In recent years, the debate over the “AI bubble” has intensified. This article attempts to examine whether AI is in a bubble and what this means for us, drawing on the perspectives of investment valuation, infrastructure, market expectations, and historical comparisons.
Is there an “AI bubble”?
From an economic perspective, a bubble exists when the price of an asset soars far above its fundamental value. The most famous example is the “Tulip Mania” in 17th-century Holland, where speculators drove up the price of tulip bulbs to astronomical heights, ultimately leading to a bursting of the bubble and the evaporation of wealth.
Similar signs are evident in the current AI industry:
1. High Price-to-Earnings Ratios: Approximately one-third of S&P 500 high-tech companies trade at P/E ratios exceeding 50. Nvidia’s P/E ratio is around 50, while Tesla’s is as high as 200. The “Big Seven” (Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla) comprise over one-third of the index, and their stock prices have surged significantly due to the “AI narrative.”
The P/E ratio can be simply understood as the payback period: the lower the P/E ratio, the faster the payback period. For example, suppose a stock has a market price of 24 yuan and earnings per share of 3 yuan over the past year. The P/E ratio is 24/3 = 8, giving the stock a P/E ratio of 8. If inflation is not factored in, the payback period is 8 years. In theory, a lower P/E ratio indicates lower investment risk and greater investment value. A high P/E ratio suggests the market predicts rapid future earnings growth, but may indicate a bubble. It’s important to note that a stock with a price-to-earnings ratio of zero indicates it lost money last year.
2. Infrastructure Overbuilding: Companies are pouring billions of dollars into GPUs, power, and cooling infrastructure. Companies like OpenAI, Nvidia, and Oracle are investing in each other and jointly building hyperscale data centers. This “mutually pumping” phenomenon resembles a Ponzi cycle: money flows between companies, but real user value remains difficult to prove.
Infrastructure bubbles occurred repeatedly in the late 19th century, when railroad investors built thousands of miles of unnecessary track to meet future demand that never materialized. The most recent one occurred in the late 1990s, when anticipation of a surge in internet traffic led to the laying of vast quantities of fiber optic cable, a demand that didn’t materialize until decades later.
3. Inadequate Returns: Expectations for a new technology outstrip reality, and the discussion surrounding it becomes increasingly detached from possible future outcomes. Social media, print, and online media are awash with AI-related content, and the hype surrounding AI has dominated the business world for the past few years. A recent MIT study showed that 95% of 300 publicly disclosed AI projects had zero return on investment, suggesting that the AI craze remains largely at the conceptual and experimental stage, rather than generating large-scale profits.
Sam Altman believes we’re in the midst of an AI bubble. “When bubbles occur, smart people get overexcited about some truth,” he explains. “If you look back at most bubbles in history, like the tech bubble, they were all real. Tech was really important. The internet was really important. People got overexcited. Are we in a phase where investors are overexcited about AI as a whole? I think so. Is AI the most important thing for a long time to come? I think so too.”
This unrealistic expectation is also reflected in AI-related humanoid robots. iRobot co-founder and renowned roboticist Rodney Brooks recently stated that investors pouring billions into humanoid robot startups are wasting their money. This is because the human hand is incredibly complex, with approximately 17,000 specialized touch receptors, which no robot can match. While machine learning has revolutionized speech recognition and image processing, these breakthroughs are built on decades of existing technology used to capture the right data.
Brooks argues that billions of dollars are being invested in expensive training experiments that will never reach mass production.
Historical Echoes of Bubbles
To understand the AI bubble, we can look back at history:
British Railway Bubble (1840s): The British railway transportation industry experienced a stock market bubble in the 1840s. It followed a familiar pattern: as railroad shares rose, speculators invested more money, further driving up the stock prices until they collapsed. The frenzy reached its peak in 1846, when Parliament passed 263 bills establishing new railway companies, planning to build a total of 9,500 miles (15,300 kilometers) of lines. Roughly one-third of the approved lines were never built—the companies either collapsed due to poor financial planning, were acquired by larger competitors before completing their lines, or were ultimately proven to be fraudulent enterprises designed to divert investor funds to other businesses.
American Railroad Speculation (Second Half of the 19th Century): Between 1866 and 1873, 35,000 miles of new track were laid in the United States. Banks and other industries poured money into railroad construction, leading to a rapid expansion that far exceeded actual demand. The collapse of Jay Cooke and Company, a bank heavily invested in railroads, triggered the Panic of 1873. However, the United States eventually developed a national market and transportation system.
