A new issue brief underscores a profound transformation in the concept of air superiority, driven by the rapid integration of Artificial Intelligence (AI) and Unmanned Aerial Systems (UAS). The brief argues that the next decisive air battle will not be determined by the speed or stealth of a single aircraft, but by the ability of combined human-machine systems to process information, make decisions, and act with unprecedented speed.
The new paradigm shifts the focus from traditional metrics of pilot skill and platform performance to what the author terms “cognitive tempo”—the velocity and reliability of the observe-orient-decide-act (OODA) loop when humans and machines operate as a single, cohesive system. This evolution is being fueled by advanced technologies such as edge AI, sensor fusion, and coordinated drone swarms, which allow raw sensor data to be converted into combat effects at machine speed.
Global Military Powers Embracing the AI-Driven Future of Warfare
This shift is not theoretical; it is already being actively developed and implemented by nations and military groups around the world. The United States, for instance, has made a pivotal decision to field a new generation of crewed fighters alongside a fleet of over 1,000 Collaborative Combat Aircraft (CCA). This strategy of Manned-Unmanned Teaming (MUM-T) is now a cornerstone of their future air combat planning, moving from a conceptual ambition to an operational doctrine. Similarly, the Defense Advanced Research Projects Agency (DARPA) is running its Artificial Intelligence Reinforcements (AIR) program, which focuses on developing AI systems capable of operating in the messy, unpredictable complexities of real-world combat scenarios.
The conflict in Ukraine has served as a real-world laboratory for this new era of warfare. Both Ukrainian and Russian forces have extensively adopted small and medium-sized drones, including First-Person-View (FPV) drones, for diverse missions. The widespread use of these systems highlights a tactical shift where drones act as a permanent “grape-shot” or “reactive shield,” saturating front lines and infiltrating rear areas to hunt logistics and fire support assets. Ukraine’s military has also been developing standalone AI-driven software to be integrated across various platforms, enhancing autonomous functions like target recognition and navigation to remove warfighters from direct combat.
Beyond state actors, militant and organized crime groups such as the Islamic State and the Houthis have also employed drones for attacks and logistical purposes, democratizing access to advanced warfare capabilities. In a notable instance in Libya in 2020, a Turkish-made UAV with a built-in explosive payload detected and attacked forces without human command, showcasing the potential for fully autonomous systems.
The Challenges of the New Paradigm
While AI and drone technology offer immense operational advantages, the brief also highlights significant challenges. The effectiveness of this new approach depends on the resilience of these systems in contested electromagnetic environments, the security of model-assurance pipelines, and the ergonomic design of human-in-the-loop controls. The crucial resource is shifting from physical aircraft and munitions to the development of trusted data ecosystems and rapid, auditable software-update cycles. This requires a complete reconfiguration of procurement priorities, training, and allied interoperability.
The widespread proliferation of this technology, especially to non-state actors, also raises serious questions about the future of warfare and strategic stability. The shift towards “multi-fire, multi-domain” combat, where drones serve as the “robotic and increasingly automated nervous system” of a force, is leading to a new type of military revolution.
This insightful analysis underscores the urgent need for defense planners, policymakers, and international partners to adapt to this evolving landscape to maintain a strategic edge and ensure accountability in the face of increasingly autonomous systems.
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