Tech Giants' Tribulation: The Divergence Between 2026 U.S. Tech Seven Giants' Financial Reports and Stock Prices

Ask AI · Why is the market so harsh on the return on investment for tech giants’ AI?

In the first quarter of 2026, Wall Street staged a confusing magical show.

Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia, Tesla—these seven companies known as the “Magnificent Seven”—have, according to market data, delivered their tenth quarter of over 25% profit growth in the past eleven quarters. Nvidia’s data center revenue for the quarter hit an astonishing $62.3 billion, up 75% year-over-year; Meta’s annual operating profit margin reached 41%, while the overall profit growth rate for the seven giants in Q4 was 27.2%, far surpassing the 9.8% growth of the other 493 companies in the S&P 500.

However, these numbers did not bring applause but a uniform wave of sell-offs.

Nvidia’s stock dropped 5.5% in a single day after earnings; Microsoft’s stock price fell over 23% year-to-date; Tesla, Amazon, and Alphabet were all affected. The market seemed to collectively say: We’re no longer interested in this report card.

This sharp divergence between fundamentals and stock prices is not merely a technical correction. Behind it are multiple cracks simultaneously opening: AI enters the “ROI audit period,” capital markets begin to rigorously question every dollar invested; the outbreak of the Iran war rewrites the energy cost equation, directly impacting the economic viability of AI data centers; the Federal Reserve’s hesitation in the face of rising inflation leaves high-multiple valuations without relief; and tariffs and antitrust restrictions tighten the survival space for giants on both cost and compliance fronts.

More profoundly, a historic capital rotation is quietly underway, pushing the once golden tenet of “mindless holding of tech giants” into a reconsideration crossroads.

#01

The bill of the AI feast—Wall Street begins a strict “ROI audit”

If the past two years were the “wishing pond era” of AI, then in the first quarter of 2026, Wall Street finally started counting the coins at the bottom.

$530 billion—this is the minimum expected investment by the seven tech giants into AI in 2026. The upper limit is $650 billion. Meta raised its full-year expenditure guidance to $115–135 billion, and Google and Microsoft’s annual investment plans remain at an astonishing level above $90 billion. Most of this money flows into building AI data centers, massive GPU procurement, and the development of competing large models.

The problem is, money flows in, but profits have yet to flow out proportionally.

On the hardware side, Nvidia’s sales remain fiery; but on the application and software side, there are very few “killer apps” that can truly turn AI capabilities into profit growth for enterprise clients. Microsoft’s Azure cloud business continues to grow, but the penetration rate of Copilot subscriptions has not met the most optimistic expectations. Large investments are creating capacity, not converting into cash flow. This “capital expenditure outpacing revenue realization” rhythm has made the market start to worry about the so-called “AI capital expenditure cliff”—when this money-burning race finally needs to deliver returns, who holds the stronger hand?

What makes the market even more uneasy is an unexpected signal from an unlikely direction.

In early 2026, DeepSeek demonstrated the possibility of achieving top-tier inference capabilities at extremely low computational costs. This may still be technically controversial, but it planted a seed of doubt in investors’ minds: if algorithm optimization can significantly reduce dependence on top-tier GPUs, how can Nvidia’s proud hardware premium logic justify itself?

Nvidia’s full-year GAAP gross margin slightly declined from 75% to 71.1%—a small number in itself, but market interpretation saw it as an early sign of intensified competition and the fading of the hardware monopoly halo. Its forward P/E ratio fell from over 35x to around 21x, reflecting not poor performance but a shaken narrative logic.

Meanwhile, the entire group of seven giants, with a market data forward P/E ratio once as high as 28.3x, had already priced in a “perfect expectation.” Such “perfect pricing” is a double-edged sword: as long as results are good, the market remains indifferent; once there are slight flaws, a wave of sell-offs ensues. Even Nvidia’s record-breaking quarterly report couldn’t prevent its stock from falling—because the market demands not just “beating expectations,” but “destroying expectations.” This threshold has become almost cruelly high.

#02

Black swan arrives—2026 Iran war’s deadly squeeze on AI economics

On February 28, 2026, the closure of a waterway triggered a valuation earthquake on Wall Street thousands of kilometers away.

The US and Israel launched a coordinated strike against Iran, which then announced the closure of the Strait of Hormuz. This strategic choke point, responsible for transporting 20% of the world’s oil and liquefied natural gas, turned within days from a geographical name into a nightmare for global energy markets. Brent crude oil prices surged from $68 to over $119 per barrel in about three weeks—this was a brief price peak, not a slow climb, but an almost vertical jump. The blood of the global economy suddenly became expensive and scarce.

The damage to tech stocks from this war goes far beyond market panic.

Wall Street quickly realized a structural contradiction that had been deliberately ignored: AI, by nature, is an extremely power-hungry beast. Large AI data centers run 24/7; a medium-sized data center’s annual electricity consumption can rival that of a small city. When energy costs suddenly double, these carefully built AI profit models become like castles on sand—foundations start to loosen. The Guardian’s analysis hits the mark: the high energy costs triggered by the Iran war threaten the “fragile economics” of AI prosperity—accurately describing how the ROI logic established in a low-energy-price era must be re-examined at oil prices of $119.

A more covert damage comes from supply chain risks.

Conflict zones are not only oil-producing regions but also critical sources of semiconductor raw materials. Qatar supplies one-third of the world’s helium—an indispensable material for chip cleaning processes; Israel and Jordan together supply two-thirds of the world’s bromine, a core component of semiconductor flame retardants. When these raw material supply chains fracture, investor anxiety about the capacity of tech giants in subsequent quarters becomes very tangible.

These dual blows form a brutal logical loop: high energy costs squeeze AI data center profits; supply chain disruptions restrict hardware expansion; both are the core pillars of the AI investment narrative over the past two years. When these pillars wobble, the high-multiple valuations built upon them naturally cannot sustain.

#03

Macroeconomic and policy headwinds— from “Golden Girl” to “Stagflation Cloud”

A good macro environment is an invisible protector of high valuations for tech giants. But in the first quarter of 2026, this protector turned away.

The next three headwinds do the same thing: raise the implicit costs of holding tech stocks.

At the start of the year, market consensus expected the Fed to enter a continuous rate-cutting cycle, bringing relief to overvalued assets. However, the surge in oil prices caused