A report said the systematic investment in Nasdaq 100 (QQQ), long trusted by Korean retail investors trading U.S. stocks, has entered a new phase. As leadership in the artificial intelligence (AI) industry shifts from existing software to the hardware that supports it—especially semiconductors and memory—the returns of large-cap big techs with heavy weights in the index have been relatively weak.
According to Investing.com on the 27th, the Nasdaq 100 index has risen 1.4% so far this year. Although it has continued a gentle uptrend since the start of the year, it is seen as a stagnant pattern compared with the explosive gains of recent years. Despite overall strength in AI-related stocks, shares of software-centered big techs at the top of the market cap rankings—Microsoft (-3.65%), Meta (-0.2%), and Amazon (3.61%)—have not risen as much as expected.
By contrast, semiconductor and memory stocks directly tied to AI infrastructure are showing clear strength. According to Investing.com, iShares Semiconductor ETF (SOXX), a representative exchange-traded fund (ETF) for the U.S. semiconductor industry, is up 14.46% this year, while iShares Expanded Tech-Software Sector ETF (IGV), which reflects the broader software industry, is down 7.55% over the same period. The gap in returns within tech is widening.
As leadership within the AI industry moves from software to hardware, this shift is being reflected in ETF returns as well. As AI moves from a training focus to an "inference" focus, demand for memory—which determines computational efficiency and data throughput—is surging. In this process, memory manufacturers are enjoying a supplier-advantaged windfall, while the expense burden for big techs that must purchase large volumes is growing.
In fact, major big techs such as Microsoft and Google (Alphabet) are continuing large-scale investments to secure data centers and power infrastructure to avoid falling behind in the AI race. The Bank for International Settlements (BIS) said that capital expenditures exceeding free cash flow (FCF) are inevitable in this process, and that software corporations are turning into an "expense-burdened group."
According to Hana Securities, the year-over-year growth rate of capital expenditures (CAPEX) for Alphabet, Amazon, Microsoft and Meta this year is estimated at 41%, 21%, 34% and 60%, respectively. The combined capital spending outlook for the four corporations this year is $497.8 billion, up 36% from the previous year. That exceeds the 30.6% compound annual growth rate (CAGR) forecast for AI infrastructure investment presented by major research institutions.
By contrast, memory manufacturing corporations are assessed to have entered a structurally favorable phase. The spread of AI services is creating unprecedented memory demand, but supply is failing to keep up. A structure has formed in which an increase in shipment volume (Q) translates directly into improved results.
Kim Dong-Won, head of research at KB Securities, said, "With short-term capacity additions in memory supply realistically limited in 2026–2027, supply shortages are more likely to intensify," adding, "For example, Samsung Electronics' NAND wafer production capacity this year is projected to decrease 5% from a year earlier, so memory prices are expected to enter a brisk upward phase."
This industrial structure shift is being reflected as is in the Nasdaq 100 index. While software big techs that occupy the top of the market cap rankings are sluggish on concerns their profitability will deteriorate, semiconductor and infrastructure stocks in the lower market cap tier are showing strength. However, because lower-cap stocks have small weights, their gains are not offsetting the weakness of large caps.
Experts note that a strategy of mechanically accumulating the Nasdaq 100, as before, is unlikely to guarantee the same performance as in the past. A global strategy manager at an asset manager said, "Considering U.S. Starlink and global sovereign AI projects, it is highly likely that data center-centered capital spending will continue through 2032," adding, "In the short term, the index's gains could concentrate in hardware areas where profitability is becoming visible."
The manager added, "We are approaching more conservatively than before a strategy of mechanically buying indexes with a high software weight."
Lee Kyung-min, a researcher at Daishin Securities, said, "It is important to confirm the real demand for the AI industry and the data center investment cycle through this week's earnings from major big techs such as Meta, Microsoft and Apple," adding, "The impact of last year's surge in memory prices on big tech profitability is also a key variable." She added, "Whether AI corporations' expansion of investment expenditure can actually connect to monetization will determine expectations for the industry's long-term growth going forward."