The AI trade is over. Top Wall Street analysts say the AI opportunity might be just starting

The crash that was widely predicted just last summer hasn’t arrived yet. There was no single day when the AI stock market euphoria buckled, no Lehman moment, no front-page meltdown. Instead, over the better part of a year, Wall Street did something far more methodical—and far more telling: It slowly, deliberately, and almost silently wound down its euphoric investments in AI.

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“You know, that’s a really interesting way to put it,” said David Royal, chief investment officer at Thrivent, in a recent interview, when asked if the bubble had already burst and nobody noticed. “I think I agree with that … It came down in a pretty orderly way.”

Royal centered his analysis on Nvidia, the giant that became the face of the AI investment supercycle and yet has seen its stock price stagnate for roughly three quarters even as its earnings continued to grow at a blistering pace. The result: Its forward price-to-earnings multiple has compressed from the low 30s to around 20. That’s not a collapse. That’s a controlled descent. New research from Goldman Sachs’ and Morgan Stanley’s top equity analysts agrees with the emerging pattern in markets: a slow climb-down after the bubble warnings months ago.

The numbers tell the story

Goldman Sachs’ Peter Oppenheimer put it slightly differently from Royal, in a note published Tuesday morning: The technology sector has just endured one of its worst periods of relative underperformance compared with the rest of the global market since the early 1970s. The IT sector now trades at a forward P/E below consumer discretionary, consumer staples, and industrials—a positioning that would have seemed inconceivable just 18 months ago.

The selloff wasn’t irrational panic. It was a repricing driven by a simple, nagging question: What exactly are the hyperscalers getting for all that capital expenditure? Spending among the largest AI cloud providers has surged to historic levels as a share of cash flow from operations, yet the history of technology breakthroughs—from railways to the early internet—is littered with infrastructure booms that produced meager returns for the builders and outsize gains for those riding on top. Oracle, an extreme example, has had to raise fresh financing and recently laid off workers to manage the load. Investors, apparently, finally started reading the history books.

The Mag Seven splinters

For most of the AI boom, the Magnificent Seven moved in near-lockstep, a monolith of correlated bets. That correlation has now broken down. Goldman notes that the three-month realized pairwise correlation among the major AI hyperscalers—Amazon, Google, Meta, Microsoft, and Oracle—has fallen sharply, with rising dispersion among the dominant names. The monolith has cracked, giving way to a market that demands differentiation.

Part of what cracked it was fear of disruption from within. The release of successive generations of large language models—including DeepSeek—raised uncomfortable questions about competitive moats. For the first time in a generation, investors started to seriously question the terminal values of long-duration growth companies. Fears of AI disruption led to a sharp de-rating of software stocks specifically, which fell from a premium market multiple to parity in a matter of months. Investors began hunting for the AI era’s version of Kodak: a dominant company hollowed out by the very wave it helped create.

Oppenheimer framed this as the “technology value opportunity,” calling it a once-in-a-lifetime chance to acquire stocks that have been expensive for decades. This has been one of the weakest periods of relative returns for technology over the past 50 years and a stark contrast from most of the post–Great Financial Crisis era, he noted. The air coming out of the AI trade balloon, in other words, is a rare opportunity for investors to buy the dip. Or perhaps, the fear of a bubble is a healthy thing to have in volatile times like these.

Oppenheimer’s views are aligned with those of Morgan Stanley’s chief U.S. equity strategist Michael Wilson, who wrote in his weekly note the day before that the S&P 500 is “carving out a low” and that the correction is well advanced in both time and price. Wilson’s thesis is built on a critical data point: The S&P 500’s forward P/E multiple has already fallen 18% from its six-month peak—a level rarely exceeded in the absence of a recession or aggressive Fed tightening, neither of which is Wilson’s base case.

Specifically regarding the hyperscalers, Wilson was unambiguous. The Magnificent Seven, he writes, now trade at roughly 24 times forward earnings—nearly the same multiple as consumer staples at 22 times—yet carry more than three times the forward earnings growth of that defensive sector. “From a relative value perspective,” Wilson wrote, “the group looks quite attractive here after having already been through six months of consolidation and correction for reasons that are now well understood.” Those re