“A Market Correction Is Coming”: Wall Street Titans Warn of a Crash as AI Bubble Fears Loom

Wall Street Turns Gloomy on New York Stocks
“Massive Investment, Meager Returns” — AI Bubble Fears Shake Markets
AI Industry Dismisses Bubble Claims but Must Prove Value Through Profit

Voices of Caution Grow on Wall Street as Analysts Warn of a Potential New York Stock Market Downturn. Many argue that tech shares in particular have become excessively overvalued and that a correction is imminent. The rising pessimism largely stems from renewed concerns over a possible “artificial intelligence (AI) bubble,” a debate that has persisted since early this year.

Wall Street Bets on a Market Downturn

On the 4th, according to the U.S. Securities and Exchange Commission’s (SEC) 13F filings, Scion Asset Management purchased $912 million in Palantir put options and $187 million in Nvidia put options during the third quarter. A put option gives investors the right to sell a stock at a predetermined price — meaning Scion is effectively betting that the share prices will fall. The firm is led by Michael Burry, the “Big Short” investor who famously predicted the 2008 U.S. stock market crash. Burry employed a similar strategy ahead of the global financial crisis.

Other major investors are also preparing for a possible decline in their own ways. Berkshire Hathaway, led by Warren Buffett, revealed in its third-quarter earnings report earlier this month that its cash reserves hit a record $381.7 billion. The company has refrained from buybacks, a move seen as reflecting concerns over market overvaluation. The so-called “Buffett Indicator” — the ratio of total U.S. stock market capitalization to GDP — currently stands at around 230%, surpassing even levels seen during the dot-com bubble and signaling historically high valuations.

The pessimism has also spread across the investment banking sector. Goldman Sachs CEO David Solomon, speaking at a financial summit in Hong Kong on the 4th, warned that “tech stocks are significantly overinflated” and that the market could decline 10–20% within the next 12 to 24 months. Morgan Stanley CEO Ted Pick echoed that view, saying a 10–15% correction would actually be “a healthy adjustment.”

AI Bubble Fears at the Center of Market Pessimism

At the heart of Wall Street’s growing anxiety lies what many call the “AI bubble.” The theory has gained steady traction throughout the year as massive investments in artificial intelligence have yet to translate into meaningful profits. Major tech companies are expected to invest a combined $750 billion in AI data centers through 2025, while global AI spending is projected to reach $3 trillion by 2029. Yet, so far, Nvidia — which profits from selling vast numbers of AI GPUs — remains virtually the only major firm showing significant returns.

Another concern is the rise of circular investment flows among leading AI players, where companies invest heavily in one another, artificially boosting valuations. For example, last month Nvidia announced a $100 billion investment in OpenAI, shortly after OpenAI signed a $300 billion cloud computing contract with Oracle. Oracle, in turn, is one of Nvidia’s largest customers, spending tens of billions of dollars on its AI chips. In effect, money cycles between these firms — from Oracle’s chip purchases to OpenAI’s investment funding and back to Oracle via cloud contracts.

Such circular transactions — where investors and customers are effectively the same — recall the chaos of the dot-com bubble. Back then, telecom equipment makers such as Cisco, Nortel, and Lucent lent money directly to clients to encourage aggressive equipment purchases. The practice fueled the bubble’s expansion and eventual collapse, leading to massive oversupply and widespread bad debt that dealt a heavy blow to the market.

Without Real Returns, Market Skepticism Unlikely to Fade

The AI industry argues that concerns about an investment bubble are overstated. Speaking at The Wall Street Journal’s Tech Live conference in California on the 5th, OpenAI CFO Sarah Friar said, “There is too much focus on the possibility of an AI bubble,” adding that “given AI’s tangible impact on individuals and industries, more exuberance is actually warranted.” Nvidia CEO Jensen Huang echoed this sentiment, telling local media that “AI infrastructure hyperscalers already operate businesses exceeding $2.5 trillion in value — this is nothing like the dot-com era,” stressing that “we’ve only just begun investing hundreds of billions into a multi-trillion-dollar transformation.”

The U.S. Federal Reserve also maintains an optimistic stance. At a press conference on the 29th, Fed Chair Jerome Powell stated, “The dot-com era was about ideas, but today’s companies have profits and substance.” He emphasized that unlike the early 2000s bubble, today’s AI firms generate real earnings and have established business models.

Still, many analysts say market anxiety won’t subside without tangible results. The only real way to disprove the AI bubble theory, they argue, is through profits that justify the enormous scale of investment. Some experts predict it could take years for massive AI spending to translate into measurable productivity gains. Tony Yoseloff, CIO of Davidson Kempner Capital Management, noted, “It took about a decade after the spread of personal computers in the 1980s for productivity to rise, and five to six years after the internet became mainstream,” adding that “the AI boom could likewise take years before yielding economic results — yet markets are reacting as if those gains are right around the corner.”