Whether the MSS is indicative of an unfolding RMA remains a subject of debate. At a minimum, it represents a significant leap in how modern militaries sense, decide, and act in combat. From a scholarly perspective, RMAs are not defined by single technological breakthroughs but by clusters of innovations that fundamentally transform the conduct of warfare.

They typically involve shifts in doctrine, tactics, organization, culture, and technology. Unlike broader military revolutions, which reshape societies and political systems, RMAs are confined to the military sphere—and they often unfold quietly, only recognized in hindsight.

Several RMAs were identified in the past, providing a framework to anticipate future ones. In The Dynamics of Military Revolutions: 1300–2050, MacGregor Knox and Williamson Murray outline five significant military revolutions in the West since 1618. Each one, they argue, set off a chain of revolutionary changes in military affairs.

These include the emergence of the modern state with its standing armies, the political and social upheavals brought on by the French Revolution, the industrialization of warfare in the 19th century, the era of total war in the 20th century, and the transformative impact of nuclear weapons. If a new RMA is underway, we may not fully recognize it until it has already matured.

The concept of RMA has drawn justified criticism for being abstract, amorphous, and debated to the point of analytical paralysis. After the Gulf War, the DoD’s fixation on identifying the “next RMA” often overshadowed the operational impact of emerging capabilities. Scholars frequently focus on definitional purity rather than assessing real battlefield transformation.

Whether the MSS fits a textbook definition, adopted by the DoW or derived from historical theory, is less important than its functional impact. If an RMA is indeed emerging or approaching, there should be tangible real-world consequences. Otherwise, theory becomes disconnected from practice. In this light, the MSS may serve as a bridge between the long-unfolding information RMA and a new, AI-driven transformation.

The MSS could be indicative of another significant shift in command and control (C2). While the US Army’s command post computing environment (CPCE) already integrates legacy systems into a modular, cloud-capable architecture for multi-domain operations, the MSS pushes these capabilities toward revolutionary real-time situational awareness.

While initially developed to automate drone feed analysis, the MSS has evolved into an AI-powered battlefield intelligence engine. It fuses intelligence, surveillance, and reconnaissance (ISR) data, enables real-time targeting, and supports distributed decision-making. As with the telegraph in the 19th century, the MSS may redefine the military’s relationship with information and time.

Historically, C2 was slow and fragmented. Commanders relied on flags, runners, and direct observation, limited by geography and transmission delay. The Industrial Revolution began to change this. Introduced in 1793, Claude Chappe invented the optical telegraph which allowed faster coordination across long distances. It was Samuel Morse’s electrical telegraph, patented in 1837, that truly revolutionized communication.

AI is reshaping combat just as electricity once did. Electricity transformed communication by creating the foundation for critical innovation, like the internet. The harnessing of electricity for industrial use itself was not an RMA, but it was the essential prerequisite for one. Without it, the revolution in communication that began with the telegraph would not have been possible. AI may not constitute a full RMA on its own, but it is the enabling foundation for one.

During the Crimean War and the American Civil War, the telegraph enabled real-time command for the first time. In the US, President Lincoln relied on the War Department telegraph office to direct Union forces and enforce strategic decisions. Strategic-level C2 became possible, and expectations for real-time situational awareness took hold. The rise of the steam-powered printing press and the expansion of railways accelerated this transformation, making war reporting nearly instantaneous—a precursor to modern information warfare.

Similarly, Project Maven, initiated in 2017, began as a machine learning initiative to automate drone video analysis. Since then, the MSS has grown to integrate cloud computing, ISR fusion, and targeting. The MSS delivers intelligence to the tactical edge at machine speed on enterprise cloud infrastructure. It processes unfathomable amounts of data in milliseconds— augmenting analysts and automating portions of the workflow.

Just like the electric telegraph centralized control and supported linear commander decisions, the MSS introduces machine learning, machine inference, and adaptive analytics to take command and control. The MSS provides a picture of the theater that is not merely quantitative, but qualitative.

A true RMA requires more than new technology. It demands operational adaptation, organizational restructuring, and doctrinal evolution. The MSS checks many of these boxes. Technologically, the MSS merges AI, edge computing, and cloud infrastructure in a holistic fashion. Operationally, it uses human-machine teaming to accelerate kill chains. Organizationally, it catalyzed the creation of institutions such as the Joint AI Center (JAIC) and the Chief Digital and Artificial Intelligence Office. Doctrinally, it promotes shifts toward algorithmic and mosaic warfare, which are adaptive, data-driven models of conflict.

The MSS could signal a broader shift in military operations, much like the telegraph reshaped communication in the 19th century. By combining intelligence, surveillance, and reconnaissance (ISR) with artificial intelligence at operational speed, the MSS is changing how armed forces interpret the battlespace, make decisions, and coordinate action—all while improving the shared situational picture. Yet without a corresponding cultural shift, even the best tools can fail to yield a true RMA. Whether the Department of War can fully adapt its doctrine and institutions to leverage the MSS remains to be seen.

Lieutenant Colonel Matthew J. Fecteau is an information operations officer working with artificial intelligence. The views expressed in this report are those of the author and do not necessarily reflect the official policy or position of the Department of the Army, the Department of War, or the US Government. 

Signals of a New Revolution: Maven Smart System and the AI-RMA Horizon was originally published on Global Security Review.

