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The world's largest financial institutions are sounding the alarm. The IMF is warning of a potential abrupt revaluation of AI-related tech stocks that could mark the end of the investment boom and trigger macrofinancial instability. An alert that resonates with the recent warnings of Jamie Dimon, CEO of JP Morgan, and even Sam Altman, boss of OpenAI.
The numbers make you dizzy. AI-related investments have increased by 0.4% of American GDP since 2022, a pace that is certainly lower than the 1.2% recorded between 1995 and 2000 during the dot-com bubble. But the financial scale is worth it.
According to experts, if big tech companies like Nvidia and Alphabet lost just 20% of their value, that would mean a loss of $4.4 trillion in the markets. In the worst-case scenario, with a fall of 50%, we would be talking about 11 trillion dollars evaporated.
The Magnificent Seven (Microsoft, Apple, Google, Google, Google, Amazon, Amazon, Amazon, Amazon, Amazon, Apple, Google, Google, Google, Google, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Amazon, Meta, Nvidia, and Tesla) now represent nearly 35% of the S&P 500's market capitalization and have generated over 70% of the performances since the beginning of 2023. An increasing concentration that worries regulators.
Valuation is reaching dizzying heights: the 10 largest stocks in the index are trading at a multiple of 29 times the expected profits, compared to 19 times for the rest of the S&P 500.
The paradox is striking. Despite 30 to 40 billion dollars invested in generative AI, 95% of organizations get no return on investment, according to MIT. The Grand Continent. Only 5% of pilot projects generate millions of dollars in value.
Microsoft, Meta, Alphabet and Amazon are multiplying the pharaonic ads. Microsoft is talking about $30 billion in investments in the current quarter alone, or $120 billion annualized. UBS forecasts a 67% explosion in global AI spending to reach $375 billion.
The managing director of the IMF, Kristalina Georgieva, issued a clear warning to investors: “Fasten your seat belts: uncertainty is the new normal.” Favorable financial conditions mask worrying trends, especially in terms of job creation.
The Bank of England joined these concerns, saying that the risk of a sharp market correction has increased as valuations seem exaggerated for AI-focused tech companies.
The admission is surprising. The head of OpenAI believed that investors were “overexcited” about artificial intelligence, saying: “When bubbles happen, smart people are overexcited by a core of truth.”
This Frankness Contrasts with the Consistently Optimism. OpenAI is also preparing to raise funds that would value the company at 500 billion dollars, the highest valuation ever obtained for an unlisted company.
Jamie Dimon, CEO of JP Morgan, warns that a significant correction in the stock market could occur in the next two years. Goldman Sachs and Morgan Stanley expect shares to fall by 10 to 20%.
But not everyone is betting on a systemic crash. Pierre-Olivier Gourinchas, chief economist at the IMF, points out that investments are not based on debt but on the liquidity of tech companies, which would limit the impact of a correction.
For e-commerce decision-makers and entrepreneurs, several lessons are emerging:
The extreme concentration of valuations on a few actors creates systemic vulnerability. To manage your business in 2025, vigilance is required in the face of what some analysts already describe as the largest speculative bubble in modern economic history.
Sources:
A stock market phenomenon where asset prices greatly exceed their intrinsic value, fuelled by excessive optimism on the part of investors.
The total value of a listed company, calculated by multiplying the number of shares by their unit price.
Return on investment, indicator measuring the profitability of a project in relation to the amounts invested.
A stock market indicator measuring the relationship between the price of a share and earnings per share, used to assess whether a company is over or under valued (a high multiple suggests overvaluation).