AI Bubble Warning: Could Collapse Entire US Economy
Concerns are mounting among experts that the extensive capital flowing into artificial intelligence companies may be artificially inflating the entire U.S. economy, raising comparisons to past economic bubbles.
Paul Kedrosky, an investor, recently noted to the Wall Street Journal that current spending on AI infrastructure has already surpassed the investment seen in telecom and internet infrastructure during the dot-com era two decades ago. He suggested this massive AI spending could be functioning as a “private-sector stimulus program,” potentially masking the full impact of recent tariffs.
Further highlighting the scale of this investment, Neil Dutta, head of economic research at Renaissance Macro Research, revealed that capital expenditures for AI have contributed more to U.S. economic growth this year than the entirety of consumer spending combined. This unprecedented situation has led some to warn of a potential economic downturn even more severe than the dot-com crash, should the AI industry fail to deliver on its ambitious promises.
The market is currently experiencing a surge of AI-driven hype, with investor enthusiasm propelling company valuations to record highs. Tech journalist Brian Merchant, in his newsletter Blood in the Machine, pointed out that while Apple was the first to reach a $1 trillion valuation in 2018, nine AI companies have since achieved similar or greater market capitalizations. Notably, AI chipmaker Nvidia’s valuation has tripled to an astounding $4 trillion in less than a year. Microsoft also recently reached a $4 trillion valuation, reporting booming sales in its Azure cloud computing business and a record $30 billion in capital spending on AI in a single fiscal quarter, according to CNN.
Despite these soaring valuations, questions linger about the long-term return on investment. While AI chatbots have gained widespread popularity, their operational costs—including training, running, and maintenance—remain exceptionally high, leading to significant utility expenses for AI companies. Microsoft, for instance, primarily profits by selling computing power to other companies attempting to monetize AI. The challenge for these companies lies in scaling their offerings profitably, especially when users are accustomed to freemium models like OpenAI’s ChatGPT and Anthropic’s Claude. If widespread profitability proves elusive, the current market structure could face instability.
Adding to the complexity, the AI sector is witnessing intense competition for talent, with firms offering astronomical contracts to poach skilled professionals. Domestically, the White House has shown little interest in regulating the industry or enforcing antitrust measures, as noted by the Wall Street Journal. This regulatory vacuum means a significant threat could emerge from international competition, particularly from China, which is rapidly advancing in the global AI race.
The ultimate destination of this immense investment remains a multi-trillion-dollar question. With the U.S. economy increasingly supported by unprecedented AI infrastructure spending, understanding the potential aftermath of an AI market correction—and identifying the resulting winners and losers—becomes crucial. The debate also continues whether this phenomenon is a genuine bubble or, as Wall Street firm Citi recently suggested, a “longer-term bull market.” The stakes are exceptionally high, placing the onus on AI companies to demonstrate both the financial and societal benefits of their innovations to shareholders.