Although the nature of war remains constant over time, innovative technology deployed at scale disrupts the military status quo and ultimately can transform the character of war. The cutting-edge technology’s use tied to an effective strategy and tactics is a game-changer revolutionizing maneuver, enhancing mass, improving precision or facilitating surprise to achieve strategic, operational or tactical advantage on the battlefield. This shift in the character of warfare typically triggers a cycle with the innovation spreading to other adopters, some militaries lagging behind or failing to adopt, and spurs efforts to win a new race for technological dominance.
Basil H. Liddell Hart’s observation — reflecting on lessons learned from World War I —that “… the only thing harder than getting a new idea into the military mind is to get an old idea out” aptly characterizes the technology innovation cycle in the context of warfare. It encapsulates the tension between actively embracing new technologies and prolonged reliance on older, less effective capabilities. Addressing this reality ensures integrating new technologies and military strategy can lead to real-world advantages.
Just as technological breakthroughs like tanks and airplanes in World War I or radar and aircraft carriers in World War II revolutionized warfare in the past, artificial intelligence (AI) is the latest new technology capable of remaking the character of war. Its conceptual roots go back to British code breaking work at Bletchley Park in World War II. Building on that experience, the convergence of breakthroughs in high performance computing, more powerful microchips, and the volume of big data availability over the past decade has fueled burgeoning recognition that AI promises to revolutionize warfare by fusing not just synchronizing mass and precision to dominate the battlefield.
Leveraging AI’s functionality significantly enhances military capabilities, fundamentally alters the nature of missions, and impacts operations. For example, during Operation Desert Storm in 1990-1991, the state-of-the-art for military-embedded AI had matured enough so the DARPA-funded Dynamic Analysis and Replanning Tool (DART) was used for logistics scheduling. By 2002, AI was being used on the battlefield for a drone to autonomously navigate and provide situational awareness to special operations teams. Since then, the US military has expanded its reliance on a mix of static AI systems that use fixed rules or algorithms for deterministic tasks such as imagery analysis and dynamic AI systems. Dynamic AI systems are advancing rapidly and can learn, adapt, and respond in real-time to changing circumstances, data, and user interactions for applications to more complex tasks like target generation, surveillance, intelligence, and decision support.
Viewed retrospectively, a central challenge in warfare over the past 25 years — from counterinsurgency to conventional battles — has been synthesizing and interpreting vast amounts of real-time data to detect, characterize, track, and target threats faster than adversaries can adapt. With the sheer volume of information available, making sense of it all becomes overwhelming. Success in such dynamic environments hinges on the ability to observe, orient, decide, and act (the OODA loop) more quickly than the opponent. This is possible because dynamic AI systems offer a solution to the challenge of information overload created by the exponentially increasing volume and velocity of digital data.
In essence, AI-embedded military systems facilitate solving the problem of leveraging quantity and quality of strike power — especially as asset stocks decline by use or are degraded by enemy actions in high-intensity wars of attrition. This is a real not hypothetical problem. The protracted Russia-Ukraine War, the short but intense 12-Day Israel-Iran War, and periodic US strikes against the Houthis in the Red Sea demonstrate consumption rates for equipment like artillery munitions for ground strikes or drones, missiles and air defense systems for aerial operations is staggering.
To place this in perspective, the US launched more than 150 Terminal High Altitude Defense (THAD) interceptors at incoming Iranian targets during the brief 12-Day Israel-Iran War — more than 25 percent of existing US inventory and more than three times the annual purchase rate. Similarly, US naval operations against the Houthis in January 2024 used more Tomahawk missiles than the Navy bought in 2023.
Simultaneously solving the problems of having adequate inventory on hand, stockpile replacement/surge capacity and an effective real-time integrated system for threat identification, classification, tracking and targeting is critical. Failure to develop and deploy accurate and reliable AI-based systems at scale creates a major capability gap even if the first two problems are addressed. As a result — unless all three problems are resolved satisfactorily — the likelihood decreases the US, its NATO allies, and regional partners deter or win future high-intensity wars of attrition — especially with a pacing competitor like China — or respond to threats to North American Continental Defense, in NATO’s Far North, and its Eastern Front.
Successfully bridging these capability gaps matter for navigating the current and future strategic landscape. The US, its NATO allies, and regional partners like Japan and Australia face a significant resource allocation challenge coping with four major adversaries — China, Russia, Iran, and North Korea — across three main theaters — Asia, Europe, and the Middle East. These known adversaries are increasingly cooperating, amplifying their collective threat to the West. Inevitably, new and unforeseen threats also will emerge.
The integration of AI into the complex geometry of multi-domain operations — encompassing air, land, sea (surface and subsurface), space, information, and cyberspace — is driving a transformative leap in the speed, precision, scope, scale, and effect of military actions. The sheer magnitude of AI’s prospective impacts explains why America and China’s competition to dominate AI military use applications — particularly in areas like air defense, unmanned systems, command and control, logistics, intelligence, and situational awareness — mirrors their rivalry over dominance in commercial applications. Paralleling the US-China efforts, investing in developing and deploying military-embedded AI is a priority for numerous countries including Russia, Israel, Ukraine, UK, Japan, Finland, Poland, Estonia, Germany, and France. Ultimately, the pace and scale of integrating functioning AI systems into military capabilities not simply the sophistication or technical quality of those applications will determine which armed forces have sufficient technological dominance to deter or win wars. This advantage will help determine the winners and losers in a tumultuous geopolitical landscape.
Co-Founder and CEO
Audax Concepts
United States of America
Regents Professor Emeritus
University of Oklahoma
United States of America
