AI stocks led a major market selloff, erasing $1.3 trillion, sparking debate on whether the AI bubble is bursting or it's just a sector rotation and profit-taking. Analysts from Goldman, Bridgewater, and BofA offer conflicting views.
* **Stocks had their worst day in over a year.** The [Nasdaq fell 4.2% and the S&P 500 dropped 2.6%](https://www.cnn.com/2026/06/05/markets/stock-market-sell-off-fed), the worst session since April 2025, as AI names tumbled and the odds of a Federal Reserve rate hike rose on a stronger-than-expected jobs report. * **Semiconductors led the carnage.** [Chip stocks slid hard](https://www.cnbc.com/2026/06/04/chipmaker-equities-micron-marvell-broadcom-intel.html) after Broadcom's AI-chip outlook disappointed: Nvidia fell about 6% and dipped below a $5 trillion valuation, with Micron, AMD, and Marvell falling alongside it. # The case for "just profit-taking" * **The Dow hit a record the same day.** Even as chips cratered, the [Dow climbed to a record high](https://www.cnbc.com/2026/06/03/stock-market-today-live-updates.html) as money rotated into health care and financials. That is the signature of a sector rotation, not a market-wide flight from stocks. * **The classic bubble-burst signals are missing.** Wall Street analysts point out that [corporate earnings never collapsed and there has been no dot-com-style IPO frenzy](https://fortune.com/2026/04/07/the-ai-trade-is-over-top-wall-street-analysts-say-the-ai-opportunity-might-be-just-starting/), leading some to argue the AI opportunity is still early rather than ending. * **Goldman's CEO says the AI selloffs are "too broad."** David Solomon has [argued the rout is overdone](https://www.bloomberg.com/news/articles/2026-02-10/goldman-s-solomon-says-software-selloff-has-been-too-broad), expecting AI to produce "winners and losers" and "plenty of companies" to "pivot and do just fine" rather than face wholesale destruction. # The case for "the bubble is bursting" * **Ray Dalio says it is a bubble that will burst.** The Bridgewater founder [warned](https://www.bloomberg.com/news/articles/2026-06-03/dalio-sees-ai-bubble-bursting-as-wealth-is-converted-into-money) that the AI market is showing the classic signs of a bubble that will eventually pop as paper wealth gets converted back into cash. * **BofA says the chart looks like March 2000.** Bank of America's Michael Hartnett [told clients](https://www.cnbc.com/2026/06/01/the-stock-market-just-did-something-eerily-similar-to-the-dotcom-bubble-top-in-2000.html) the market just echoed the dot-com top, with gains dangerously concentrated in a sliver of stocks, and pushed his closely watched Bull & Bear indicator into "sell" territory. * **The math still does not close.** By Sequoia's widely cited estimate, [the AI industry needs to earn roughly $600 billion a year to justify its hardware spending](https://www.tomshardware.com/tech-industry/artificial-intelligence/ai-industry-needs-to-earn-dollar600-billion-per-year-to-pay-for-massive-hardware-spend-fears-of-an-ai-bubble-intensify-in-wake-of-sequoia-report) — a shortfall that has intensified fears of an AI bubble. From : [https://aiweekly.co/issues/wall-street-cant-agree-if-the-ai-bubble-just-burst](https://aiweekly.co/issues/wall-street-cant-agree-if-the-ai-bubble-just-burst)
The article discusses a sell-off in AI-related tech stocks, raising doubts about whether the massive spending on artificial intelligence will yield returns. It highlights market volatility, with major companies like Micron, Nvidia, and Alphabet experiencing significant drops.
Tech stocks were set to wipe out over $1 trillion in market value amid growing investor skepticism about massive AI spending, with Amazon and Intel plunging after lackluster earnings and Alphabet suffering a record $500 billion loss.
US tech stocks fell sharply for a second consecutive day as investors grew worried about massive AI spending nears $1tn, with Intel plunging 30% and Alphabet losing over $500bn in market value amid concerns of an AI bubble.
Discussion of the AI bubble debate, noting that focus is on American AI companies while Chinese AI firms may be more resilient due to low token prices, potentially dominating if US companies collapse.