Nasdaq falls 2.2% as investors question whether massive AI spending will ever translate into returns
The AI trade that powered US tech stocks to record highs is hitting a wall. The Nasdaq Composite dropped approximately 2.2% as investors began asking a question that had been conspicuously absent during the sector’s euphoric run: what exactly are we getting for all this money?
The S&P 500 followed with a 1.4% decline, dragged lower by the same megacap names that had been carrying it higher for months. Seven companies account for roughly 30% of the S&P 500’s total market value, which means when AI sentiment turns, the broader market feels it immediately.
The numbers behind the nervousness #
This wasn’t a flash crash or a one-day anomaly. It was the second major leg down in recent weeks, following a roughly 4.2% Nasdaq drop on June 5 driven by similar cooling enthusiasm around AI.
The damage was concentrated in the names you’d expect. Micron, Broadcom, Arm, Marvell, and Nvidia were among the hardest-hit stocks. These companies sit at the center of the AI infrastructure buildout, manufacturing the chips and networking equipment that power the data centers behind every large language model and AI application.
The sell-off wasn’t limited to US markets. Samsung and SK Hynix, two of the world’s largest memory chip manufacturers, saw their shares plunge approximately 12% in Asian trading.
AI-related corporate borrowing could exceed $500 billion in 2026, a staggering figure that raises serious questions about balance sheet health across the sector. Companies are borrowing enormous sums to build infrastructure for AI products that haven’t yet proven they can generate proportional returns.
What this means for investors #
When a handful of stocks represent nearly a third of a major index’s value, any sustained rotation out of those names creates outsized downward pressure on the broader market. Capital expenditure commitments in AI are locked in for quarters or years ahead. Revenue growth, on the other hand, depends on enterprise adoption rates that remain uncertain.
When AI-related borrowing approaches the half-trillion-dollar mark in a single year, any slowdown in adoption doesn’t just hurt stock prices. It creates credit risk. Companies carrying heavy debt loads tied to infrastructure that isn’t generating expected returns face a very different conversation with bondholders and lenders.
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