In the 1990s, under the guidance of thinkers such as Andrew Marshall and Arthur Cebrowski, the U.S. military developed an advanced operational concept known as Network-Centric Warfare.
The idea was to connect large reconnaissance and strike drones such as the Predator, cruise missiles, ground forces, and other military assets through communications networks. Information from the battlefield would be gathered and transmitted to command centers in the United States, where commanders could issue orders to forces operating thousands of miles away in places such as Afghanistan. For many years, this system helped guarantee America’s military superiority.
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Since then, however, innovation within the U.S. defense establishment has slowed. Weapons development has increasingly been dominated by a handful of large defense contractors, creating a system that often consumes enormous amounts of time and money while becoming increasingly rigid.
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The Age of Startup-Driven Innovation
Palantir’s AI Command System TITAN
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Artificial intelligence has now begun to transform the concept of Network-Centric Warfare.
AI systems can gather and analyze enormous quantities of information and generate operational recommendations. They can help determine when, where, and with what weapons a target should be attacked, and then transmit recommendations or even commands through military networks.
Initially, the U.S. Department of Defense entrusted part of this effort to Google. However, following internal opposition from employees, work increasingly shifted to companies such as Palantir Technologies. Programs associated with this evolution include Project Maven and TITAN (Tactical Intelligence Targeting Access Node).
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Reports suggest that elements of these systems were tested during the recent conflict with Iran. U.S. forces reportedly struck multiple targets almost simultaneously while also intercepting incoming Iranian missiles and drones.
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The challenge is that targets cannot always be identified reliably through satellites and sensors alone. Another concern is that if too much decision-making authority is delegated to AI systems, military planners may find themselves consuming large quantities of weapons and ammunition at a very rapid pace.
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As a result, it is reported that the U.S. military has already used up about one-third of its stockpile of Tomahawk cruise missiles in the initial stages of the attack on Iran, and is now in a situation where it cannot fulfill its contracts with European countries and Japan.
Accordingly, the United States now faces growing pressure to maintain large stockpiles not only of Tomahawk cruise missiles but also of many other categories of munitions and military equipment.
If countries beyond the United States adopt systems similar to TITAN, they too may begin accumulating massive weapons inventories. Military production could expand dramatically, potentially creating conditions reminiscent of the Industrial Revolution in the 19th century. The current enthusiasm for AI-related stocks in the U.S. market may, consciously or unconsciously, reflect expectations that reach this far into the future.
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Ukraine and Palantir
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One particularly interesting development is that Palantir has already established a close working relationship with Ukraine.
Palantir CEO Alex Karp recently visited Ukraine. Around the same time, Eric Schmidt—who played a major role in advancing AI initiatives at Google before moving into venture investing—also visited the country.
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This naturally raises questions about whether American technology firms are helping shape some of Ukraine’s recent military tactics, including large-scale drone operations against Russian targets.
Defense Minister Mikhailo Fedorov (35) comes from the IT sector and has strong connections within the U.S. IT industry. However, military officers, including Commander-in-Chief Oleksandr Syrsky, remain attached to traditional close-quarters combat, making it difficult to know how fully AI-driven concepts have been embraced throughout the armed forces.
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In any case, Ukraine, like Iran, has become one of the world’s most important testing grounds for emerging military technologies.
The Ukrainian government appears well aware of this reality. It has even suggested that battlefield data could become a valuable national asset. Such data might include information about how soldiers react when pursued by drones, what evasive maneuvers they attempt, and which methods prove effective or ineffective against them.
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When AI gets access to Nuclear Weapons
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Allowing AI systems to influence decisions about when and where to use military force creates obvious risks.
Imagine an AI system concluding that a country might be preparing to use nuclear weapons. It could reason that the safest course of action would be to strike first against suspected launch facilities before those weapons could be deployed.
In such a scenario, speed becomes everything. The side that attacks first may appear to gain an advantage. Yet that very logic could trigger the catastrophe it was trying to prevent.
An AI-driven decision to strike a nuclear facility could rapidly escalate into a full-scale nuclear conflict. For that reason, humanity may need robust safeguards to ensure that human beings remain firmly in the decision-making chain. Lest thousands of nuclear warheads be launched within minutes, there must be mechanisms that allow human judgment to intervene before events spiral beyond control.
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