AI stocks after the 2026 midterms: What changed?

The post-election AI selloff has raised concerns about the pace of infrastructure development. Explore why demand for computing power remains strong.

Key takeaways

  • Post-election volatility in AI stocks appears more like a reassessment of how quickly AI infrastructure can be built rather than a change in the underlying demand for it.
  • Following the midterms, markets were quick to price in a sharp slowdown in development, even as policy implications remain far from clear. The shift in power has created concerns that the infrastructure needed to meet the demand for AI may take longer, and cost more, to build.
  • As demand for AI infrastructure and capacity expands, we continue to see a significant long-term opportunity in related investments. Our view is that the AI buildout could take longer as election outcomes influence permitting and development decisions in certain markets, but demand for computing power continues to outstrip supply and the investment opportunity remains compelling.

Why did AI stocks sell off after the U.S. midterms?

AI and the data center buildout have been central themes in the markets and key issues for the U.S. midterm elections. Shares in the AI ecosystem had risen nearly 40% through October on continued strong demand.1 But the outcome of the Nov. 3 elections, which saw Democrats win control of both the U.S. House and Senate, as well as in many state elections, prompted concerns about the future pace of the AI buildout.

Stocks rallied the day after the election as uncertainty faded, with the S&P 500 up 2%.2 But AI stocks quickly reversed. On Nov. 5, just two days after the election, the Nasdaq fell 6% in its worst day since the Covid-19 plunge of March 2020, and semiconductors dropped 10% (reducing gains for the year to 29%, from a peak of 107% in June).3 The selloff was particularly severe across the companies most exposed to the AI infrastructure buildout.

We believe the election may change the outlook for AI supply but not for demand and that the market is reassessing the pace of AI investment, not the long-term opportunity. In this article, we break down what happened and how investors can position their portfolios as the AI trade continues to evolve. (See the BlackRock Investment Institute’s Bulletin on the midterms for more about overall market implications.)

How could the US midterms affect AI infrastructure?

The issue is not that the demand for AI has weakened. Instead, the outcome of the election has created concerns that the infrastructure needed to meet the demand for AI may take longer, and cost more, to build.

AI investment has been an important strategic and economic priority, but as the scale accelerates at a rapid pace, many are paying attention to the potential impacts of the infrastructure on communities. The magnitude of the Democratic victories has brought data center regulation into even more focus, particularly at the state and local level: across 41 local ballot initiatives nationwide, voters overwhelmingly favored restricting new development.4

Texas is particularly important to the future of AI. Approximately 30% of planned U.S. data center projects in 2028 are slated for Texas.5 Governor-elect Gina Hinojosa, a Democrat, has added to the uncertainty, having called for a pause on new data-center approvals until stronger protections are established around electricity costs, water supplies and community input, as well as the elimination of data-center tax incentives.

Markets were quick to price in a sharp slowdown in development, even as policy implications remain far from clear. Beyond the local ballot measures, much of the concern rests on campaign proposals rather than enacted policy, with considerable uncertainty around the scope and severity of any eventual restrictions.

Sentiment for physical AI has deteriorated alongside buildout

State legislature and Virginia voter polling

Source: Washington Post, LegiScan, George Mason University. Legislation represented by the number of data center-related bills introduced in state legislatures; sentiment represented by Washington Post–George Mason University polling of registered Virginia voters in March 2023 (n=1,002) and March 2026 (n=1,101), margins of error ±3.0 and ±3.4 percentage points, respectively. As of 7/15/2026 (bills) and April 2026 (polling).

Chart descriptions: Bar charts showing the rise in state data center legislation and declining share of Virginia residents comfortable with local data centers. 


What does the AI stock selloff mean for investors?

For investors, it’s important to distinguish between projects being delayed and projects being cancelled.

Much of the data center capacity expected to be built in 2027 is already committed, with approvals and construction plans in place. But the bigger uncertainty is buildouts in 2028. Leading up to the midterms, the BlackRock Fundamental Equities technology team had expected about 66 gigawatts of new data center capacity globally (ex-China) for that year, but lowered its expectations following the election to be closer to 62 gigawatts, with the remaining capacity more likely to be delayed than permanently lost.6 That is a meaningful adjustment, particularly for companies whose valuations depend on rapid growth in AI infrastructure spending. But it doesn't necessarily change the longer-term demand picture.

