Policy & Regulation

AI stocks plunge as Democrats’ midterm sweep fuels policy fears

The Dow fell 3.44% and the Nasdaq lost 5.52% after Democrats’ midterm gains revived concern over AI regulation, data-center power use and infrastructure costs.

Stocks plunge as Dem midterm sweep fuels AI regulatory concerns
Stocks plunge as Dem midterm sweep fuels AI regulatory concernsbsdrouin / pixabay
By Sophie Lindqvist6 min read

Why it matters

  • Dow Jones Industrial Average fell 1,833.06 points, or 3.44%, Thursday.
  • Nasdaq Composite fell 5.52%, its worst day since April 2025, and closed at least 10% below its Oct. 6 record close.
  • Nvidia fell about 9.26%; Philadelphia Semiconductor Index plunged more than 12%.
  • IREN, Applied Digital and Nebius Group each fell more than 14%.
  • S&P 500 fell 4.36%; Tesla fell about 10.77%; SpaceX dropped 9.05%.

By Sophie Lindqvist

How broad was the AI rout?

The Dow Jones Industrial Average fell 1,833.06 points, or 3.44%, on Thursday as a sharp selloff in AI stocks hit Wall Street. The Nasdaq Composite dropped 5.52%, its worst day since April 2025, and closed in correction territory.

Correction territory meant the Nasdaq finished at least 10% below its Oct. 6 record closing high. The S&P 500 fell 4.36%. Technology and chip stocks were among the hardest-hit groups as investors weighed what Democrats’ sweeping midterm victories could mean for AI regulation and data center development.

The losses reached well beyond Nvidia. Data center operators, power suppliers, equipment companies and several large technology and growth stocks also fell. In one session, an election result became a new variable in the investment case for AI infrastructure.

In short, investors repriced the political and cost risks around the AI buildout across the market.

What did the election change?

Thursday’s selloff came one day after U.S. stocks rallied following the midterm elections. eToro market analyst Jakub Rochlitz said: “The obvious catalyst for the sharp selloff is that markets are pricing in the midterm results, after yesterday saw markets rise across the board as the political risk premium unwound.”

Rochlitz tied the reversal to the election result and the market’s swift return to infrastructure concerns. The election gave investors a clearer signal on which policy risks deserved attention: campaign proposals affecting data centers and the electricity they need.

Rising electricity prices helped turn the rapid construction of power-hungry data centers into a political issue during the midterm campaign. Some Democrats called for restrictions or pauses on new projects, according to Rochlitz.

Rochlitz said: “The market’s interpretation is that the AI infrastructure buildout will become slower and more expensive, which is rewriting growth expectations across the whole supply chain.”

In plain terms, the market now expects a slower and costlier AI buildout, with that expectation reaching every major layer of the supply chain.

Who sold hardest?

The company moves showed how widely the concern spread.

  • Nvidia fell about 9.26%. The Philadelphia Semiconductor Index plunged more than 12%.
  • Meta Platforms fell 3.96%. Amazon and Google parent Alphabet also declined.
  • Data center operators IREN, Applied Digital and Nebius Group each fell more than 14%.
  • Companies tied to supplying power and equipment to the AI boom also declined. They included GE Vernova and Constellation Energy.
  • Tesla shares plunged about 10.77%. SpaceX dropped 9.05%.

The breadth of that list matters. The selloff reached chip companies, large technology platforms, data center operators, and power and equipment suppliers. It also reached companies outside the groups explicitly tied to AI infrastructure, showing that the repricing had spread into the wider market.

Argent Capital Management portfolio manager Jed Ellerbroek told Reuters: “This feels like the capitulation phase for the data center capex beneficiary stocks, especially the semiconductors. But I think the magnitude of the moves is outsized.”

Ellerbroek’s two sentences separate the mood of the selloff from its scale. He calls the mood capitulation, then questions whether the size of the moves is justified. His comments capture the tension in the session: sentiment had changed sharply, yet he still viewed the magnitude as excessive.

In short, investors sold the companies most exposed to data-center capital spending, and the reaction spread across both AI infrastructure and the broader market.

Why did data centers become the political issue?

The data center was the mechanism linking AI policy to construction and electricity. Rising electricity prices had already made the pace of new projects politically sensitive before the election.

After the Democrats’ broad victory, investors had a stronger political signal to weigh. That did not require a detailed law. It required only a reassessment of whether campaign calls for restrictions or pauses would slow projects.

The expectation then moved through the supply chain. The market linked continued data-center construction to semiconductor sales, exposed operators to project constraints, and tied power and equipment suppliers to the same buildout.

The reported selloff concerned future assumptions rather than reported changes in current activity. The report described no changes in AI orders, project cancellations or enacted rules. Investors were marking down policy, timing and cost expectations.

In plain terms, investors repriced future AI infrastructure economics, not evidence that current AI demand had vanished.

What does the correction mean?

The Nasdaq’s move carries more weight because it put the index into correction, meaning it sat at least 10% below the Oct. 6 record close. Its 5.52% fall was also the worst session since April 2025, while the Dow lost 3.44% and the S&P 500 fell 4.36%.

Many analysts cited in the report said the scale of the declines, now extended into a second straight day, suggested changing sentiment. They saw further selling starting with Friday’s Asian sessions as a likely risk.

Japan’s Nikkei and Korea’s Kospi had each risen more than 20% this year. Both declined significantly after Wednesday’s Wall Street rout, and the report said they might decline again on Friday. Their next trading sessions offered an early test of whether US losses would travel or begin to unwind.

The sequence also showed how quickly political expectations can reverse. One day earlier, stocks had rallied across the board after the election. Rochlitz described that rally as an unwinding of the political risk premium, and the latest session focused on data-center costs and restrictions.

The correction status matters because it marks a broad loss from the peak, not merely one volatile session. It also gives investors a clear measure of how quickly AI-related expectations can reset.

In short, policy risk was large enough to push the Nasdaq into correction, even as Ellerbroek warned that the moves might be outsized.

What could happen next?

The first test comes Friday in Asia, according to the analysts cited in the report. The Nikkei and Kospi could extend the rout after their strong performance earlier in the year, or show that the US reaction is starting to unwind.

The second test is political follow-through. The report covered campaign calls for restrictions or pauses, not a detailed implementation schedule. If those demands become concrete restrictions, they would support the slower-and-more-expensive interpretation Rochlitz described.

If the proposals remain vague, the outsized-move concern from Ellerbroek becomes more important. Markets could recover some ground if investors conclude that election language did not change the underlying buildout case.

For AI investors, the election has added a new risk to the model: data centers may take longer and cost more, forcing supply-chain forecasts to reset. Friday’s Asian session will show whether Thursday’s rout marks a durable policy repricing or a broader mood swing.

Source: moxie.foxbusiness.com

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Sophie Lindqvist

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Staff writer covering regulation, policy and their impact on artificial intelligence and machine learning at AI In Context.

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