Concerns about a potential AI "death spiral" for heavily indebted data center firms have put the spotlight back on the hardware behind the hype: the chips, tools and foundries that actually power these models. That is where the real picks and shovels of this trend sit. This article walks through three stocks from our semiconductor supply chain screener that align with that practical, cash backed part of the AI story.
The stocks covered next are just a starter pack from this theme, and the full semiconductor supply chain screen surfaced 58 more hardware focused companies with equally compelling stories that are not covered below.
To really pressure test your own AI hardware thesis, head straight into the Semiconductor Supply Chain screener to identify, analyze, and focus on the ideas that best fit your conviction.
Applied Materials (AMAT)
Overview: Applied Materials supplies the specialized equipment and software that chipmakers and foundries use to build advanced AI focused semiconductors.
Operations: Applied Materials generates about US$22.4b from Semiconductor Systems and US$7.2b from Applied Global Services, with key markets including China, Taiwan, Korea and the United States.
Market Cap: US$298.1b
Applied Materials matters in this screener theme because its fabrication tools and process control systems feed directly into the build out of AI capable chips.
"The mix shift toward leading edge foundry logic, DRAM including high bandwidth memory, and advanced packaging is expected to account for most wafer fab equipment growth in 2026 and 2027, and Applied Materials is forecasting more than 70% growth in advanced packaging revenue and more than 50% growth in process diagnostics and control in 2026."
The real swing factor is how one quiet shift inside this product mix filters through to margins and the durability of AI driven demand.
To see how that mix shift could rewire profitability and cycle risk, read the full narrative for Applied Materials for the moving parts management cannot show in one quote.
Micron Technology (MU)
Overview: Micron Technology produces DRAM, high bandwidth memory, NAND SSDs and other memory chips that feed AI servers, data centers and many everyday devices.
Operations: Micron generates US$43.1b from Cloud Memory, US$37.6b from Core Data Center, US$36.6b from Mobile and Client, and US$15.9b from Automotive and Embedded segments.
Market Cap: US$969.1b
Micron Technology matters in this theme because its memory and storage lines are what keep AI accelerators supplied with the bandwidth and capacity they need.
"The central change is HBM. High bandwidth memory is stacked DRAM designed to feed AI accelerators with enough bandwidth to keep them busy."
The real question is how one shift in where that high end memory is sold ultimately filters through to pricing power and margins.
That pricing power debate is exactly what sits behind the full narrative for Micron Technology, which maps how HBM demand, capital cycles and AI server buildouts could be decoupling.
Lam Research (LRCX)
Overview: Lam Research supplies wafer fabrication tools that handle high precision etch and deposition steps for advanced logic and memory chips used in AI hardware.
Market Cap: US$287.5b
Lam Research plugs into the Semiconductor Supply Chain theme as the behind the scenes equipment provider that memory and foundry customers rely on to push AI chips to finer geometries and denser storage.
"NAND conversion pace. The June quarter's doubling is the first real evidence the upgrade cycle has started."
What really moves the needle from here is how one under appreciated shift in customer spending patterns feeds through to Lam Research’s margins.
That shift in spending is exactly what the full narrative for Lam Research unpacks, revealing how accelerating NAND conversions and AI tooling demand could reshape Lam Research’s risk reward profile.
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