In a striking warning that’s reverberating across financial circles, Torsten Slok, chief economist at Apollo Global Management, has sounded the alarm: Wall Street’s obsession with artificial intelligence may be inflating a bubble even more dangerous than the infamous dot-com crash of 2000.
Back then, investors poured billions into internet startups with little more than a domain name and a dream. Today, the magic word is “AI,” and the stakes are even higher.
According to Slok’s analysis, the top ten companies in the S&P 500—many of which are deeply entrenched in AI development—are now more overvalued than their tech counterparts were at the peak of the dot-com era.
His chart comparing forward price-to-earnings ratios paints a sobering picture: the market is betting on AI with a level of confidence that borders on reckless.
The AI boom has been fueled by soaring expectations. Companies like Nvidia, Microsoft, Apple, Alphabet, and Meta have seen their valuations skyrocket, driven by investor belief that AI will revolutionize productivity, unlock new revenue streams, and reshape entire industries.
But Slok and other analysts caution that these expectations are being priced in as certainties, not possibilities.
Unlike the broader market, which has shown modest growth, the S&P 500’s recent gains are disproportionately concentrated in these few tech giants.
This narrow rally means that the health of the entire stock market is precariously tied to the performance of a handful of firms. If even one falters, the ripple effects could be catastrophic.
Adding to the concern is the lack of tangible returns. While AI has dazzled with its potential—from generative models to autonomous systems—many companies have yet to demonstrate meaningful cost savings or revenue growth from their investments.
The gap between hype and reality is widening, and history suggests that such gaps don’t close gently.
Gordon Johnson, a Wall Street analyst, predicts that the AI bubble could burst within 18 to 24 months. He points to speculative spending, inflated valuations, and the absence of proven business models as key indicators of an impending collapse.
Johnson warns that the turning point may come when AI systems cause high-profile failures or regulatory backlash, shaking investor confidence.
Ray Dalio, founder of Bridgewater Associates, echoes these concerns. He notes that while AI is undeniably transformative, the current investment frenzy is reminiscent of the late 1990s, when enthusiasm for the internet blinded investors to fundamental risks. Dalio emphasizes that high interest rates and geopolitical tensions could be the pin that pricks the bubble.
Despite the warnings, the market continues to surge. Every corporate earnings call now includes an “AI strategy,” and startups are racing to brand themselves as AI-first. But as Slok’s chart reminds us, valuation without substance is a dangerous game.
The lesson from 2000 is clear: revolutionary technology does not guarantee revolutionary profits. The internet did change the world, but it also wiped out trillions in market value when the bubble burst. AI may be bigger than the internet—but that only raises the stakes.
If earnings don’t catch up to expectations soon, Wall Street could be headed for a painful reckoning. And this time, the fall might be steeper, the losses deeper, and the recovery slower. Investors, take note: history doesn’t repeat itself, but it often rhymes.