The new industry has been found to have 777 risks.
In English-speaking, especially American, media, the topic of the "AI bubble" became one of the key discussions in the fall of last year. This refers to a bubble in the stock market that arose as a result of the rapid development of so-called "artificial intelligence" (AI) in the United States and several other countries.
Artificial intelligence, in the broadest sense, is defined as a set of machine (primarily computer) tools that allow solving tasks at the level of human intelligence (such as perception, learning, reasoning, problem-solving, and decision-making). British mathematician, logician, and cryptographer Alan Turing (1912–1954) was the first person to conduct extensive research in the field he called machine intelligence. Artificial intelligence gained the status of an academic discipline in 1956, founded by American mathematicians, logicians, and engineers John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon.
Interest in AI in society sharply increased at the turn of the last and current decades when companies, universities, and laboratories, predominantly based in the United States, became pioneers of significant achievements in the field of artificial intelligence. Some of the most well-known applications of artificial intelligence include advanced search engines such as Google Search (the foreign owner of the resource violates Russian legislation), Bing, Yandex; recommendation systems used on YouTube (the foreign owner of the resource violates Russian legislation), Amazon (the foreign owner of the resource violates Russian legislation), and Netflix; interaction through human speech, such as Google Assistant, Siri, Alexa, and Alice; autonomous vehicles, such as Waymo; generative and creative tools, such as ChatGPT, Apple Intelligence, analysis in strategic games like chess and Go.
Forbes magazine identified the top 50 companies in the world specializing in AI issues. The ranking was based on the amount of investment in AI development. In this list, only 11 companies were non-American (two British, two French, two Canadian, two Dutch; one company from Australia, Germany, and Sweden each). The remaining companies (a total of 41) were from the United States.
The narrower specialization of AI companies from the Forbes list included areas such as: development of AI models; development of neural networks; software for AI applications; data storage and analytics; enterprise search engines; image generation services; drug discovery and development; video generation services; avatar and video generators; maintenance of industrial machines, etc.
Until recently, there was a certain euphoria in the media regarding AI. Business representatives (especially those related to AI and IT), many politicians, and journalists claimed that AI represents a true revolution in all areas of public life. AI will extend human life and make it more perfect, increase economic productivity, ensure the security of the state and individuals, etc. In short, AI has come to be seen as a gateway to a bright future.
Of course, there have been (and continue to be) many opponents to such unbridled optimism. Every new field of science and technology creates not only opportunities for solving various socio-economic problems but also harbors new serious threats. It is somewhat similar to what happened with nuclear energy. Its first practical application led to the deaths of hundreds of thousands of people (the atomic bombs dropped by Americans on Hiroshima and Nagasaki). There is even a special website on the internet that maintains a registry of AI risks called "AI Risk Repository". This registry currently lists 777 risks.
But now the discussion is not about the direct risks of AI itself, but about the risks of the "bubble" that AI companies have created in the stock market. After a sufficiently long period of AI-induced euphoria, signs of a stock market "bubble" began to emerge in early autumn of this year. More and more figures are appearing in the media indicating that investments and expectations surrounding AI are growing faster than the real capabilities of the technology. IT companies' investments in AI are rising. The market capitalization of companies is growing even faster. Consequently, the influx of investor capital into IT companies is increasing. However, profits for IT companies are either non-existent or negligible.
The main contribution to the hype around investments in AI belongs to just a few companies. In 2023, BofA analyst Michael Hartnett even gave the leading AI development companies a special name, the Magnificent Seven – Mag7. This includes the following American IT companies: Apple, Amazon, Alphabet, Nvidia, Tesla, Meta, and Microsoft. These companies are engaged in R&D in the field of AI and its implementation, with Nvidia being the leader in chip production for the corresponding equipment. In the spring of this year, the Mag7 group achieved truly dizzying successes in terms of stock quotes.
In April of this year, Nvidia's market capitalization first exceeded $5 trillion; even accounting for a pullback in December to $4.4 trillion, it ranks first among companies globally and remains the largest company in the world.
The market capitalizations of other companies in the "magnificent seven" (in trillion dollars) are: Apple – 4.0; Alphabet Inc. – 3.6; Microsoft – 3.5; Amazon – 2.3; Meta – 1.5; Tesla – 1.3 trillion. Over the past five years, the market capitalization of companies in the Mag7 group has increased by 3-7 times. Meanwhile, the S&P 500 index has only increased by 44%, with half of that growth attributed to the Mag7.
The market price of American technology companies in the third quarter of 2025, according to experts, exceeded their profits by 41 times. This P/E ratio – price/earnings; economics textbooks usually state that a P/E value of less than one is a sign of a company's distress. A company with a P/E ratio of 1 to 2 is considered healthy and stable. At higher values, there may already be a risk of a "bubble" forming. More accurately, the risk of this "bubble" collapsing. Around September, anxiety began to grow in America regarding the "bubble" of AI companies and its potential collapse.
