decision-making in dynamic operational environments. The recent Decision Advantage Sprint for Human-Machine Teaming (DASH) wargames illustrate how these innovations are transitioning from theoretical models into practical, real-world applications.

The DASH Wargames: A Testbed for Innovation

In July, the 805th Combat Training Squadron executed its second iteration of the DASH wargame series in Las Vegas, where Air Force personnel collaborated with industry leaders in software development. This two-week event provided a platform for testing AI-driven microservices specifically designed to refine the decision-making aspects of battle management.

• Key Objectives:
  • Shortening decision-making timeframes for air battle managers.
  • Delivering a comprehensive overview of the battlefield.
  • Validating the integration of AI technologies into traditional C2 operations.

Colonel John Ohlund, director of the Advanced Battle Management System (ABMS) Cross Functional Team, emphasized the initiative’s significance, stating that initial findings indicate a promising trajectory for human-machine collaboration and the alignment of operational tactics.

AI-Enabled Microservices: Enhancing Battle Management

The wargame focused on a pivotal function known as “match effectors,” which pertains to selecting optimal weapon systems for identified targets. During tactical scenarios, air battle managers analyzed numerous variables, including:

• Tactical Considerations:
  • Type of target and operational readiness of blue forces.
  • Environmental conditions, such as weather and potential civilian risk.

As highlighted by Captain Steven Mohan, the complexity of choosing the right system involves coordinating various elements: “I need to assess not just one weapon on one platform, but multiple assets in concert.”

To alleviate cognitive demands, participating software companies designed AI microservices that could process battlefield data, ranking available effectors by effectiveness. This innovative approach not only expedited the selection process but also provided rationales behind each ranking, bolstering the confidence of decision-makers.

Real-Time Feedback and Collaborative Development

The wargame included structured testing phases termed “vulnerabilities” (VULS), where developers received immediate input from air battle managers. This iterative approach allowed for rapid enhancements to the software.

Senior Airman Besner Carranza noted a striking improvement in efficiency. While a traditional run of task assignment could take about ten minutes, the integration of AI tools significantly reduced this time. The user interface facilitated a seamless integration of human expertise and machine capabilities, ultimately refining tactical choices.

Challenges in Data Integration and Multi-Domain Operations

Despite the progress made, participants recognized inherent difficulties that persist. Issues related to data quality and organization emerged, indicating the need for a more robust information framework. Air battle managers at the DASH events also pointed out that while the integration of multi-domain capabilities posed challenges, it demonstrated critical insights:

• Diverse Operational Assets:
  • Collaboration with other services, incorporating systems like the Army’s Terminal High Altitude Area Defense (THAAD) and Navy ships.
  • Enhancements in situational awareness, demonstrating alternatives beyond Air Force platforms.

Staff Sergeant Jacob Mucheberger remarked on the newfound awareness around leveraging various resources, recognizing the importance of integrating non-Air Force systems in future engagements.

The Future of the DAF Battle Network

The findings from DASH will inform future requirements for the Air Force’s Program Executive Officer for Command, Control, Communications, and Battle Management (C3BM). The lessons gleaned from these wargames are expected to support a strategic shift toward developing tailored AI solutions for distinct operational needs.

As Lieutenant Colonel Shawn Finney of the 805th outlined, moving to a demand-driven acquisition framework could allow the Air Force greater flexibility in identifying solutions that align closely with combat requirements.

Looking ahead, the 805th Combat Training Squadron plans additional DASH sprints, with four more scheduled for 2026. This iterative process reinforces a commitment to refining the DAF Battle Network further, enabling agile adaptation of software amidst evolving tactical landscapes.

Conclusion

The Air Force’s innovative approach to integrating AI into its operational framework aims to create a certain decision advantage in multi-domain scenarios. By emphasizing rapid development, interdisciplinary collaboration, and real-time feedback loops, the military’s path to enhanced decision-making is on a trajectory informed by practical use cases and collaborative expertise. The potential of the DAF Battle Network signals a future where AI not only supports but enhances the complexities of modern warfare.