For years now, certain experts have warned that the AI industry is a massive bubble waiting to burst. The enormous hype driving a market frenzy, they say, could lead to a collapse if it’s exposed to be built on widespread overpromising.
Most recently, Apollo Global Management chief economist Torsten Slok warned that the current AI bubble is starting to look even worse than the market conditions leading up to the dot-com implosion of the late 1990s.
“The difference between the IT bubble in the 1990s and the AI bubble today is that the top 10 companies in the S&P 500 today are more overvalued than they were in the 1990s,” Slok wrote in a note that was widely circulated online.
A chart shows the price to earnings (P/E) ratios of the top ten performing companies in the S&P 500 against the rest of the index. A high P/E ratio, generally speaking, indicates that a stock’s price is extremely high relative to its earnings.
The chart shows that the P/E ratio continues to creep higher and higher over the last five years, well above the rates we saw throughout the 1990s. In other words, the top ten companies in the S&P 500 are far more overvalued than they were in the years leading up to the dot-com crisis.
Slok is ringing the alarm bells over the apparent market frenzy, driven by tech titans that are heavily invested in the AI industry. By index weighting, AI chipmaker Nvidia leads the pack in the S&P 500, followed by Microsoft, Apple, Amazon, Meta, and Alphabet, all of which have made multibillion-dollar investments in AI.
Yet earnings are still lagging far behind the astronomical spending on building out infrastructure, with some tech leaders already showing early signs of hesitancy, given the massive P/E discrepancy.
Slok is far from the first to compare the current hype surrounding AI to the dot-com bubble. Even in 2023, when OpenAI’s ChatGPT was only a few months old, analysts warned investors were overinvesting in unproven tech.
AI critic Ed Zitron has also compared the situation to the subprime mortgage crisis of 2007, which led to the collapse of the US housing market.
Silicon Valley’s endless appetite for AI was seriously tested earlier this year when a Chinese AI company called DeepSeek demonstrated that its AI chatbot, which cost a fraction of the computing power to train as conventional models, could trade blows with the latest large language models from the likes of OpenAI, Meta, and Google, triggering a more than $1 trillion selloff at the time.
How long investors will continue to prop up sky-high valuations of the key players in the AI race remains to be seen. Despite an explosion in popularity for tools like ChatGPT and Google’s Gemini, revenue still pales in comparison to the tens of billions of dollars being spent on data center expansions.
According to an S&P Global research note published in June, the generative AI market is projected to grow at a breakneck pace, reaching an aggregate revenue of $85 billion by 2029. However, when you consider that’s only a little more than the over $60 billion Meta will spend on capital expenditures this year alone, tech companies still have a lot of reassuring to do that their massive bet on AI will eventually pay off — and not lead to the sequel of one of the biggest stock market crashes in history.
More on the AI bubble: OpenAI May Be in Major Trouble Financially