AI stocks erase $13.2 trillion in market value as selloff deepens
A post-midterm rout in chip and infrastructure names has wiped out a staggering share of the AI trade since its 2026 highs
AI stocks have shed approximately $13.2 trillion in market value since their 2026 highs. That tally runs through November 7, after a brutal week that turned a slow leak into a burst pipe.
The losses are concentrated in the companies that build the physical backbone of artificial intelligence: chipmakers, memory suppliers, power providers and the hyperscalers spending heavily on data centers. The trigger was not an earnings miss or a technical breakdown. It was an election.
One day, trillions gone
The sharpest blow landed on November 5, the day after the US midterm elections. The Nasdaq 100 dropped 6.4% in a single session.
That was the index’s steepest one-day decline since March 2020.
Roughly $2.3 to $2.5 trillion in value vanished from the Nasdaq 100 in that one session alone. Wall Street’s fear gauge reacted accordingly. The VIX, which tracks expected volatility in the S&P 500, jumped 70% on November 5, one of the largest single-day increases in its history.
The damage was not confined to AI names. Broader US equities have lost about $5.7 trillion in market value since an October 6 peak. The two figures cover different windows: the $13.2 trillion figure measures AI stocks from their highs earlier in 2026, while the $5.7 trillion covers the whole market over roughly the past month.
Who took the biggest hits
Some of the largest companies on the planet absorbed losses that would dwarf most national economies.
Sector-level declines were just as stark. Memory stocks are down an average of 60% from their 2026 highs. AI power stocks, the companies positioned to keep energy-hungry data centers running, have fallen an average of 53%.
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Those percentages matter more than the headline dollar figures for anyone holding a single position. A 60% drawdown means a stock needs to rise 150% just to get back to even.
There was a modest reprieve on November 6. Markets stabilized somewhat, and chip stocks clawed back part of their losses.
Why an election rattled the AI trade
The selloff was driven by fears that Democratic gains in the midterms could bring tougher rules on data-center construction and AI development.
That concern hits the AI infrastructure story where it lives. The bull case for chips, memory and power has rested on the assumption that the buildout of AI capacity would keep accelerating. Any policy shift that could slow new data centers threatens the demand pipeline behind those valuations.
Notably, the regulatory risk here is a fear, not a law. No specific legislation is cited as the cause. Markets were pricing in the possibility of a stricter environment, and they priced it in quickly.
The political jolt also landed on top of a pre-existing worry. Questions about whether the enormous capital being poured into AI will generate returns that justify it had been simmering in the background. The midterm results gave investors a reason to act on those doubts all at once.
What this means for investors
The first lesson is about concentration. AI-linked stocks have been a major engine of US market growth, which means a downturn in that group drags on everyone, including investors who thought they owned a diversified index fund. The fact that broad US equities lost about $5.7 trillion since early October shows how tightly the market’s fortunes are tied to a narrow set of themes.
The second lesson is about policy sensitivity. AI infrastructure was largely traded as a technology and demand story. This week reframed it as a political one too. Companies whose growth depends on building physical capacity, such as data centers and the power to run them, are exposed to permitting, zoning and regulatory decisions in a way pure software businesses are not.
The third issue is the capex question. The scale of AI spending by companies like Alphabet, Meta and others has been justified by expected future returns. When markets start doubting those returns at the same moment they fear new restrictions, the combination can be harsh.
Disclosure: This article was edited by Vivian Nguyen. For more information on how we create and review content, see our Editorial Policy.
