The AI bubble is a theorized stock market bubble growing amidst the AI boom, a period of rapid increase in investment in artificial intelligence (AI) that is affecting the broader economy.^[1] Speculation about a bubble largely originates from concerns that leading AI tech firms are involved in a circular flow of investments that are artificially inflating the value of their stocks. It has also drawn comparisons between the current environment of tech financing and the dot-com bubble of the 1990s and 2000s.

In late January 2025, the unexpectedly successful launch of the Chinese-made chatbot DeepSeek resulted in concerns about a possible AI bubble. The stock prices of many AI companies dropped, such as Nvidia's shares dropping 17% in one day. Nvidia's share price recovered 8.8% the following day.^[2] In August 2025, a report by Nanda (Networked Agents and Decentralized AI), under Massachusetts Institute of Technology's MIT Media Lab stated "despite $30–40 billion [USD] in enterprise investment into Gen[erative]AI, [...] 95% of organizations are getting zero return".^[3] Spending from US mega caps is expected to reach $1.1 trillion between 2026 and 2029, and total AI spending is expected to surpass $1.6 trillion.^[4]

Due to the growing demand for semiconductors to sustain AI technologies, Nvidia became the highest valued company in the world and the first to ever have reached a market value of $4 trillion in July 2025. The figure had quadrupled since 2023, when it surpassed $1 trillion. The company's value made up roughly 7.3% of the S&P 500, which hit an all-time high.^[5][6] In October 2025, the company's value grew beyond $5 trillion,^[7] rising higher than the GDP of every country except for the US and China, according to data from the World Bank. Over the year 2025, AI-related enterprises accounted for roughly 80% of gains in the American stock market. Some sceptics warned that the rapid rise of AI tech firms may be the result of excessive financial engineering.^[8]

Microsoft disclosed that it had spent almost $35 billion on AI infrastructure in the three months leading up to the end of September. In October, it became the second most valuable company in the world largely due to its 27% stake in OpenAI. While seeing increases in revenue by 18% and in net income by 12%, share values dropped by 4% in after-hours trading amid investors' concerns about the possible costs of sustaining the AI boom.^[9]

In late 2025, 30% of the US S&P 500 and 20% of the MSCI World index was solely held up by the five largest companies, which was the greatest concentration in half a century, and share valuations were reportedly the most stretched since the dot-com bubble.^[10][11] Experts warned that AI companies were extremely overvalued, with the S&P 500 trading at 23 times forward earnings, and the FTSE Index trading at 14 times, showing how expensive the US market had become. The Case–Shiller price-to-earnings ratio for the US market also exceeded 40 for the first time since the dot-com crash.^[11]

Sam Altman, CEO of OpenAI and creator of ChatGPT, stated in 2025 that he believed that an AI bubble is ongoing.^[13] In early 2025, Bridgewater Associates co-chief investment officer Ray Dalio said that the current levels of investment in AI are "very similar" to the dot-com bubble.^[13] In September 2025, the Australian Financial Review said that "If we really are in another share-market bubble, it's surely the most anticipated example in history."^[14]

In October of that year, Jamie Dimon, head of JP Morgan, the largest bank in the US, said he thinks "AI is real" but said he believes some money invested now will be wasted. He also said there is a higher chance of a meaningful drop in stocks over the following two years than the market was reflecting.^[15] Dimon warned that an AI-driven stock crash could result in a lot of invested money being lost, although he acknowledged that AI "[would] pay off […] just like cars in total paid off, and TVs in total paid off, but most people involved in them didn't do well". However, he further stated on AI that "the level of uncertainty should be higher in most people's minds".^[16]

The value of technology company stocks have been inflated based on AI hype regardless of market fundamentals or the financial reality behind monetizing AI products.

OpenAI committed to spending $1.4 trillion over 8 years in building new datacenters, partnering with Nvidia to deliver 10 gigawatts of datacenter compute, with just $13 billion in revenue.^[17][18] This long term spending is funded by debt.^[19] An estimate from Morgan Stanley put global spending on datacenters between 2025 and 2028 at $3 trillion, $1.5 trillion of which is covered by private credit.^[20] OpenAI has failed to present a reasonable roadmap to profitability or how it will pay for these investments. In November 2025, OpenAI said it expected to report annual losses through 2028, including $74 billion in operating losses in 2028 alone.^[21] The Wall Street journal obtained financial documents where OpenAI projects significant profits in 2030 despite preceding years of deep losses.^[22] Deutsche Bank analyst Jim Reid estimated OpenAI's losses amounting to $140 billion between 2024 and 2029.^[23]

Aside from its sizable expenditures in datacenters, OpenAI has also been incurring rising inference costs as time goes on, making ChatGPT increasingly costly to run when a user submits a prompt. In 2024, they spent $3.76 billion on inference which rose to $5.02 billion on inference with Microsoft Azure in just the first half of 2025.^[24] Former Fidelity manager George Noble said that OpenAI is "burning $15 million per day on Sora alone." He also highlighted that AI companies will face diminishing returns in model improvements paired with rising costs, saying that "It's going to cost 5x the energy and money to make these models 2x better."^[25] OpenAI has been projected to run out of money by mid-2027.^[26]