Focusing on information operations is critical. Drones, for example, use artificial intelligence capabilities, as do defensive systems. However, conflict between near-peer adversaries and competitors is still unlikely as gray zone and hybrid conflict are the dominant avenues for competition. With the information environment transcending all domains of warfare, artificial intelligence capabilities become the go-to capability to ensure and maintain information advantage.

China’s AI-enhanced information operations are becoming increasingly sophisticated. For example, the Chinese advanced persistent threat actor Spamouflage Dragon uses generative AI to create online personas to influence public opinion. China and its proxy companies seek to develop or compete for AI supremacy within the information environment.

Of course, China will use anything within its arsenal to shape strategic, operational, and tactical levels of war to its advantage, expand its influence, and create an ecosystem that is dependent on its technologies. For example, Baidu, known as the “Google of China,” invested billions into AI capabilities, creating the proprietary ERNIE model, which has been trained on billions of parameters, increasing the output’s quality and complexity.

However, China is also leveraging open-source AI models to shape the information environment. With the recent release of open-source large language models such as DeepSeek and Qwen, Chinese-linked subsidiaries, High-Flyer and Alibaba Group created a way to expand their influence, revise history, and likely create a dependent ecosystem for target countries. Unlike the much more expensive ChatGPT, for which the more basic model is free, China’s investment in generative AI models is free for the public and even surpasses ChatGPT’s in some respects.

There is a debate about how China’s proxy state companies were able to create these advanced models without US-based critical components. China allegedly did not have access to the advanced critical Nvidia chips for which most AI models are dependent. China seems to have created generative models just as suitable or even better than that of ChatGPT, but allegedly at a fraction of the cost and free of charge to the public. The US limited Nvidia chip exports to China, a market predicted to top $1 trillion in revenue within a decade. Still, the accusation is that the Chinese subsidiary leased or bought the more advanced Nvidia chips from Singapore, circumventing restrictions, and used ChatGPT to train its model.

Regardless of how China secured these critical technologies, the cat is indeed out of the bag. China has shown that it has the capability to develop new and emerging AI technologies. From the capabilities already built, it now has a baseline to create even more capabilities to develop its own AI chip ecosystem. With such capabilities, China will become more active within the information environment with the help of AI capabilities, and its motives are far from benevolent.

Why is the Chinese model free? China has several motives, but it is likely in hopes that data and information across the globe are the price tag for using the model while lessening a dependency on Western technologies and becoming a global leader in AI by 2030. Whatever data is obtained by the United States is icing on the cake. The West is not the primary target audience. Both models have servers in Singapore and China, where information is likely subject to Chinese laws, and terms and conditions are meaningless.

The Chinese will use AI technologies to gain an advantage in the information environment and seek to expand influence by creating an ecosystem for which other countries are dependent on their models. The incentive is to give countries this technology to foster dependency. The idea is similar to China’s debt-trap diplomacy—the Belt and Road Initiative. While ChatGPT’s basic model is free, China seeks to develop better models at a cheaper price to serve as leverage over countries that cannot afford the higher-end US-based models.

The United States is taking the right approach to maintaining its information advantage through AI development and investment. The billions pouring into creating AI data centers will play an important role in ensuring the United States has the edge in AI.

These data centers remain critical for identifying and countering any malign information operations against the United States, its partners, and its allies. When Iran attempted to influence the 2024 presidential election using the generative model GPT, OpenAI detected and shut it down. Without this expansive investment in AI data centers that keep information within the letter of US law and oversight, these interventions would be out of reach, and information operations may be even more challenging to detect.

However, this approach is insufficient without incorporating artificial Intelligence into all aspects of military operations. The DoD uses artificial intelligence within some branches, but given the expansive nature of AI, this is not enough. AI is expected to touch nearly all aspects of military operations, especially information operations, and may not have time to wait for its major AI initiative, Project Maven, to fully develop.

Some military scholars have called something like this a revolution in military affairs, but perhaps, given the impact of war, it could be classified as such. The concept is somewhat antiquated and outdated without some context, but it remains the best way to describe what should take place within the DoD. The foundation is already in place through the conceptual framework of multidomain operations.

Artificial capabilities are widely available through graphical user interfaces in deployable, ready-to-use form, such as ChatGPT or even internal large language models. The joint force should use these capabilities to the broadest extent possible. If anything, artificial intelligence, including large language models, will make joint and combined forces more lethal and accurate as they counter Chinese efforts within the information environment.

The DoD must adopt incentives for service members to understand the capabilities of AI and incorporate them in all training environments. These incentives can include bonuses for taking AI-driven courses. The DoD can also increase awareness and accessibility of AI courses on its education platforms which now have a paucity of artificial intelligence courses.

The DoD must also improve the training environment. With proprietary or off-the-shelf software, the DoD can incorporate AI offensive and defensive platforms within all training and mission-critical tasks. Even simply assisting with identifying generative outputs, e.g., deepfakes, will counter Chinese influence within the information environment, especially during hybrid conflict. Furthermore, military doctrine should recognize the importance of AI, especially information operations, with an emphasis on psychological operations.

While AI investment is critical to countering Chinese influence within the information environment, the only way to truly embrace multidomain operations is to ensure service members have the AI technical competency necessary to maneuver within the information environment deterring Chinese aggression.

US Army Lieutenant Colonel Matthew J. Fecteau is a PhD researcher at King’s College London studying how artificial Intelligence will impact conflict. He can be reached at matthew.fecteau.alumni@armywarcollege.edu.

China’s AI-Driven Information Operations Are Here: The US Needs an AI RMA was originally published on Global Security Review.