AI Stocks Slump as $720 Billion Spending Push Sparks Profitability Fears

3 articles · Updated · The Associated Press · Jun 23

Sandisk sank 13.6% Tuesday, Marvell dropped 9.4% and the iShares Semiconductor ETF slid 7.9% as investors sold AI-linked names after a powerful rally.
Up to $720 billion in 2026 spending planned by Alphabet, Amazon, Meta and Microsoft has sharpened doubts over whether AI data-center buildouts can generate enough profits and productivity.
Alphabet is raising $80 billion and plans to spend as much as $190 billion this year, while Amazon sold $54 billion of bonds and targets about $200 billion in AI investment.
Tech’s recent surge left valuations stretched: Marvell’s price-to-earnings ratio neared 100, Sandisk shares are up more than 700% this year, and some analysts said the pullback also reflected profit-taking.
Morningstar warned heavy AI capital spending could create future oversupply, pressure pricing and leave semiconductor companies especially exposed even as some bulls say Asian AI demand remains strong.

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The Associated Press10h ago

AI Stocks Slump as Investors Question Profitability, Take Profits

The Independent12h ago

AI stock slump raises the question if investors are just taking profits or getting very nervous | The Independent

Toronto Star10h ago

Sharp drops in Big Tech companies pull the Nasdaq lower

11 Sources

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The $575 Billion Question: AI Infrastructure Spending, Investor Skepticism, and the 2026 Tech Power Shift

Overview

In 2026, major technology companies rapidly shifted from considering AI adoption to aggressively investing in AI infrastructure, driven by the emergence of highly capable AI models and new business use cases. This surge in investment created a powerful feedback loop: as advanced AI models unlocked more opportunities, demand for critical infrastructure intensified. Tech giants like Alphabet, Amazon, Meta, and Microsoft, supported by strong growth and large cash reserves, committed to expanding foundational elements such as cloud infrastructure and specialized hardware. As a result, overall spending on AI infrastructure is projected to reach trillions of dollars, with no signs of slowing down.

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