U.S. semiconductor stocks were on track to lose $2 trillion in market value on Oct. 15 as investors sold shares amid growing concerns over higher interest rates and the cost of expanding artificial intelligence infrastructure, according to Reuters.
The Philadelphia Semiconductor Index, which tracks major chip stocks, fell 3.3% on Thursday, adding to a cumulative market value loss of $1.64 trillion over the previous six trading sessions, Reuters reported.
The sell-off reflects mounting investor concerns about the financing and profitability of the AI infrastructure boom, as technology companies continue to invest heavily in data centers, computing capacity and advanced semiconductors.
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Expectations of further Federal Reserve interest-rate increases have added pressure to the sector. Higher borrowing costs can make large infrastructure projects more expensive and reduce the appeal of highly valued technology stocks.
The market pressure has extended beyond semiconductor manufacturers to companies involved in building and financing AI infrastructure. Reuters reported that debt-related concerns have contributed to declines in shares of data center operators and other businesses tied to the AI investment cycle.
The broader technology sell-off has also spread across international markets, with Asian semiconductor stocks among the hardest hit. However, concerns about financing costs and market valuations do not necessarily indicate that demand for AI technology is disappearing.
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Investors are increasingly weighing the expected returns from AI-related spending against the substantial capital required to support it, leaving semiconductor stocks vulnerable to shifts in interest-rate expectations and sentiment toward technology investments.
The latest decline also raises questions about whether semiconductor valuations have outpaced the near-term financial returns from AI investments. While demand for advanced chips remains central to the expansion of AI services, investors are increasingly focused on revenue growth, profit margins and whether heavy spending will deliver sustainable returns over time.