US tech stocks have entered a correction phase, with a deepening sell-off in AI-related companies and semiconductors. This downturn is largely attributed to investor concerns over overcrowded equity positioning and increasing corporate debt levels as the AI build-out progresses. Nvidia Corp.'s recent deals, totaling over $750 billion, have triggered worries among investors about artificially inflated demand for AI, leading to a reassessment of the sector's valuations.
The impact of this sell-off has been particularly severe in Asia, where major chipmakers have seen substantial declines. SK Hynix Inc. slumped as much as 13% and Samsung Electronics Co. fell up to 10%, dragging down South Korea's Kospi Index by 9%. Japan's Nikkei 225 Stock Average and Taiwan’s benchmark gauge also fell almost 4%. The Philadelphia Semiconductor Sector index, which tracks the top 30 US-traded companies in the industry, fell around 4.5%. Analysts like Kyle Rodda from Capital.com highlight that investors fear excessive capital expenditure and spending by AI companies will erode returns, while Hebe Chen from Vantage Global Prime noted that doubts over spending, returns, and valuations are deepening.
Several factors are fueling investor anxiety, including growing threats of competition from China. A report from The Information, indicating a Chinese state-backed company has begun mass-producing immersion deep ultraviolet lithography machines, has particularly alarmed investors and caused shares of Japanese chip-equipment makers like Nikon Corp. and Tokyo Electron Ltd. to slide more than 9%. Google's parent company raising its capital spending forecast to as much as $205 billion for the year has also reignited concerns about a lack of fiscal discipline in the race for AI dominance. With many megacap technology companies, including Microsoft, Meta, Apple, and Amazon, set to report earnings this week, along with SK Hynix and Samsung, investors are keenly looking for signs that these companies can justify the billions of dollars they have poured into AI technology.
