Why Big Tech Stocks Are Falling as Investors Question AI Returns

Why are big tech stocks falling?

Investors are asking whether the money big tech is pouring into AI will come back as profit fast enough to justify share prices. The doubt has shown up in several sell-offs this year. Fortune reports that the Nasdaq closed down 2.9% and the S&P 500 fell 1.8% on Friday, October 30 ^[2]. Nasdaq 100 companies lost more than $1 trillion in market value that day, and Fortune says weak guidance from chipmaker Intel also played a role ^[2].

How much is the AI buildout costing?

Fortune reports that the largest tech companies are set to invest as much as $828 billion in capital expenditures this year, covering data centers, high-powered chips and other infrastructure ^[2]. Based on company earnings releases and calls, Amazon is expected to spend $220 billion in 2026, Alphabet up to $205 billion, Microsoft about $170 billion, Meta up to $145 billion and SpaceX up to $88 billion ^[2].

A bill of that size has to be paid before returns show up in earnings. Fortune also reports that several banks, including Evercore and Bank of America, see AI-related capital expenditure reaching $1 trillion in 2027 ^[2].

Is the spending already paying off?

The evidence is mixed. Fortune reports that Google’s cloud revenue more than doubled last quarter to $30.7 billion, while Microsoft’s Azure grew 48% to about $33.3 billion and Amazon Web Services expanded 39.3% to $46 billion ^[2]. Fortune also reports more than $265 billion in future minimum purchase commitments, mostly for cloud computing and other infrastructure services ^[2].

Those cloud numbers show that demand exists. They do not yet show whether that demand will cover the full cost of the buildout.

When did the doubts start?

The worry began well before October. In mid-February, RTE reported that “Investors are questioning whether heavy spending on AI will generate sufficient returns to justify the lofty valuations of big tech companies,” and that Amazon had shed about 13.85% so far that year ^[1].

In June, BNN Bloomberg reported that Alphabet and Amazon looked set to lose billions of dollars in market value, driven by AI spending concerns ^[3].

What did the sell-off cost, and why?

The Guardian reports that the tech sell-off drove US markets down by hundreds of billions of dollars on Friday. It says the decline had knocked nearly $1 trillion off the tech-heavy Nasdaq in one week and erased about $2 trillion in a month ^[4].

The Guardian’s figures for the Friday move differ from Fortune’s. It says the S&P 500 fell by more than 1%, where Fortune reports 1.8% ^[2][4]. It also puts the Nasdaq composite down more than 3%, where Fortune reports a 2.9% close ^[2][4]. Check the index and the time before you repeat a percentage.

Earnings were part of the cause. Amazon fell 1.8% after reporting weaker profits for the summer than analysts expected, and it said it had spent more this year than anticipated ^[4]. Intel tumbled nearly 30%, and the Guardian says it was flirting with its worst day since 1974 ^[4].

Spending plans moved the other way. Meta Platforms, Alphabet and Amazon raised their spending forecasts further as they race to expand AI infrastructure ^[4]. The Guardian frames the question this article asks: whether the billions being poured into artificial intelligence “can generate returns quickly enough” ^[4].

Does the spending pay back?

The spending Fortune describes runs into hundreds of billions of dollars, so payback depends on revenue from AI products growing at a similar scale ^[2]. Whether that happens is the open question for the next few earnings cycles.

Why does free cash flow matter?

Free cash flow is the cash a company has left after paying for its operations and its capital spending. Fortune reports that “Some of the market’s jitters can be drawn to concerns over free cash flow” ^[2]. When spending rises faster than the cash a company generates, investors have less reason to be patient.

What should AI users take from this?

Shareholders are effectively asking for a timetable, and you can set the same kind of timetable for your own AI use. Before you add another AI tool, subscription or automated workflow, write down the one task it should improve and how long that task takes today. Check again after two weeks. Keep the tool if the time or quality improves, and cancel it if it does not. Compare the tool’s monthly cost with the hours it saves.

What should you watch next?

Watch the next earnings reports for two things: whether companies raise their spending plans again, and whether revenue from AI products grows at a similar pace. If spending keeps rising while revenue lags, the doubts are likely to return.