AI Stock Correction: Over Two-Thirds of Tech Stocks Down 20% From Recent Highs

A significant correction is underway in the technology markets, with 69% of stocks within the S&P 500 Information Technology sector having dropped over 20% from their recent 52-week intraday highs. This decline places these stocks into bear market territory by some definitions. Semiconductor companies have been particularly hard hit, with shares of Micron Technology (MU) falling 25%, Broadcom (AVGO) down 21%, and Marvell Technology (MRVL) dropping 30% from their recent peaks. These declines occurred despite the sector's impressive performance in the second quarter.

Several factors are driving this selling spree. Firstly, investors are engaging in profit-taking after the PHLX Semiconductor Index (SOX) achieved record gains in the second quarter. Many analysts suggest this pullback is a natural progression after a substantial rally. Secondly, the immense scale of artificial intelligence (AI) investments and the uncertainty surrounding their returns are causing market apprehension. According to Bridgewater Associates, U.S. technology giants are projected to collectively invest approximately $650 billion in AI-related infrastructure this year.

Renewed expectations of interest rate hikes from the Federal Open Market Committee (FOMC) have also intensified pressure on tech stocks. Higher interest rates increase financing costs for high-growth technology companies and diminish the present value of future earnings, negatively impacting valuations. Furthermore, reports of Chinese AI startups, such as DeepSeek, developing their own AI chips are fueling competitive concerns, potentially reducing reliance on major players like Nvidia.

These developments have had a broad impact across markets. The tech-heavy Nasdaq Composite (COMP:IND) and Nasdaq-100 indices have experienced notable declines. The semiconductor sector's sell-off has spread globally, affecting South Korea's Kospi Index and Japan's Nikkei. Analysts note that such swings reflect a balance between profit-taking and opportunistic buying.

In a broader economic context, the technology sector's share of the U.S. stock market, including communication services, now surpasses levels seen during the late 1990s dot-com bubble, raising concentration risks. Investors are questioning whether the massive spending by big tech companies on AI will ultimately pay off. Goldman Sachs estimates that tech companies will spend $7.6 trillion by 2031 to build thousands of new data centers. However, skepticism persists regarding consumers' and businesses' willingness to pay sufficiently for AI services.

Analysts and market expectations largely view the current downturn as a healthy reset of expectations rather than the end of the AI boom, believing the fundamental drivers of AI adoption remain strong. While volatility is expected to persist, these periods often present opportunities rather than reasons for panic for long-term investors. Moving forward, focusing on companies that can translate innovation into revenue and margin growth will be crucial. Additionally, if the hardware sector experiences a correction, there might be a shift towards AI hyperscalers and software/networking stocks as potential leaders.