A lack of innovation of A.I. is holding back military integration, but further innovation could revolutionize military technology.

Similarly, AI is sparking military systems evolution in the United States and China, two countries that lead in global AI development by a number of different markers, but not yet in a militarily transformative way. Military systems evolution refers to the ways that new technologies are incorporated into new or existing military capabilities and applications. AI applications have advanced in autonomy and robotics, decision support, predictive maintenance and logistics, cyber, and modeling and simulation, yet are subject to many of the weaknesses mentioned above; progress is generally broader than it is deep. Many higher-profile AI-enabled programs in the unclassified realm across different types of applications, such as Joint All-Domain Command and Control (JADC2) or Loyal Wingman, are comparatively nascent. Military access to the useful, clean, and comprehensive data sets necessary to train AI applications can be limited.

As such, AI has done little to spark either operational innovation or organizational adaptation in the United States and China. Operational innovation stems from critical thinking about how militaries can capitalize on new technologies and systems to achieve their objectives; organizational adaptation connotes changes to the structure of the fighting force to exploit new systems and patterns of operations. For example, German blitzkrieg warfare centered new operations around speed and mechanized (tank) maneuvers, leading to the organizational adaptation of separating tank units from soldiers moving on foot.

In the United States today, current and forward-looking joint and service operational concepts continue to emphasize the importance of traditional elements like long-range fires, maneuver, information dominance, and joint force projection as augmented but not transformed by AI. In China, AI similarly does not appear poised to transform the informatization concept of warfare, which emphasizes dominating the information environment as part of an asymmetric strategy to counter U.S. comparative advantages. Intriguingly, though, the future “intelligentization” concept discussed by some Chinese strategists, envisions AI as helping dominate the “cognitive” domain—including an adversary’s psychology, perception of information, and even brain function—and represents longer-term thinking about disruptive operations. Regardless, though, with military AI applications largely too immature to dictate shifts in operations, neither the United States nor China has altered its military organizations based on AI.

U.S.-China AI Competition Through the RMA Lens

So, what can policymakers do with this information? How can insights gleaned from the RMA framework inform U.S. policy approaches to tech competition with China? Why should defense analysts, technologists, or the public care if AI is not sparking imminent revolutionary changes to military affairs?

For one, thinking in RMA terms helps to evaluate mental models for AI’s impact on security and defense along an “evolutionary to revolutionary” spectrum. AI might spark evolutionary near-term change in the next decade or so, augmenting reconnaissance-strike capabilities without overturning dominant patterns of operations. In the United States, discussion about JADC2 points to this possibility—connecting “sensors to shooters” has been a joint goal since the Gulf War. AI could continue advancing autonomous capabilities, fulfilling noncombat functions like predictive maintenance, or augmenting cyber capabilities. However, analysis of seemingly less revolutionary change, including careful analysis of technological developments that may seem less obviously militarily applicable, must accompany evolutionary framing. With certain AI applications and methods advancing rapidly, it is important to acknowledge AI’s game-changing potential and how unforeseen technological applications could generate new, revolutionary military systems and operations. Analysts and policymakers who offhandedly dismiss even seemingly militarily irrelevant applications of AI do so at the risk of ceding advantages to creative adversaries. It is better to be safe than sorry.

Policymakers can also use the RMA framework to identify indicators of AI-driven transformative change. Open-source technology monitoring could uncover potentially disruptive academic or private-sector tech progress. Specific AI signposts could include advanced development of enabling computing technologies, new, less compute-heavy learning methods, or progress in explainability that could help warfighters trust previously opaque capabilities. Advanced government signposts could include AI assurance cases and dependable test and evaluation frameworks that suggest a need and ability to assess application performance at scale, as well as new doctrinal guidance incorporating AI that informs future training and force development. For example, examining new Chinese doctrine will help determine the importance the People’s Liberation Army sees for AI applications in its future force. Passing these early- and late-stage signposts would indicate that AI technology may be making disruptions to military paradigms increasingly likely.

Finally, and crucially, the RMA framework can help identify the missing pieces of the intellectual puzzle when it comes to military applications of emerging technology. To date, the United States and China have made little progress on operational innovation and organizational adaptation with AI. A future AI RMA instigated by the United States or China will therefore require more grappling with how AI might change patterns of operations, thinking, and experimentation that historical case studies illustrate—such as the carrier aviation RMA and China’s writing on intelligentization—can be done even before new technological applications become operational. In the case of the carrier RMA, both the U.S. and Japanese navies possessed cutting-edge (for the time period) carrier and aviation technologies. However, the unique way the United States came up with operational patterns and structures using the new capabilities transformed naval warfare from being centered around battleships and thus provided a decisive advantage compared to the Japanese. Without critical thinking and experimentation around how new technologies will be applied, their impact on military affairs is not guaranteed to be revolutionary.

Conclusion

AI may not yet or even imminently spark a revolution in military affairs. Nonetheless, using the RMA analytical framework to delve into why it is not doing so, and how it might in the future, can help us think systematically about AI’s potential impact on future warfare. AI’s impact could one day be transformative enough in areas like cyberwarfare or even nuclear deterrence without over-hyping nascent capabilities. To ensure that militaries use AI-enabled capabilities thoughtfully and responsibly, military futures analysis should be as rational and grounded as possible.