Recent turbulence in the US technology sector highlights the contrasting fortunes of different tech industries and companies. Over the past year, the performance of software and semiconductors, in particular, has diverged – and the divergence has become even more pronounced in 2026. For all the attention focused on the famous “hyper-scalers,” which provide computing infrastructure, this cohort has not performed particularly well, either.

To illustrate this point, we compare returns of three indices:

·      The broad tech sector (Nasdaq), dominated by the largest firms: Alphabet, Amazon, Meta, Microsoft, Nvidia

·      The software sub-sector (IGV)

·      The semiconductor sub-sector (SMH)

From the beginning of 2025 through February 6, 2026 returns have been as follows:

·      Nasdaq: +20.1%

·      IGV (software): -17.6%

·      SMH (chips): +66.4%

And year-to-date through February 6, 2026 returns have been as follows:

·      Nasdaq: -0.9%

·      IGV (software): -22.0%

·      SMH (chips): +11.5%

Given broadly increased spending on technology, why are these different segments of technology trading so differently?

First, expectations for capital expenditure at the large cloud-computing providers are notably higher compared to just one month ago. Projected capital spending for four of the companies investing the most into datacenters is now expected to be well above $600 billion for the full year 2026. Raised capital spending forecasts have increased expectations for semiconductor demand while calling into question the return on capital for large data center projects. The Wall Street Journal recently published a graphic that captured the growing scale of capital spending at the 4 major cloud-computing providers:

Second, a large portion of this massive capital expenditure supports growth in artificial intelligence workloads. Two recent releases out of the leading AI labs, Anthropic and OpenAI, have targeted automation of knowledge work. The capabilities are impressive and include the ability to build some applications without coding knowledge.

These tools from Anthropic (“Claude Cowork”) and Open AI (“Codex”), have led to multiple concerns for software companies:

1.      Existing software can now be replaced relatively easily

2.      AI-driven automations will decrease the need for human labor, lead to layoffs, and drive down the number of seat-based licenses companies need to purchase

3.      existing software will be “abstracted away” by AI tools, leading to reduced pricing power and revenue growth for incumbents.

While software appears at risk of being devoured by AI tools, shortages of chips required for data centers ensure strong pricing power and margins for chip-makers. These companies generally show extended order backlogs. Additional memory-chip capacity, for instance, won’t become available until late 2027.  

The expanding scope of AI data-center investment – and the speed at which the leading AI labs innovate and launch competitive offerings – weighs on the valuations of most software stocks. Yet the recent collapse in their share prices  attracts our interest, particularly as the above concerns have been well-flagged by now. In our view, the supposed dichotomy between software applications and AI-based tools is misleading. As the software industry learns to integrate AI, selective investment situations may prove rewarding, especially in light of historically low valuations.

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