Summary of Key Points
The most significant change in U.S. tech stocks during the first half of 2026 was a complete shift in the logic of AI investment: from focusing on technology giants with advanced large models to favoring semiconductor companies (especially those in storage and equipment infrastructure) that are actually generating revenue from AI. The semiconductor index rose by more than 100% over the half-year, with storage companies experiencing astonishing gains (Sandisk up 850%, Micron up 300%). In contrast, the traditional "Big Seven" of U.S. tech stocks saw a significant decline in market value due to high AI-related expenses and slow commercialization (a loss of $2.3 trillion in market value in just one month). The market has begun to revalue the semiconductor industry chain, with infrastructure providers becoming the clear beneficiaries.
1. Storage Chip Companies "Made Huge Profits," and the Semiconductor Index Rose by Over 100%
The biggest winners among U.S. tech stocks in the first half of the year were mostly from the semiconductor industry chain, particularly the storage sector:
- Data Highlights: The Philadelphia Semiconductor Index (SOX) rose by more than 100% overall, with a sharp increase of 80% in the second quarter. The top ten companies in the S&P 500 growth ranking were all from the tech industry, including Sandisk (up 850%, the highest performer on the S&P) and Micron (whose market value exceeded one trillion dollars, entering the top ten of the U.S. stock market). Western Data, Intel, and others also saw gains of over 200%. TSMC rose 57%, and ASML, a leader in lithography equipment, increased by 86%.
- Why Has Storage Suddenly Become So Popular? In the past, storage was considered a cyclical stock with large price fluctuations and profits dependent on market conditions. However, AI has changed everything: AI servers require large amounts of high-bandwidth storage (HBM), high-capacity memory (DRAM), and enterprise-level solid-state drives (SSDs), leading to exponential demand that supply has struggled to meet (Micron expects supply shortages until 2027). This imbalance in supply and demand has driven up storage prices, resulting in soaring profits for companies and transforming storage from a cyclical stock into an AI infrastructure asset.
- Comparison with Former AI Stars: Nvidia reached record highs but only gained 7% during the first half of the year (ranking at the bottom of the semiconductor index components). Qualcomm and Broadcom also fell behind because they are no longer the sole beneficiaries of AI growth; the benefits of AI are now spreading across the entire industry chain.
2. The Logic of AI Investment Has Changed: From "Competing on Models" to "Generating Revenue," and the Market Has Become More "Pragmatic"
In the past, investors were interested in who had the most powerful large models. Now, they focus on who is actually making money from AI:
- Shift in Focus: As AI development has progressed, the competition for large models has entered a phase of heavy spending. Investors no longer look at future potential but at current profits. For example, whether Microsoft or Google wins the large model race, both will need to build data centers, purchase servers, and upgrade storage—these companies (storage providers, chip equipment manufacturers, wafer fabricators) have stable demand, which translates directly into revenue and profit.
- Examples: Micron has continuously raised its earnings forecasts due to surging demand from data centers. Sandisk's profit expectations have also been raised due to increased demand. Meanwhile, tech giants like Microsoft (with annual capital expenditures of $190 billion, up 61%) are still incurring high costs, and the market is concerned about when their AI investments will pay off.
3. The "Money Burn Anxiety" of the Tech Big Seven: A Loss of $2.3 Trillion in Market Value in One Month
The traditional "Big Seven" tech stocks (Microsoft, Apple, Google, etc.) performed poorly:
- Microsoft Leading the Decline: Its market value dropped from $4 trillion to $2.77 trillion, a decrease of over 22%. This is due to massive AI-related investments—annual capital expenditures of $190 billion, plus additional costs due to rising component prices. The market is skeptical about whether AI business growth will cover these expenses.
- Apple's Dilemma: Lacking breakthrough AI products and facing higher storage chip prices (increasing costs for Macs and iPads), Apple has become a passive participant in the market changes.
- Collective Market Value Decline: In June alone, the combined market value of the seven stocks fell by $2.3 trillion, marking the worst performance of the year. Tesla and Meta also saw declines, with only Google (up 14%) and Amazon among the few gainers.
- Core Issue: The scale of AI investment exceeds any previous cloud computing cycle, putting significant pressure on the giants' free cash flows. Money has been spent, but the time required to generate profits is longer than expected.
4. AI Profits Are Moving Upstream, with Infrastructure Providers Becoming the Biggest Winners
The new profits created by AI are no longer concentrated in large model companies but are flowing upstream to the semiconductor industry chain:
- In the Past: Internet giants with models and platforms (like Microsoft, which benefited from ChatGPT) received valuation premiums.
- Now: Upstream companies such as storage chip manufacturers, advanced packaging providers, wafer fabricators, and server suppliers are converting AI demand into actual profits. For example, TSMC, ASML, and Micron are essential for AI infrastructure, and all AI-related activities rely on their products.
- Expert Opinion: Zhang Yi, CEO of iMedia Research, states that a major structural reconfiguration of the industry and capital is underway due to the long-term demand for computing power and storage. Technological advancements will create more growth opportunities.
5. The Focus for the Second Half of the Year: Earnings Reports to Determine Who Can Turn AI Investments into Real Cash
The market will no longer focus on "improvements in large model performance" or the scale of capital expenditures but on who can convert AI investments into revenue, profit, and free cash flow:
- Critical Moment: The upcoming second-quarter earnings reports will be a test of the new AI investment logic. Questions include whether companies like Micron and Sandisk can continue to achieve high profits, whether Microsoft and Google's AI businesses are becoming profitable, and whether Apple has any new AI initiatives.
- Investors' Concern: The focus is not on how much money has been invested in AI but on how much profit has been generated from it—this will determine the direction of tech stocks in the second half of the year.
Conclusion
The changes in U.S. tech stocks in the first half of 2026 reflect a shift from AI being a speculative concept to a practical business opportunity. Investors have shifted from betting on the future to focusing on current profits, with companies that provide essential AI infrastructure and can quickly generate revenue becoming the winners. The traditional tech giants must prove that their AI investments will yield real returns; otherwise, they will face continued valuation pressure. The earnings reports in the second half of the year will be a crucial test of this new reality in AI-driven business models.