Can Micron Technology Capitalize on the AI Boom Amid Market Volatility?

TradingKey - Micron Technology, Inc. (MU) specializes in storage and memory technology and is currently positioned as a key bottleneck for artificial intelligence (AI) development. 

That is because AI processing clusters use enormous quantities of ultra-fast dynamic random-access memory (DRAM) to support processing via graphics processing units (GPUs) and AI acceleration in close proximity to the processing units. 

Similarly, inference processing servers use large-capacity solid-state drives (SSDs) to store and deliver various training data sets that become available for training and learning by AI systems. 

As resource requirements continue to grow (processing power and memory, as well as all forms of data), memory has ceased being a cyclical afterthought and is now positioned as a strategic input within hyperscale AI architectures. 

High-bandwidth memory is now an essential part of maintaining hyperscale AI services and has given Micron leverage to raise prices across all varieties of DRAM and NAND memory. As a result of this changing landscape, Micron is positioned for substantial revenue and profit in the year ahead.

Over the past twelve months, Micron's stock has significantly outperformed other semiconductor stocks, including Nvidia（NVDA）, AMD（AMD）, Taiwan Semi（TSM）, and Broadcom（AVGO）, increasing by 452%. Micron's stock continues to rise as we move into 2026, due to investors believing that AI will put meaningful upward pressure on semiconductor supply and prices in the years ahead.

The Google TurboQuant That Spooked Micron Stock

As excitement was peaking, Google（GOOGL）（GOOG）, a division of Alphabet, released a new set of quantization algorithms on March 24, which will allow for the dramatic reduction in size of large neural networks and vector search engines. 

The research provides a digital "cheat-sheet" that can reduce memory usage by about 6x, speed up processing time by 8x with zero loss of accuracy. If this technology works as well in actual production environments as it has in laboratory environments, we could see approximately 83% reduction in memory usage going forward. 

The news hit a nerve with many companies in the memory market; according to S&P Global Market Intelligence, Micron's stock lost as much as 18.1% of its value during the month of March as investors reassessed their short-term outlooks for demand.

The reduction of the amount of available model memory that needs to be saved and moved should put the most direct pressure on Micron's NAND‐based storage (which represented roughly 21% of Micron's total revenues). 

This also forms the argument for the bear case for DRAM, as more efficient models reduce the total amount of memory that is required for each accelerator. 

However, the basis for this is that efficient software typically leads to more widespread usage, which is the essence of the Jevons Paradox, since falling costs and rising performance usually create increased consumption. In other words, reduced memory per node could result in more total nodes, larger total deployments, or new workloads that lead to an increase in total demand even if memory per server is less than before.

Is the AI Memory Supercycle Sustainable for Micron?

AI demands memory consumption to grow significantly larger than any type of memory has experienced historically. As AI models and their datasets continue to grow in size, the need to train and operate those models requires exponentially more memory resources than traditional memory experiences. 

In addition, because a large number of AI models are constantly being trained and older models still require availability for inference, it creates a more stable environment for AI memory than traditional memory cycles. 

Given the level of investment by large technology companies into AI infrastructure, Micron has been able to increase pricing and improve margins in advance of reaching a stable demand-and-supply equilibrium for the industry.

2025 Performance Recap for Micron Stock

The trend of buying Micron stock in 2025 reflected the company’s strong performance due to many years of investment in AI by users and a limited number of chips available. 

A report in March showed revenue, gross margin and EPS exceeded analyst estimates and further validated investment in this asset; however, news of the compression at Google has raised ambiguities surrounding how much demand we will see in the near term.

Going forward, we expect that the levels of volatility will increase vs the last uptick in price as a result of the market having to balance strong fundamentals versus the uncertainty associated with whether software could replace part of the hardware scale. 

However, it usually takes a significant amount of time for new cutting edge algorithms to move from research to production, especially given the unevenness of the adoption curve for various AI workloads, thus there is still a good chance that the supply of Micron’s DRAM and HBM will continue to be tight while users are determining what “efficient AI” will look like in production.

Micron’s Financial Performance in Context

The record revenue growth of 196% on a year-over-year basis, along with the record EPS growth of 682%, and the increase in gross margin to 74.4%, paint a clear picture of the combination of scarcity due to COVID-19 and a tsunami of demand from the resumption of microprocessor/semiconductor demand, as well as the expansion of the cloud, which continues to expand. 

Micron surpassed Wall Street's estimated revenues ($20B) and earnings per share ($9.31), thus providing strong evidence that it will continue benefiting from both improved product mix and increased pricing power.

Although these results may be adversely affected through continued pricing discipline and increased capital expenditures in AI growth, they also illustrate execution by Micron across product categories, which is why Mehrotra grouped the terms "demand," "supply constraints," and "execution" together when talking about the results.

Pricing remains stable and as High Bandwidth Memory builds production volume over the coming quarters, Micron's margin is expected to remain equal to/above current levels even with slowing unit volume growth.

Should you buy Micron stock now?

Micron is still critically important for AI infrastructure, and its most recent quarter reinforces that importance due to continued significant growth and profitability. Due to the compression headline being a substantial factor influencing near-term sentiment, it is likely that the company will experience large amounts of volatility as the market determines whether software efficiencies will lead to reduced total memory needs in the absolute sense or expanded deployments resulting in increased aggregate memory consumption. 

For those investors considering Micron, they should be ready for the potential for volatility as the collective market determines whether software efficiencies result in less total memory use or more memory consumption from larger deployable quantities. 

There has not been enough time to determine which will occur, and knee-jerk reactions run the risk of missing what has been a long time coming with respect to the arc of AI adoption that has driven Micron’s fundamentals.