The Dot-com Bubble (1990s): This was a stock market bubble that erupted in the late 1990s. Driven by the widespread adoption of the World Wide Web and the internet, many investors were eager to invest in any dot-com company, regardless of valuation, especially if its name contained an internet-related prefix or suffix. Venture capital was easily raised, leading to a rapid increase in the allocation of available venture capital and the valuations of emerging internet startups. The bubble burst in 2000, and the Nasdaq index plummeted 72%, erasing all gains made during the bubble. After the dot-com bubble burst, many startups failed to turn a profit after exhausting their venture capital, or even achieved any substantial revenue or finished products. However, the surviving companies (such as Amazon and Google) fueled a new wave of technology.
This chart shows the contribution of the railroad bubble, dot-com bubble, and artificial intelligence bubble to US GDP, respectively. It’s estimated that by 2025, AI capital expenditures could account for 2% of US GDP, meaning AI’s contribution to GDP growth in 2025 will reach 0.7%.
The AI bubble is similar to previous bubbles in that massive amounts of capital were poured into AI, allowing some startups to secure multimillion-dollar valuations simply by adding “AI” to their names. AI companies expanded infrastructure, adding GPUs, increasing training data, and investing in each other, leading investors to believe returns were in their sights. When companies built excessive infrastructure, outstripping demand, they ultimately suffered a devastating recession due to declining market expectations and inability to repay loans.
At this point, the AI bubble began to burst, leaving behind a vast supply of cheap infrastructure. Most companies built infrastructure that failed to generate profitability and ultimately faced acquisition by larger competitors. While the bursting of the bubble had a severe economic impact, it also fostered future technological advancement and new business models, just as the United States will eventually run out of railroads and fiber optic cables.
Risks and Potential of an AI Bubble
The current AI bubble continues to grow, manifesting itself in the following ways:
1. Valuations detached from fundamentals: If AI companies fail to deliver on their profit promises in the next few years, investor confidence will collapse rapidly, and capital withdrawal will trigger a stock price avalanche. Many startups rely on venture capital for transfusions, and if their funding chains break, widespread closure will occur.
2. Overexpanded infrastructure: An oversupply of GPUs and data centers could lead to a repeat of the oversupply of railways and fiber optic cables. Huge investments in assets that are not immediately profitable could ultimately lead to massive asset devaluation and debt defaults. The long-term costs of energy consumption, land requirements, and cooling infrastructure could also become a crushing burden for companies.
3. Impact on the broader economy: According to Morgan Stanley, the AI industry generates $45 billion annually, and this is based on fabricated accounting. To justify these valuations, the industry would need to achieve $2 trillion in revenue by 2030, a highly unlikely target. (The Wall Street Journal points out that this exceeds the combined revenue of Amazon, Google, Microsoft, Apple, Nvidia, and Meta.)
If the bubble bursts, the consequences could be similar to the 2000 dot-com bubble. Currently, countries are prioritizing AI and accelerating infrastructure development. Investment in AI far exceeds anything seen in the early 21st century. If the bubble is large enough, it could be a repeat of the 2008 financial crisis.
How can ordinary people cope with the risk of a bubble?
For ordinary people, the bursting of the AI bubble will severely impact employment. Tech workers are likely to bear the brunt, with a wave of unemployment further tightening the job market. After the dot-com bubble burst in 2000, many programmers entered a saturated job market, worsening the employment situation. The number of computer science-related university freshmen has declined significantly, forcing the unemployed to change careers.
Secondly, asset devaluation will occur. Individual investors who invest in tech stocks through the stock market, funds, and bonds may suffer significant losses due to falling valuations. If a wave of defaults threatens the solvency of the banking system, the entire economy could stagnate.
With the bursting of the bubble, the economy will slow further. Tech giants are the backbone of today’s investment and employment. If they scale back investment due to the bubble burst, it will not only directly affect millions of jobs but could also drag down sectors such as real estate, consumption, energy, and even tourism, creating a chain reaction. This was already demonstrated during China’s real estate bubble, which triggered a decline in consumer confidence.
Amidst the dual impact on employment and assets, young people’s declining trust in the tech industry may affect their educational and career choices, leading to a further decline in the tech workforce for some time to come.
For the average person, the strategy is to avoid over-concentrating investments in a single sector, especially in highly valued tech stocks. Maintain flexibility in career choices and focus on industries with long-term, essential demand (such as healthcare, energy, and infrastructure maintenance). Understand the opportunities that emerge after a bubble bursts. Just like Google and Amazon after the dot-com bubble, the field of artificial intelligence will ultimately leave behind truly valuable companies and applications.