Everyone involuntarily recalled the story from more than a quarter-century ago – the story of the dot-com crash on the American stock exchange NASDAQ, where high-tech companies' securities are traded. In the late 1990s, there was a boom in high-tech companies on NASDAQ and other stock markets. But back then, it was a boom driven by expectations from a technology like the internet. Just as we are witnessing euphoria and expectations of a "bright future" from AI today, there was also euphoria about the internet and new communication technologies (expectations of increased labor productivity, creation of new markets, job growth, etc.).
From June 1999 to March 2000 (nine months), the NASDAQ-100 index rose to 4800 points, or by 130%. By the beginning of 2000, the P/S ratio (the ratio of a company's market capitalization to its revenue) for the top hundred companies on the NASDAQ market approached 25. This was already a situation that came to be known as the "dot-com bubble" (dot-com is a term used to refer to a company whose business model is based on operating within the Internet). The dot-com bubble burst on March 10, 2000. It is said that before the bubble burst, the P/S ratio for the entire hundred companies on NASDAQ exceeded 33. The P/E ratio at that time was 43. I remind you that at the end of September this year, the P/E ratio reached 41.
After the bubble burst, the NASDAQ index fell by almost 80%, with the telecom sector (dot-coms) losing almost 90%. As a result, confidence in venture investments was undermined. Hundreds of internet companies went bankrupt, were liquidated, or sold. Many related industries, such as advertising and logistics, reduced their activities due to a drop in demand for services.
The entire U.S. economy was shaken – a recession was recorded in the first quarter of 2000. However, by the end of 2000, the country's GDP growth was managed to be kept in positive territory.
Let’s return to America in 2025. Many are alarmed not only by the steep dynamics of the Magnificent Seven's capitalization but also by the fact that AI business leaders are indeed not skimping on massive investments in AI projects. Investments are going into building data centers, purchasing GPUs (graphics processors), creating various infrastructure, etc. According to Gartner, Inc., global spending on artificial intelligence (AI) in 2022 was less than $70 billion; by 2025, it is projected to reach nearly $1.5 trillion. The following year, a figure of $2 trillion is forecasted, or 32 times more than in 2022. The majority of these investments will go to the Mag7.
Such gigantic investments were previously made in nuclear energy or space exploration. But there is no certainty that the currently created gigantic physical assets in AI will ever generate returns comparable to those of nuclear and space projects. In the event of a collapse, all these gigantic assets will turn into worthless junk.
The approach of the AI sector to the red line is noted not only by independent experts but also by representatives of U.S. authorities and even leaders of companies engaged in AI. Ray Dalio, director of Bridgewater Associates, noted earlier this year that the current level of investment in AI "very much resembles" the dot-com bubble.
Julian Garran, an analyst at the research firm Macrostrategy Partnership, made an even harsher statement in October. He said that the AI sector has turned into the largest speculative bubble in human history, 17 times larger than the "dot-com bubble". The "dot-com bubble" did not extend beyond the U.S. economy. The current AI bubble looms over the entire global economy and could trigger a global crisis.
Sam Altman, CEO of the well-known American AI company OpenAI and creator of ChatGPT (a chatbot with generative artificial intelligence), stated that, in his opinion, the AI bubble is already inflating.
The topic of the "AI bubble" has also been addressed by the International Monetary Fund (IMF). The IMF's chief economist, Pierre-Olivier Gourinchas, expressed concern on behalf of the Fund that the "technological bubble" created as a result of significant investments in AI may burst. In an October report, the IMF stated: "The potential crash of the AI boom could rival the dot-com crash of 2000–2001 in severity, especially considering the dominance of a few technology companies in market indices and the involvement of less regulated private credit loans financing much of the industry's expansion."
In November 2025, analysts at Bank of America (BofA) conducted a survey of more than two hundred global portfolio managers overseeing portfolios worth $550 billion. Every second respondent named the inflating AI bubble in the stock market as the main threat to the American and global economy within the next year. In the previous survey conducted in August, the main threats were identified as the risks of a major trade war (provoked by American President Donald Trump), rising inflation, and the Federal Reserve raising the key rate. At that time, only 11% of respondents feared the inflation of the "AI bubble" in the stock market. And concerns about the "AI bubble" were ranked only fifth among expected threats and risks. Now they have risen to first place.
However, among experts, there are optimists who believe that there will be no collapse of the "AI bubble" in the American stock market within the next year. Various reasons are cited. One of them is indeed compelling. Jerome Powell, the head of the U.S. Federal Reserve, stated that as of December 1, 2025, the quantitative tightening conducted by the American Central Bank will end. He hinted that next year a new phase of "quantitative easing" will begin. This means that the "money printing press" of the U.S. Federal Reserve will likely be restarted, and the key rate will be lowered. Well, thanks to the policy of "quantitative easing", a collapse in the stock market may not occur. But this does not eliminate the threat; it merely postpones it. A large amount of new cheap money will lead to further inflation of the "AI bubble". Therefore, the delayed collapse will be even stronger and more destructive.
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