AI bubble fear triggers volatility in Wall Street 

The recent market volatility shows growing concern about whether the rapid rise of artificial intelligence can be supported by real earnings. With tech companies investing heavily in AI infrastructure, investors are questioning if the industry’s growth can keep up with its soaring valuations. 

Wall Street had a turbulent week around November 20 as concerns about a possible artificial intelligence stock bubble caused major technology stocks to fall. Recent trading has raised doubts about whether the rapid rise in AI investments can be supported by actual earnings. During one of the sharpest selloffs, the Nasdaq Composite fell about 2.2% and the S&P 500 dropped 1.6%, showing that investors across many parts of the market were becoming uneasy.  

Many investors had become used to tech stocks driving the market upward for most of the year. Some investors saw the pullback as an early test of whether the rapid gains driven by artificial intelligence could be sustained. 

An AI bubble happens when stock prices for artificial intelligence companies grow much faster than those companies’ real performance. This can occur when investors become overly enthusiastic about future potential without enough evidence that profits will match the hype. If expectations become unrealistic, stock prices can drop quickly once investors reassess the risks.  

Throughout the week, the technology sector led the declines. Several AI and semiconductor companies, which had been some of the market’s strongest performers earlier in the year, saw noticeable losses. For example, Nvidia fell 3.2% on November 20 alone, and few days later, its stock was down roughly 11% for the month. Analysts pointed out that many of these companies have high valuations and may be vulnerable whenever confidence dips. A high valuation means that the stock price is already assuming strong future earnings, so even a small disappointment can cause sharp drops.  

A major reason for investor caution is the enormous amount of money being directed into AI infrastructure. Companies across the tech industry have invested heavily in data centers and powerful AI chips. Reuters reported that several analysts are unsure whether businesses will adopt AI technology fast enough for companies to earn back their spending in the near term, especially if overall economic growth slows.  

Building data centers requires massive amounts of energy, specialized cooling systems, and expensive equipment, which means that the cost of expansion is extremely high. If demand for AI tools grows slower than expected, companies might end up with large expenses that can take years to recover. This risk has become an important part of the debate over whether AI investments are growing too quickly. 

Markets briefly recovered after Nvidia reported stronger-than-expected earnings and forecast higher revenue, citing continued demand for AI chips. Nvidia CEO Jensen Huang addressed concerns directly during an analyst call on November 19, 2025, saying, “There’s been a lot to talk about an AI Bubble. From our vantage point, we seen something very different.” This reassurance helped stabilize investors sentiment temporarily, especially since Nvidia is considered one of the most important companies in the AI sector. 

Even so, the relief was short lived. While Nvidia’s results helped fuel a brief global rally, concerns returned as the week progressed. Reuters reported that tech stocks quickly gave up their early gains as investors grew uneasy about high valuations and the possibility of an AI bubble Some analysts said that the market may be entering a phase where investors look more closely at earnings instead of relying on the general excitement surrounding AI. 

Looking ahead, upcoming corporate earnings and key economic reports will play an important role in determining whether the markets stabilize or remain volatile. Investors are now looking for clear evidence that AI companies can deliver consistent and sustainable profits. They also want to see whether demand for AI tools remains strong across industries such as healthcare, finance, and transportation, since broader adoption would help justify recent investments. 

As the industry moves forward, investors will be watching closely to see which part of the AI surge can genuinely stand the test of time. 

Cover image: Anh Pham Tuan/Vectors