Conclusion
Artificial intelligence is a crucial future direction, but there’s a significant gap between current market enthusiasm and actual returns. A bubble may have formed, and its bursting point depends on the critical mass of capital information.
The key for us is to recognize the risks posed by the AI bubble while also understanding the foundations its burst may leave behind for future development. In other words, the future of AI won’t disappear due to a bubble, but its historical development path is destined to be more tortuous than today’s narrative.
When the AI bubble bursts, what will be the next bubble? Bitcoin?
Reference Articles
1、I talked to Sam Altman about the GPT-5 launch fiasco：https://www.theverge.com/command-line-newsletter/759897/sam-altman-chatgpt-openai-social-media-google-chrome-interview
2、There isn’t an AI bubble—there are three：https://www.fastcompany.com/91400857/there-isnt-an-ai-bubble-there-are-three-ai-bu
3、OpenAI Teams Up With Oracle and SoftBank to Build 5 New Stargate Data Centers：https://www.wired.com/story/openai-oracle-softbank-data-center-stargate-us/
4、Are We In an A.I. Bubble? I Suspect So.：https://gideons.substack.com/p/are-we-in-an-ai-bubble-i-suspect
5、Pluralistic: The real (economic) AI apocalypse is nigh (27 Sep 2025)：https://pluralistic.net/2025/09/27/econopocalypse/
6、‘Dot-Com Bubble 2.0’ could burst at any time：https://www.reddit.com/r/technology/comments/1ni2qiq/dotcom_bubble_20_could_burst_at_any_time/
7、‘Dot-Com Bubble 2.0’ could burst at any time：https://marxist.com/dot-com-bubble-2-0-could-burst-at-any-time.htm
8、Nvidia adds more air to the AI bubble with vague $100B OpenAI deal：https://www.theregister.com/2025/09/22/openai_nvidia_chips/
9、The AI bubble is the only thing keeping the US economy together, Deutsche Bank warns：https://www.techspot.com/news/109626-ai-bubble-only-thing-keeping-us-economy-together.html
10、The AI bubble is the only thing keeping the US economy together, Deutsche Bank warns | When the bubble bursts, reality will hit far harder than anyone expects：https://www.reddit.com/r/technology/comments/1nqydkg/the_ai_bubble_is_the_only_thing_keeping_the_us/
11、Famed roboticist says humanoid robot bubble is doomed to burst：https://techcrunch.com/2025/09/26/famed-roboticist-says-humanoid-robot-bubble-is-doomed-to-burst/
12、The AI bubble is the only thing keeping the US economy together, Deutsche Bank warns：https://www.techspot.com/news/109626-ai-bubble-only-thing-keeping-us-economy-together.html
13、The AI Bubble grows Ponzi Scheme Symptoms：https://www.ai-supremacy.com/p/the-ai-bubble-grows-ponzi-scheme-symptoms-to-meet-compute-demands?utm_source=post-email-title&publication_id=396235&post_id=174595316&utm_campaign=email-post-title&isFreemail=true&r=7wg20&triedRedirect=true&utm_medium=email
14、维基百科-郁金香狂热：https://zh.wikipedia.org/wiki/%E9%AC%B1%E9%87%91%E9%A6%99%E7%8B%82%E7%86%B1
15、维基百科-日本泡沫经济：https://zh.wikipedia.org/wiki/%E6%97%A5%E6%9C%AC%E6%B3%A1%E6%B2%AB%E7%BB%8F%E6%B5%8E
16、维基百科-美国互联网泡沫经济：https://zh.wikipedia.org/wiki/%E4%BA%92%E8%81%AF%E7%B6%B2%E6%B3%A1%E6%B2%AB
18、维基百科-NET炒作泡沫：https://zh.wikipedia.org/wiki/NFT
19、维基百科-ChatGPT：https://zh.wikipedia.org/wiki/ChatGPT
20、Mark Zuckerberg on Meta’s new Ray-Ban display glasses, the AI bubble, and superintelligence | ACCESS：https://www.youtube.com/watch?v=23FyskyFoP8&t=4119s
21、Sam Altman：https://blog.samaltman.com/
22、Will data centers crash the economy?：https://www.noahpinion.blog/p/will-data-centers-crash-the-economy
23、Railway Mania：https://en.wikipedia.org/wiki/Railway_Mania
24、Wiki- Dot-com bubble: https://en.wikipedia.org/wiki/Dot-com_bubble
25、市盈率：https://zh.wikipedia.org/wiki/%E5%B8%82%E7%9B%88%E7%8E%87
26、Honey, AI Capex is Eating the Economy：https://paulkedrosky.com/honey-ai-capex-ate-the-economy/
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