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Americans have placed an unprecedented bet on the transformative power of artificial intelligence. The past 50 years of economic history suggests it won\u2019t pay off, at least not on a timetable the market expects.<\/p>\n
Not since the Gilded Age\u2014when, in 1885, railroad stocks accounted for more than 80% of active trading on the New York Stock Exchange\u2014has the U.S. economy wagered so much on a single theme. When that bubble burst in the Panic of 1893, a third of railroads went bust, more than 500 banks failed, and the economy plunged into a four-year depression.<\/p>\n
Today\u2019s frantic AI buildout may be on a similar trajectory. AI-related capital spending has surged to about 2% of U.S. GDP, from near zero five years ago. But this time, the AI wager is concentrated in far fewer companies than the railway mania ever was.<\/p>\n
In January, the Federal Reserve Bank of St. Louis reported that investments in information processing equipment, software, research and development, and data centers\u2014four investment categories economists consider the closest proxies for AI investment\u2014accounted for 39% of U.S. economic growth in the first three quarters of 2025, higher than the 28% those activities contributed in 2000, the peak of the dot-com boom.<\/p>\n
Pantheon Macroeconomics calculates that without AI spending, U.S. corporate investment in equipment was negative last year.<\/p>\n
Consumption, too, is heavily dependent on AI. The top 20% of income earners now account for approximately 60% of all U.S. consumer spending, according to Moody\u2019s Analytics. The source of their wealth? The AI stock rally.<\/p>\n
One theme, every market<\/p>\n
AI has become the dominant theme across all segments of U.S. capital markets.<\/p>\n
In equities, the \u201cMagnificent Seven\u201d\u2014Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, Tesla\u2014boast a combined $25 trillion in market capitalization. That\u2019s 35% of the value of the S&P 500 and the highest concentration in a handful of stocks since just before the crash of 1929.<\/p>\n
Separately, research from the Federal Reserve Bank of Kansas City shows that AI-related companies\u2019 share of investment-grade bond issuance increased from 2% in 2023 to 10% in 2026, highlighting the growing concentration of this kind of borrowing in credit markets.<\/p>\n
In venture capital, AI captured 81% of a record $300 billion in global venture funding in the first quarter of 2026, and just four companies\u2014OpenAI, Anthropic, xAI, and Waymo\u2014absorbed two-thirds of the total.<\/p>\n
The result is a self-reinforcing loop. Hyperscalers will spend $800 billion this year on chips, data centers, and the power to run them, propping up GDP growth. Investors are bidding up AI stocks, fattening the portfolios of the richest 20%, whose spending boosts consumption. As the buildout outgrows hyperscalers\u2019 cash flow, new investment is increasingly financed by debt and off-balance-sheet partnerships.<\/p>\n
The U.S. growth engine now runs on a narrow set of mutually reinforcing drivers. If one stalls, the others lose power too.<\/p>\n
The Bank for International Settlements warns in its 2026 Annual Economic Report that AI exuberance risks ending in a \u201clengthy investment bust.\u201d The BIS flagged \u201ccircular financing\u201d as a core vulnerability, more than half of investment in AI firms comes from other AI firms, with recipients using that money to buy their backers\u2019 products. Profits are being funded by investors rather than end customers.<\/p>\n
The late handoff<\/p>\n
America\u2019s AI bet is underwritten by a single assumption: That by 2027, growth driven by infrastructure will hand off to growth driven by AI-powered efficiency gains across the broader economy.<\/p>\n
I think that\u2019ll come much later than the market expects.<\/p>\n
As I argued in Fortune a few weeks ago, five decades of digital innovation achieved broad consumer adoption yet came with a decline in aggregate productivity growth. This is the Innovation Paradox: more innovation and slower growth.<\/p>\n
Technology diffusion follows a double K-shaped pattern. Consumers adopt almost immediately; enterprises, at a glacial pace. Within enterprises, a handful of superstar firms embrace new technologies quickly while the rest struggle to make use of them.<\/p>\n
The structure of the U.S. economy makes things even worse. The U.S. has shifted from vertically-linked industrial sectors\u2014where innovations could naturally travel through supply chains\u2014to horizontally spread service sectors that resist transformation because they depend on human judgment. These \u201cstagnant\u201d sectors, as the economist William Baumol called them, now account for roughly half of GDP in advanced economies.<\/p>\n
Firms are also saddled with debilitating administrative and regulatory compliance costs, which I estimate are now past the topping point at which they strangle innovation.<\/p>\n
Adding to the paradox: the concentration of capital in AI-linked companies starves the rest of the economy of investment needed to be AI-ready. If hospitals, schools, logistics companies, and retailers can\u2019t invest in digital infrastructure and workforce retraining, the broad-based productivity gains that justify today\u2019s AI valuations will never arrive.<\/p>\n
AI could still defy the paradox: unlike previous digital waves, it is a cognitive technology that can reason and make judgments, precisely what\u2019s needed to unlock productivity in labor-intensive Baumol sectors. But only deep adoption across a broad spectrum of the economy will realize that potential. Firms need to allocate capital to workers and workflows, not just chips and data centers.<\/p>\n
That\u2019s a possible silver lining if the AI bubble bursts\u2014that the assets financed by irrationally exuberant investors end up reshaping the economy for the better. Canals in the 1830s, railroads in the 1880s, electrification in the 1920s, telecoms and the internet in the late 1990s\u2014each ended in painful collapse, yet the physical infrastructure created in those speculative booms laid the foundations for decades of later prosperity.<\/p>\n
Will data centers, semiconductors, and AI models prove equally long-lasting? Perhaps. But that process will take decades, not months or years. In the short term, the more concentrated the bet, the more severe the potential reckoning.<\/p>\n
No prior bubble spanned so many dimensions of the economy simultaneously\u2014GDP growth, consumer spending, equity markets, debt markets, and venture capital all tethered to a single theme.<\/p>\n
That is not an economic launchpad. It is a vulnerability of historic proportions.<\/p>\n
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.<\/p>\n
#U.S #market #focused #single #betbut #AIs #payoff #decades<\/p>\n","protected":false},"excerpt":{"rendered":"
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