Prediction: 2 Artificial Intelligence (AI) Chip Stocks That Will Soar After Feb. 25 (Hint: Not Nvidia)

Source Motley_fool

Key Points

  • Big tech plans to spend nearly $700 billion on artificial intelligence (AI) infrastructure this year.

  • When Nvidia reports Q4 earnings, smart investors will listen closely to where management sees hyperscaler budgets flowing.

  • In addition to GPUs, additional capital is beginning to rotate toward custom silicon, networking gear, and memory chips.

  • 10 stocks we like better than Micron Technology ›

As earnings season comes to a close, one member of the "Magnificent Seven" is yet to provide investors with its quarterly financial update. On Feb. 25, Nvidia (NASDAQ: NVDA) will report earnings for its fourth quarter and fiscal year 2026 (which ends Jan. 25).

For the last few years, it seems like Nvidia's earnings reports essentially make or break the artificial intelligence (AI) narrative. While I am bullish that Nvidia could once again blow out Wall Street's expectations and provide optimistic guidance, I'll be looking at two other AI chip stocks that stand to benefit from a positive report from Nvidia.

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Let's dig into two semiconductor stocks that could kick into a new gear following Nvidia's fourth-quarter update.

Beyond Nvidia: What are the best pick-and-shovel AI chip stocks for the AI infrastructure revolution?

Over the last several weeks, big tech reported earnings for the fourth quarter and provided financial outlooks for 2026. Chief among the talking points was how much the hyperscalers plan to spend on capital expenditures (capex) this year.

Among Microsoft, Amazon, Alphabet, Meta Platforms, Apple, and Tesla, a cumulative sum of $680 billion will be spent on AI infrastructure in 2026. Right off the bat, accelerating infrastructure investment should serve as a robust tailwind for Nvidia's GPU and data center operations.

However, Nvidia CEO Jensen Huang recently made a remark that has me thinking big tech's capex budget is starting to broaden beyond GPU clusters.

Last month, Huang sat down with BlackRock CEO Larry Fink at the World Economic Forum in Davos, Switzerland. During their discussion, Huang described AI as a "five-layer cake" -- spanning energy, cloud services, generative AI models, chips, and critical infrastructure.

Given these remarks, I see two specialty chip businesses poised for explosive growth alongside Nvidia as the AI infrastructure era begins.

1. Broadcom

Broadcom (NASDAQ: AVGO) sits at the intersection of chips and ancillary data center equipment.

When Nvidia sells its GPUs to hyperscalers, often these purchases are made in clusters measured in the hundreds of thousands. After these GPUs are fitted into servers and moved inside data centers, a new challenge emerges: Data workloads need to flow across these clusters free of lags.

Broadcom's Tomahawk and Jericho switching chips complement Nvidia's architecture so that developers can rest easy knowing data is moving seamlessly and without any latency hiccups.

Outside of networking gear, Broadcom is also the industry leader when it comes to custom application-specific integrated circuits (ASICs). While Nvidia remains the dominant player in the GPU space, its chips tend to be used for building general-purpose applications. Custom silicon, on the other hand, is leveraged for unique use cases across deep learning, robotics, or autonomous systems.

Alphabet and Meta are two of Broadcom's marquee custom silicon customers -- a move that signals big tech may be complementing their Nvidia stacks with in-house builds to potentially move toward vertical integration and lower costs over time.

2. Micron

Another company that stands to ride Nvidia's coattails is Micron Technology (NASDAQ: MU). Micron specializes in memory and storage hardware. Frankly, this particular pocket of the semiconductor realm has historically experienced quite a bit of shade.

For years, Micron's business was highly cyclical -- riding high during periods of consumer electronics upgrades, only to experience plateaus once these runs came to an end. Rising AI infrastructure investment is beginning to shift this narrative, though.

Micron Technology building with a sign out front.

Image source: Micron Technology.

As referenced, Nvidia sells GPU clusters in huge volumes to the hyperscalers. Subsequently, big tech then uses this architecture to develop all sorts of next-generation applications. In other words, generative AI is no longer a sole function of large language models (LLMs). Developers are ushering in a new wave of sophisticated services across self-driving cars, humanoid robots, wearable smart devices, and more.

Against this backdrop, AI workloads are scaling at an unprecedented rate. As these workloads become larger, the real bottleneck shifts downstream from capacity to memory. Micron's dynamic random access memory (DRAM) and NAND chips are becoming mission-critical throughout this period of accelerating AI infrastructure investment.

Consider that Micron's inventory of high-bandwidth memory (HMB) chips is already sold out for 2026; hence, Wall Street is calling for the company's earnings profile to quadruple this year. While that's great news right now, Micron's valuation profile suggests significant valuation could be in store over the next several years.

Right now, the company trades at a forward price-to-earnings ratio (P/E) of about 12. That's roughly half the forward P/E of the Nasdaq-100. So long as Nvidia and Broadcom continue to sell GPUs and custom ASICs, which very well appears to be the case, Micron's growth prospects should remain robust as the memory supercycle takes shape.

Should you buy stock in Micron Technology right now?

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Adam Spatacco has positions in Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia, and Tesla. The Motley Fool has positions in and recommends Alphabet, Amazon, Apple, Meta Platforms, Micron Technology, Microsoft, Nvidia, and Tesla. The Motley Fool recommends BlackRock and Broadcom. The Motley Fool has a disclosure policy.

Disclaimer: For information purposes only. Past performance is not indicative of future results.
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