In the span of a few years, China and the United States have each assembled something future historians might recognize as a new kind of empire. Their dominions extend not merely over territory, trade routes, and airspace but over knowledge itself. By controlling the large language models, chips, physical infrastructure, and capital that provide the foundations for advanced machine cognition, Beijing and Washington are not only attaining new heights of economic performance and power projection; they are also setting the terms of all future scientific and intellectual progress. The term “AI superpowers” fails to capture the influence and reach that these rivals now wield. Even without active alliance building or coercion, they can make all other countries that seek access to advanced AI beholden to them.

Imperial history carries a warning. In the absence of other forces, empires seldom succumb to a challenger or to barbarians at the gates. More often, they fail because defending their vast dominions drains them dry, whether of material resources, the consent of the governed, or the loyalty of elites. The imperial center finds it can no longer maintain control over the periphery—the regions that once submitted to it. Failure can be financial, as it was for the British Empire after 1945, when the debts of two world wars forced London to liquidate its imperial assets to pay the price of victory: a welfare state for the citizens of the imperial metropole. It can be institutional, as it was for the Qing empire in the late nineteenth century, when it failed to industrialize, reform its bureaucracy, and renew the legitimacy of the Manchu dynasty.

Or it can be technological. The Royal Navy’s Dreadnought of 1906 gave the United Kingdom the first “all big gun” battleship and, with the same stroke, rendered its existing battle fleet obsolete. Overnight, this breakthrough opened the way for rivals such as Germany, erasing a century of accumulated British advantage. The resulting arms race forced the United Kingdom to nearly double naval spending between 1900 and 1914 and clashed with the Liberal government’s new social spending commitments, such as the Old Age Pension Act of 1908. The decisive question in the contest between Beijing and Washington may therefore not be who achieves artificial general intelligence first, but who can bankroll the race.

AI is imperial in two ways. On the one hand, China and the United States had empire-like qualities before the AI race began: Washington, the incumbent, pairs global military primacy with an alliance system no rival can match. It also supplies the currency for the lion’s share of international trade and transactions. Beijing, often described as the challenger, combines industrial and supply chain dominance with the world’s largest navy and a tightening grip on the physical and digital infrastructure of countries across Africa, Asia, and Latin America. For both, AI is a way to extend the power they already wield. But AI is also by its nature an imperial substance. Whoever produces and controls frontier models acquires global leverage over innovation, production, science, culture, and, ultimately, advanced thought. Much as silver underwrote Habsburg Spain and oil defined the “American century,” this new commodity will not merely enrich the powers that dominate it but also provide the basic operating system on which everyone else must depend.

What distinguishes the AI empires from their forerunners is not ambition but velocity. The familiar imperial arc—expansion, overreach, strain, unraveling—once played out across a century or even a millennium. Today, that process is happening at machine speed. The question is whether the new hegemons can convert their particular endowments—the United States’ capital markets, frontier labs, and transistors and China’s state direction, cheap energy, and watts—into durable imperial orders or whether they will run aground trying.

SUPREMACY BY SCARCITY

An empire is more than a great power. It is a polity whose authority and influence extend over vast territories and peoples without their express consent. Throughout history, empires have differed in almost every respect: in their form of government at home, in the kinds of resources they seek to control, in how their authority is sustained. They may be autocracies or republics; they may rely on soldiers and settlers or civil servants and chartered companies. Yet the underlying vector of power never changes. A center commands, and a periphery obeys. In practice, the most durable empires have relied on informal collaboration with local elites, whereas brutally coercive ones tend to be short-lived. Of course, any form of state power must not only monopolize violence but also be able to wield it. What sets empires apart is the capacity to elicit submission across immense distances. And they occur throughout history for a reason: by exploiting economies of scale, empires can achieve dominance and deliver security more efficiently than alternative structures, whether confederations or alliances of city-states. The nation-state is a relative newcomer.

Empires have often projected power through technological leadership. In antiquity, Rome’s aqueducts and China’s canals and flood-control works were the pipelines of centuries of hegemony. The imperial powers of early modern Europe led the world in printing, maritime technology, and artillery. The Cold War rivals were nuclear superpowers. Yet artificial intelligence may now give China and the United States greater imperial reach than any of those earlier technologies—and far more swiftly.

Several features mark AI as an imperial technology rather than a merely commercial one. First is the return of scarcity that it enables. An empire is, at its heart, a system for controlling finite strategic resources: able-bodied humans, arable land, grain, metals, and minerals. From the 1970s to the 2010s, software escaped this logic because it could be mass-produced at almost zero cost atop abundant, cheap silicon. AI has shattered that reprieve. According to the industry’s scaling laws, a model’s performance climbs relative to the number of parameters it contains, the volume of data it is trained on, and the processing power, or compute, spent training it. Progress therefore depends on energy, critical minerals, advanced chips, and capital on a massive scale. The moment a technology’s frontier comes to depend on vast quantities of scarce inputs, its production becomes a matter of geopolitics.

AI is by its nature an imperial technology.

AI also has an inherent center-periphery structure. Control of frontier AI and its rewards are concentrated in a handful of firms in China and the United States. Everyone else is a dependent user, whether a government running public services on a model it cannot inspect or a firm building products on an interface that can be repriced or withdrawn overnight. At the same time, AI inputs, both material and human, are drawn disproportionately from the periphery. Minerals from the Democratic Republic of the Congo and Indonesia and “ghost laborers” from Kenya and the Philippines, paid a few dollars an hour to label and filter the data from which a model in Silicon Valley learns—the plantation economics of the chatbot age. Raw inputs are extracted from the periphery, refined and assembled in the metropole, and sold back at a markup.

Like many empires, the AI stack is organized around chokepoints. Not all imperial power results from outright conquest, and not all those who are ruled are colonial subjects. The ascendancy of the British Empire in the nineteenth century was not driven primarily by vast territorial holdings, many of which had little economic value, or from control over factories and intellectual property—which was so poorly protected as to be effectively open source. Instead, British supremacy came from dominating the physical, technological, and financial pipelines through which the world economy flowed: coaling stations, strategic waterways such as the Suez Canal and the Strait of Malacca, undersea telegraph cables, and sterling finance through the City of London. The U.S.-led order after 1945 may have been an “empire of invitation,” as the historian Geir Lundestad termed it, but it also rested on the dollar and the Bretton Woods institutions, a U.S.-dominated international banking system, a global network of American military bases, and Washington’s nuclear umbrella. Today, the production and distribution of AI provides an even denser imperial lattice, with the metropoles able to switch its different elements—chips, minerals, models—on or off, as needed.

There is at least one crucial difference between the two AI empires. China’s is a deliberate act of state, whereas the United States’ is not. In 2017, China’s State Council announced a comprehensive plan to achieve global leadership in AI by 2030—specifically calling for China to develop “the world’s leading AI backbone enterprises” and to secure broad diffusion of its AI applications in the dozens of countries that are part of Beijing’s Belt and Road Initiative. Ministries, provinces, and state banks were mobilized to fulfill these goals, and Chinese leader Xi Jinping has continued to reinforce the effort, including with his 2026 push for Beijing to shape global AI standards. American AI dominance, by contrast, has emerged from private capital, a regulatory posture of noninterference, and improvised export controls. In this sense, Washington’s empire is the more conventional of the two: earlier empires were........

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