Accelerating AI infrastructure spending by hyperscalers and governments is a good indicator that GPU demand will remain high.
On the surface, Nvidia appears to be the chip company that's best positioned to benefit from rising AI infrastructure spending.
The growing demand for AI training and inference also bodes well for high bandwidth memory specialists like Micron.
On Wednesday, semiconductor giant Nvidia (NASDAQ: NVDA) will release its second-quarter earnings report.
Between the advent of DeepSeek, shifting U.S. trade policies anchored by President Donald Trump's tariff agenda, and a fluid situation regarding its business in China, this has been the most challenging year of the artificial intelligence (AI) revolution yet for Nvidia. Despite the noise, however, recent developments suggest the AI chip behemoth remains firmly on track.
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While Wall Street's attention will be focused on Nvidia's results, savvy investors may want to look elsewhere in the semiconductor space for potentially seismic stock moves next week. In particular, Micron Technology (NASDAQ: MU) is positioned to benefit handsomely if Nvidia delivers upbeat results, given that its mission-critical solutions are also part of the AI supply chain.
Let's discuss why Micron stock could skyrocket after Nvidia's Q2 report, and assess whether now would be a good time to scoop up shares.
Over the past month, investors have gotten some previews of what to expect from Nvidia's upcoming earnings report. The hyperscalers -- Microsoft, Alphabet, Amazon, and Meta Platforms -- continue to make record-breaking capital expenditures to build out new data centers and cloud computing infrastructure.
AMZN Capital Expenditures (TTM) data by YCharts.
Much of this spending is directed toward infrastructure that can support AI -- including networking equipment, servers, and, most importantly, graphics processing units (GPUs), which remain Nvidia's core products.
Another bullish signal came from Taiwan Semiconductor Manufacturing. The world's largest third-party chip foundry recently reported a blowout quarter with $30 billion in revenue. Because TSMC is Nvidia's key foundry partner, Taiwan Semi's results can effectively be taken as a proxy for demand for Nvidia's GPUs.
When you combine robust AI spending from the hyperscalers with surging order flow at the top AI chip manufacturer, it points to one conclusion: Nvidia's Q2 earnings report is likely to deliver the kind of growth that will please even the most aggressive investors.
While much of Nvidia's sales growth is being driven by hyperscalers' insatiable demand for GPUs, those chips don't operate in isolation. High-performance memory chips are also essential to handle the massive data loads generated by AI models -- and this is where Micron plays a pivotal role.
In addition, large-scale initiatives such as Project Stargate highlight just how expansive those data center buildouts have become. From cloud services providers to sovereign government AI projects, data centers are being designed with next-generation GPUs, advanced networking, and high-performance memory and storage.
Another important trend is the broadening scope of AI investments. The first wave focused on acquiring GPUs with which to train large language models (LLMs). The next wave is about deploying AI software into enterprise workflows. This shift requires more than just additional training power -- it demands hardware with more robust inference capabilities.
Inference workloads are memory-intensive, as they involve the processing of enormous volumes of real-time data. Micron's DRAM and high bandwidth memory (HBM) solutions are both designed to support these protocols, positioning the company as a critical player in the downstream adoption of AI.
Taken together, the surging capex from hyperscalers, megaprojects like Stargate, and the rise of AI inference workloads converge to show that demand for computing power is still rising. While GPUs may be the headline act of the AI infrastructure show, HBM is a key player backstage, ensuring that the show goes on.
For this reason, Micron will continue to benefit from the world's massive AI infrastructure outlays -- quietly capturing incremental revenue each time money is spent on GPUs, servers, and data center upgrades. As Nvidia's sales scale up further, Micron is positioned to scale up right alongside it -- and its shares could easily witness some pronounced buying on the heels of a positive report from Nvidia next week.
Image source: Getty Images.
As the chart below illustrates, chip giants like Nvidia, Broadcom, TSM, and Advanced Micro Devices all trade at far richer valuations than Micron. That's because investors clearly see how surging demand for GPUs and networking equipment drives revenue and profits for these businesses.
MU PE Ratio (Forward) data by YCharts.
Where I think investors are missing the mark is in how they view Micron. It's true that the high bandwidth memory business is much different from the GPU business. GPUs function as the backbone of generative AI development, and each company's chips have unique value propositions. HBM is more commoditized.
That said, what investors may be overlooking is that each new dollar spent on AI GPUs designed by Nvidia and AMD and manufactured by TSMC multiplies the need for complementary solutions like high bandwidth memory to keep those accelerators running at maximum efficiency. Moreover, when you consider that Micron's HBM products are already integrated with Nvidia's flagship GPUs, it positions the company as a direct beneficiary of AI infrastructure spending.
Nevertheless, the valuation gap is striking. Micron's forward price-to-earnings (P/E) ratio sits well below those of its tangential peers, suggesting the market has yet to fully recognize the importance HBM will play in the next phase of AI growth. That's why I see Micron as an underappreciated opportunity when valued against the most obvious chip beneficiaries at the moment.
While the stock could exhibit some volatility in the short term, I don't recommend trying to "market time" your entry points. Instead, a more reliable strategy for investors to use is dollar-cost averaging -- gradually building a position in a stock by purchasing set dollar amounts at regular intervals.
Using this approach with Micron will allow investors to buy the stock at different prices while riding the long-term secular tailwinds of the AI infrastructure narrative.
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Adam Spatacco has positions in Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.