AI chip stocks plunge as election results spark infrastructure fears

A massive selloff for chipmakers

The technology sector faced a severe correction on Thursday as investors reacted to a cooling outlook for artificial intelligence infrastructure. Nvidia led the decline, pushing the Nasdaq to its worst day in 19 months. The stock lost almost $450 billion in market capitalization in a single session.

Qualcomm also contributed significantly to the selloff, dropping more than 9% after providing a disappointing earnings forecast for the current quarter. Other major players in the semiconductor space, including Advanced Micro Devices, Micron, and Applied Materials, all saw double-digit percentage losses.

The broader market sentiment shifted as the combination of rising interest rates and high capital requirements began to weigh on stocks. Investors are increasingly concerned that companies tied to AI infrastructure are facing a situation of too much debt and not enough revenue.

Political shifts and local pushback

The recent midterm election results have introduced new variables for the AI buildout. Several states with the most ambitious plans for AI data centers turned blue, leading to fears about the future of large-scale construction. Specifically, Democrats won key contests for governor and the Senate in states like Texas and Ohio.

Voters in several regions are beginning to push back against the physical footprint of these facilities. According to Ballotpedia, 41 local ballot measures in 10 states were up for a vote to place various restrictions on data center construction. Voters sided against these projects in every measure except for one in Harwood, North Dakota.

Meta President Dina Powell McCormick noted that building these data centers is going to be harder following the elections. She mentioned that some victorious governors have expressed a desire to meet to ensure that investments and jobs do not move elsewhere. This suggests a shift toward more localized control over where and how these massive facilities are built.

Supply issues and rising costs

While demand for AI technology remains high, the path to delivering it is becoming more expensive and complicated. Qualcomm CEO Cristiano Amon stated that the company does not have a demand issue but rather a supply issue. He noted that if the company had more supply, it would likely be performing better in the current market.

A global memory shortage is currently jacking up prices for essential components. This makes it difficult for manufacturers like Intel and AMD to secure key supplies, which in turn leads to surging prices for consumer devices. Intel recently reported a 78% jump in data center revenue, but its stock was crushed by a weak forecast regarding the memory shortage.

Investors are now questioning whether the current growth in the data center business is sustainable. While AMD reported that its data center sales more than doubled in the latest period, the market is looking past the raw numbers. There is growing uncertainty about whether buyers of the technology will be able to put the hardware to productive use.

The road ahead for hyperscalers

The major hyperscalers—Alphabet, Amazon, Microsoft, and Meta—are all navigating a difficult environment. These companies have laid out ambitious infrastructure spending plans that extend well past $100 billion a year. However, Meta recently went free cash flow negative, joining Alphabet and Amazon in that trend during the latest quarter.

The stocks of these tech giants dropped between 2% and 4% on Thursday as the market weighed these spending plans against current profits. Analysts suggest that while the underlying technology will continue to develop, the physical infrastructure may face delays. These delays could cause stocks to trade off as the pace of construction slows.

Market observers describe the current situation as a knee-jerk reaction that could lead to significant concerns. Because the answers to these economic and political hurdles are not yet clear, the market remains in a state of uncertainty. The next few months will likely determine if the AI buildout can maintain its current momentum despite these new obstacles.