Concerns were raised that leading AI tech firms were using circular financing and investment to artificially boost their valuations. In September, Nvidia made a $100 billion investment into OpenAI, expanding the pre-existing stake that it held in the company. This agreement was made on the expectation that OpenAI would power additional data centres using the GPUs that it had been buying from Nvidia, establishing a circular flow of money.^[30][31]

On 9 September 2025, Nvidia entered into an $6.3 billion agreement with AI cloud-computing provider CoreWeave to purchase the latter's unsold data center capacity through to April 13, 2032.^[32] Nvidia held 7% of CoreWeave shares as at 31 March 2025, and is also supplying GPUs to the company.^[32][33]

In October 2025, OpenAI purchased billions of dollars worth of electronics from AMD, a rival of Nvidia, to supply its development of AI in an agreement that made it one of the largest shareholders in the company. Microsoft also held a large stake in OpenAI, and Oracle Corporation, a computing company, also entered into a $300 billion deal with the company.^[30]

The Bank of England warned of the growing risks of a global market correction due to a possible overvaluation of leading AI tech firms in the stock market, such as OpenAI, which more than tripled its value from $157 billion in October 2024 to $500 billion the following year. These valuations, they claimed, could be further harmed if the infrastructure requirements for sustaining the technology were too high to be met. They added that investors were not properly cautioned about the risks of a stock market crash were AI to fall short of market expectations.^[34]

The International Monetary Fund agreed with and reinforced the bank's claims. Kristalina Georgieva, a Bulgarian economist and the 12th managing director of the IMF, also drew comparisons to the dot-com bubble of 2001, highlighting that a market correction could stunt global growth and weaken the economies of developing countries.^[10]

Debt funding has also raised the risk of the bubble.^[35][36][37] Analysts at Morgan Stanley estimated that debt used to fund data centers could exceed $1 trillion by 2028.^[38]

The AI bubble has drawn comparisons to the dot-com bubble of the 2000s.^[39] Billionaire investor Ray Dalio, who predicted the 2008 Financial Crisis, warned that the AI bubble echoes the dot-com in the overvaluation of tech stocks amid low interest rates.^[40]

Ed Zitron has eschewed direct comparisons to the dot-com bubble, writing that the AI bubble is far larger and more destructive than the dot-com bubble popping was.^[41] The underlying asset powering the AI bubble, GPUs, are much more limited in their costs and utility compared to the dot-com bubble's networking and fiber infrastructure that helped power the internet.^[41] He contextualizes the AI bubble as part of the larger "rot economy" that prioritizes growth-at-all-costs.^[42] In the rot economy, Zitron writes that "Businesses are expected to be - and rewarded for being - eternal burning engines of capital that create more and more shareholder value".^[43] Julien Garran, a researcher and partner at MacroStrategy Partnership, published a report in October 2025 that called the AI bubble "the biggest and most dangerous bubble the world has ever seen" that is 17 times larger than the dot-com bubble.^[44]

Strategies from major financial institutions have largely dismissed concerns regarding an artificial "AI bubble," attributing the surge in equity valuations to tangible fundamental strength rather than speculative mania.

Goldman Sachs chief equity strategist argues that the rapid appreciation in stock prices is substantiated by robust and sustained profit growth in earnings and fundamentals among large-cap AI and technology incumbents. The firm notes that valuation multiples for the market leaders of the post-2022 bull run—specifically forward price-to-earnings (P/E) ratios—remain modest compared to the excesses of the dot-com era.^[45]

Similarly, Morgan Stanley analysts argued the fear of a bubble is "misplaced" or "premature." Their research highlights a structural shift in corporate financial health: the median cash flow and capital reserves of the top 500 US firms are approximately triple those observed during historical bubble periods. Furthermore, they distinguish current market leaders by their durable earnings streams and robust margin profiles, contrasting them with the hype-driven, revenue-negative valuations of the late 1990s.^[46][47]

JPMorgan reinforces this stance, stating that the sector does not meet the classic criteria for a financial bubble. In a December 2025 analysis, the bank applied a five-factor diagnostic framework to the AI rally, concluding that the sector exhibits genuine structural utility rather than pure speculation. The report emphasizes that AI represents a transformative economic driver, with capital inflows tied directly to measurable enterprise growth and revenue generation.^[48]

Federal Reserve Chair Jerome Powell has also distinguished the current economic landscape from the dot-com bubble. Powell posits that the AI sector is underpinned by substantial realized revenue and that the massive capital expenditure (CapEx) directed toward AI data centres is functioning as a major engine of broader economic growth, rather than a sink for speculative capital.^[49]

• Cryptocurrency bubble – Speculative bubble involving cryptocurrency prices
• Digital Revolution – Industrial shift to information technologyPages displaying short descriptions of redirect targets
• Echo chamber (media) – Situation that reinforces beliefs by repetition inside a closed system
• Fourth Industrial Revolution – 2010s–present technological convergence era
• Social media stock bubble – Speculative bubble involving social media
• Speculation – Engaging in risky financial transactions
• Workplace impact of artificial intelligence – Impact of artificial intelligence on workers
• 2024–2026 global memory supply shortage – Semiconductor memory supply crisisPages displaying short descriptions of redirect targets

• Robert Reich on the AI bubble on YouTube