Few people doubt that AI is among the most transformative technologies to emerge in the past century. By many measures, it is spreading faster and more widely than any innovation since the dawn of the Industrial Revolution. Steam engines came into common use in the nineteenth century and electricity in the early twentieth, but their full potential was not realized before the completion of railways, highways, and power grids decades later. Computers for business use emerged in the 1950s, but they gave no visible lift to the economy before the Internet connected them in the 1990s.

Commercial artificial intelligence, by contrast, appeared almost overnight on screens worldwide, at a moment when the overwhelming majority of humans already had access to a computer or smartphone. Less than four years after the release of ChatGPT, roughly 30 percent of Americans are now using AI, five times the share of Americans who were using smartphones, the Internet, or electricity at comparable stages of development. Revenue for AI companies is three times what previous digital technologies, including the Internet, cloud computing, and early mobile apps, generated in their early years.

Policymakers, investors, and business leaders are counting on AI to be a miracle cure for everything from runaway public debt to the costs associated with aging populations. Among investors, even some of the world’s most successful contrarians—who make their fortunes betting against conventional wisdom—are embracing the idea that AI could yield bigger benefits more rapidly than any past technological advance.

The euphoria is not universal, however. An ever-lonelier minority of skeptics argue that AI’s rise may seem unusually fast but is in fact following a centuries-old script. Major technology revolutions have always triggered dramatic boom-bust cycles. People get overexcited about the latest breakthrough and begin investing indiscriminately in the companies driving the innovation. As a team of researchers from Texas Tech University, Texas A&M University, and the Vlerick Business School in Belgium found in 2018, all of the most revolutionary technological innovations of the last two centuries inflated a major market bubble—a rapid increase in stock prices, followed by a precipitous decline.

The word “bubble” tends to conjure an idea as thin as air. But as with all previous tech bubbles, the innovations of the current AI boom are real, the hype born of genuine promise. That promise, however, is exactly what is inflating the bubble. Once the mania begins to crack, as it inevitably will, the shock will ripple back through financial markets into a global economy increasingly dependent on AI for growth. The damage will be felt worldwide, not only in the countries leading AI’s development but in the many now battling to supply them with inputs, as well. The weakest players will be wiped out, and the survivors will consolidate their lead. And from the rubble, a more stable AI ecosystem will emerge.

The AI competition is already reshaping the economic world order. At the top of this order stand the United States, where the foundational AI model, ChatGPT, reached consumers in late 2022, and China, where DeepSeek made its debut around a year later. Since then, the race for supremacy has come to drive both countries’ economies. In the United States, growth has been fueled primarily by the hundreds of billions of dollars of Big Tech investment in AI projects and by consumer spending energized by gains in a stock market dominated by AI. The top ten stocks in the benchmark S&P 500 are all big AI players and together account for nearly 40 percent of the index and around half of its returns this year.

China is spending far less on AI but would be lost without it. After falling in the last decade, net exports—mainly of AI-related goods—now account for a third of China’s growth. The domestic economy is otherwise moribund, hampered by bad debts and a shrinking labor force. Beijing is also heavily supporting the export of its homegrown AI models, which are catching on because they are cheaper than American frontier models but perform nearly as well.

The AI rage now extends beyond Washington and Beijing. Investors are plowing funds into companies that supply American tech giants with the computing power, semiconductors, and other building blocks they need, fueling stock market booms worldwide. In Asia, for example, three major semiconductor companies have reaped the benefits: TSMC in Taiwan and SK Hynix and Samsung in South Korea, which comprise an even larger share of their local stock indexes than big American tech firms account for in the U.S. index. In these relatively small economies, the global frenzy for AI has generated even greater shocks than in the United States. The total value of South Korea’s market exploded from $1.5 trillion at the start of 2025 to over $5 trillion this summer. Individual investors saw bigger gains in stock wealth over 18 months than they had in a lifetime. Chip exports have driven real growth in Taiwan toward double digits in some recent quarters, a pace rarely approached in any economy.

Other countries at this level of the so-called AI stack of computing infrastructure have benefited similarly from the global market tilt toward builders of AI hardware, or “picks and shovels.” High tech now accounts for as much as half of all economic growth in Israel, owing in part to the country’s expertise in the high-speed networks needed to train AI. In Japan, firms that specialize in AI-related equipment, materials, robots, and semiconductors have become market darlings; after Kioxia, a pioneer in memory chips, became a major supplier to U.S. tech companies, its share price spiked to more than 45 times what it had been a year earlier, briefly becoming Japan’s most valuable stock.

All five of these leading tech powers—China, Japan, South Korea, Taiwan, and the United States—spend, on average, much more than other countries on R & D and technology as a percentage of GDP. But they are far from the only countries racing to secure footholds in the AI stack.

Below them, secondary suppliers are forging ties to the leaders. U.S. and Chinese AI giants are spending billions on data centers in Singapore and Malaysia. Firms are investing heavily in AI server production in Mexico, which is emerging as an important exporter of AI-related hardware, as well. At least half a dozen tech companies have launched AI projects in Vietnam, including a major R & D center and training facilities to develop the country’s talent pool.

In turn, the worldwide AI construction project is expected to provide years of steady demand for the raw materials required to wire and store energy for data centers: nickel from Indonesia, lithium from Australia, copper from Chile, Peru, and the Democratic Republic of Congo. And the large cloud-service providers known as hyperscalers are looking far and wide for that energy. Amazon, Google, Meta, and Microsoft accounted for half of all clean energy deals signed across the globe in 2025.

Private spending on data center construction is up by roughly 50 percent from a........

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