Ultimately, policy changes may slow the AI buildout, not derail it.

The fundamentals have not deteriorated nearly as much as price action suggests. Capital expenditure growth has accelerated every year, from ~30% in 2024 to ~60% in 2025 to ~100% in 2026, and still hasn’t caught up with demand.7 The three largest cloud providers (Amazon, Microsoft, Google) grew revenues by 56% year-over-year in Q3, accelerating from 48% in Q2.8

Another useful barometer of AI demand is the cost of renting computing power. Despite newer, more powerful chips coming to market, rental prices for Nvidia’s H100 chips are up about 35% year-to-date, including 14% since late September – a clear sign of just how tight supply remains.9

The magnitude of the selloff also reflects an unusually large unwind in investor positioning. Prime brokerage data points to the largest reduction in hedge fund equity exposure in more than 15 years, suggesting the sharp declines have been amplified by technicals rather than a broad retreat from AI by long-term investors.10

BlackRock polling supports that distinction: among respondents planning to make portfolio changes following the selloff, 70% intend to buy AI at lower valuations.11

We expect greater scrutiny of data center development to delay some investment, particularly beyond 2027. But the post-election selloff appears more like a reassessment of how quickly AI infrastructure can be built rather than a change in the underlying demand for it.

Demand for compute remains firm

Silicon Data H100 Rental Index (SDH100RT) — NVIDIA H100 GPU hourly rental rate, last 12 months

Source: Silicon Data, Bloomberg, BlackRock. GPU rental rates represented by the Silicon Data H100 Rental Index (SDH100RT), daily NVIDIA H100 hourly rental rate in $/GPU/hour. As of 10/20/2026.

Chart descriptions: Line chart showing Nvidia H100 GPU rental prices over the last 12 months, which have risen steadily.


How can investors access AI investing opportunities?

Our view is that the AI buildout could take longer as election outcomes influence permitting and development decisions in certain markets. That matters for near-term earnings, but it does not erase the long-term opportunity as demand for computing power continues to outstrip supply and the investment opportunity remains compelling. A slower buildout could pressure near-term valuations across parts of the AI ecosystem, particularly in pockets more levered to rapid capacity expansion.

But demand for computing power continues to outstrip supply, and we believe AI adoption is still in its early stages. Near-term uncertainty will likely remain a catalyst for volatility as the market resets expectations for when capacity arrives, but we continue to see a compelling long-term investment opportunity in AI. (For more, read our Thematic Mid-year Update or explore our AI Implementation Guide for a framework to navigate the evolving AI landscape.)

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Frequently asked questions

The post-election selloff appears more like a reassessment of how quickly AI infrastructure can be built rather than a change in the underlying demand for it. The outcome of the Nov. 3 elections, which saw Democrats win control of both the U.S. House and Senate, as well as many state elections, prompted concerns about the future pace of the AI buildout.

AI stocks are not in a bubble, in our view. Gains for AI and related stocks are being supported by earnings, AI infrastructure is serving real demand, and we believe the technology’s largest economic applications are still ahead.

The dot-com bubble was characterized by excessive valuations on unprofitable companies and debt-financed infrastructure built for anticipated future demand.

The AI stock market is being supported by earnings, AI infrastructure is serving real demand, which continues to outpace supply, and we believe the technology’s largest economic applications are still ahead.

Investing in AI carries risks such as data inaccuracy, intense competition, rapid product obsolescence, and dependency on consumer base and end-user demand. Companies may also face sector-specific market and business risks, affecting overall performance.

There’s no single level of AI exposure that’s right for every investor. It depends on your investment goals, time horizon and comfort with risk. You may consider starting by first looking at how much AI-related exposure you may already have through broad equity and technology holdings. From there, investors may consider whether a thematic AI ETF could complement their existing portfolio. Depending on how targeted you want that exposure to be, some funds provide access across the AI stack, while others focus on individual layers, such as semiconductors. Investors may also want to consider how that exposure fits within a diversified portfolio, including assets beyond equities, such as commodities or alternative strategies.

Portrait of Jay Jacobs

Jay Jacobs

Head of U.S. Equity ETFs

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Kristy Akullian, CFA

Head of iShares Investment Strategy

Gareth Feighery

Director, Product Strategy, Fundamental Equity