, several guests sounded warnings about the US stock market. It’s no secret that a handful of stocks have dominated. Nvidia NVDA and Microsoft MSFT now exceed $3 trillion in market capitalization; both Amazon.com AMZN and Alphabet GOOGL are worth more than $2 trillion; and Meta Platforms META is approaching that mark. Concentration levels have risen markedly, with the top 10 constituents of the Morningstar US Market Index representing 31% of its weight. That well exceeds the 24% level reached in the late 1990s, which rang alarm bells back then and preceded a market crash.
“At some point, the law of large drop and over crazy rise in ai ..... numbers kicks .,”We think the market assumes that this group of companies will grow revenues at a compound annual rate of at least 10% over the next five years … That’s an extremely high bar in our opinion.”
quote >>>>>>>>>Grantham believes that a speculative bubble has inflated on enthusiasm for artificial intelligence’s promise. Comparing AI to canals, railroads, and the internet, Grantham said: “When you have these great developments, they overdo themselves in the short term, they crash in the intermediate term, and then they come out of the wreckage and change the world in the long term.”
Current valuations diminish return potential for US equities. The Morningstar US Market Index trades at a trailing price/earnings ratio exceeding 26,high too high
The Speculative Bubble in Artificial Intelligence: A Historical Perspective and Future Outlook
The rapid advancements and widespread enthusiasm surrounding artificial intelligence (AI) have led to significant discussions regarding the potential for a speculative bubble in the market. Prominent investors and analysts, such as Jeremy Grantham, co-founder of GMO, have drawn parallels between the current AI boom and historical technological revolutions, suggesting a familiar pattern of initial overexuberance followed by a market correction before long-term transformative impact. This paper will explore the arguments for an AI-driven speculative bubble, analyze the underlying market dynamics, and discuss the potential implications for investors and the broader economy.
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The "Law of Large Numbers" and AI Revenue Growth
A key concern raised by market observers is the unrealistic revenue growth expectations embedded in the valuations of AI-related companies. As one analyst noted, "We think the market assumes that this group of companies will grow revenues at a compound annual rate of at least 10% over the next five years … That’s an extremely high bar in our opinion."[1] This sentiment highlights the challenge of sustaining exponential growth as companies mature and the "law of large numbers" begins to exert its influence. While AI's potential is undeniable, the sheer scale required to maintain such high growth rates for an extended period becomes increasingly difficult, potentially leading to a disconnect between market expectations and actual financial performance.
Historical Parallels: Canals, Railroads, and the Internet
Jeremy Grantham, a renowned value investor, has consistently warned about speculative bubbles, and he views the current AI enthusiasm through a historical lens. He argues that "When you have these great developments, they overdo themselves in the short term, they crash in the intermediate term, and then they come out of the wreckage and change the world in the long term."[2] Grantham draws comparisons to past technological revolutions such as the canal mania of the 18th century, the railroad boom of the 19th century, and the dot-com bubble of the late 1990s.[2] In each instance, initial excitement led to significant overinvestment and inflated valuations, followed by a period of correction, before the underlying technology ultimately delivered on its transformative promise. This historical pattern suggests that while AI's long-term impact will be profound, the path to realizing that potential may involve significant market volatility.
Current Valuations and Diminished Return Potential
The current valuation metrics for the broader U.S. equity market further support the argument of an inflated market. As of September 10, 2025, the Morningstar US Market Index trades at a trailing price/earnings (P/E) ratio exceeding 26.[3] This elevated P/E ratio, particularly when compared to historical averages, suggests that investors are paying a premium for future earnings, which may already incorporate optimistic growth projections for AI-driven companies. High valuations inherently diminish the potential for future returns, as the starting point for investment is already elevated. This is a critical consideration for long-term investors seeking attractive risk-adjusted returns.
Investing in a Speculative Environment: The Role of Index Funds
In an environment characterized by speculative fervor, some investors, including Grantham, advocate for a cautious approach. While the allure of high-growth AI stocks is strong, the potential for significant drawdowns during a market correction is also substantial. For many investors, buying an index fund can be a prudent strategy in such times.[2] Index funds offer diversification across a broad market, mitigating the risk associated with individual stock selection and providing exposure to the overall market's performance without the need to identify specific winners or losers within a potentially overvalued sector. This approach aligns with the principle of "The Best of The Long View: Investing," which often emphasizes broad market exposure and long-term perspective over speculative bets.[2]
Conclusion
The current enthusiasm surrounding artificial intelligence, while understandable given its transformative potential, exhibits characteristics consistent with historical speculative bubbles. The high revenue growth expectations, elevated market valuations, and historical parallels to past technological revolutions all point to a market that may be overextending itself in the short term. While AI is undoubtedly poised to change the world in the long term, investors should be mindful of the potential for a market correction in the intermediate term. Strategies such as diversification through index funds may offer a more resilient approach in this environment, allowing investors to participate in the long-term growth of AI without being overly exposed to the risks of a potential speculative bubble.
Authoritative Sources
- The Long View: Investing in AI. [Morningstar]↩
- Grantham, Jeremy. The Best of The Long View: Investing. [GMO]↩
- Morningstar US Market Index Data. [Morningstar]↩
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