High-Bandwidth Memory Stocks: The Limiting Factor to the AI Boom?

Artificial intelligence ("AI") isn't "born" smart. Its "intelligence" relies on what it's taught and the quality of that "education."

The volume of data necessary to teach AI models is massive. For instance, GPT-3 – an earlier version of OpenAI's ChatGPT – is estimated to have trained on 45 terabytes of data. That's more than four times all the information contained in the U.S. Library of Congress.

But, just like a human, an AI model also needs to "remember" what it has learned. And the amount of memory that AI systems currently employ to process this data is insufficient. This is causing a major bottleneck – slower speeds and less efficiency – in AI model training and deployment. And that must be addressed quickly to keep up with demand from users during this AI boom.

Fortunately, a few tech companies have the products to address this. And two pureplay memory companies that should be on your radar are Micron Technology (MU) and SK hynix (A000660 KOSE). Both are known for fast, high-bandwidth memory ("HBM") chips to ease the bottleneck and allow AI to perform tasks at much faster rates.

But this technology doesn't just maintain the momentum of the AI boom. HBM is completely revolutionizing AI performance. Let's examine how.

The AI Memory Wall and Why Chips Alone Can't Keep Up

The widening gap between processor speed and memory bandwidth – and the reason for the bottleneck – is called the AI memory wall. This occurs when processors wait too long for data from memory, resulting in a significant lag in AI performance. It's a bit like if you, a human, struggle to remember an important detail. You have to pause and think before continuing with whatever task you're on.

This bottleneck is caused by one thing. Processor performance has improved exponentially. But memory performance and speed haven't kept up. Even when using the most powerful processors, AI applications still lose efficiency because the memory isn't feeding them the data they need to perform optimally.

Currently, AI models are simply too complex and large for the dynamic random-access memory ("DRAM") available to them. So, new solutions are imperative. One solution is faster memory, which Micron and SK hynix are busy manufacturing.

The key to HBM is its physical design. Traditionally, memory chips are placed next to one another on a flat chip board. HBM uses a 3D stacking structure. Multiple DRAM chips are stacked upon each other using advanced packaging techniques. This unique structure enables HBM to operate with much faster data transfer rates than typical memory solutions like graphics double data rate.

We've reached a point where standard memory alone, no matter how advanced or powerful, is not enough to keep up with the memory demands of AI. That's where HBM comes into play.

What Is High-Bandwidth Memory and Why It Matters for AI

Its name is fairly self-explanatory... high-bandwidth memory is, according to microchipusa.com, a "next-generation memory architecture that enables faster data transfer, improved energy efficiency, and compact integration – key to supporting everything from large language models to advanced graphics rendering."

HBM offers several critical advantages when it comes to helping support data-intensive AI systems, including:

• Very high bandwidth (as its name suggests) for fast transfer of tons of data.

• Lower latency than standard memory, which reduces signal travel distance and accelerates processing.

• Less power consumption, which results in better performance and reduced operating costs.

• A smaller footprint, which frees up space on a circuit and chip boards to add more processing power.

Together, these HBM features prevent data bottlenecks. And they allow AI models to do their work more quickly and efficiently while improving performance. In other words, HBM changes how memory interacts with processors.

And that's what makes HBM one of the vital components for the state of AI. High-bandwidth memory will provide the power that propels AI deep learning, supercomputing, next-gen graphics processing units ("GPUs") and gaming consoles, and autonomous vehicles.

High-Bandwidth Memory Companies Powering AI's Next Leap

There are three companies that specialize – and dominate – in developing and producing HBM. Those would be Micron, SK hynix, and Samsung. However, Samsung's memory business is just one piece of its massive consumer electronics empire. Micron and SK hynix, on the other hand, are pureplay memory companies. So, we'll focus there.

Micron Technology (MU)

Micron, America's primary memory maker, is causing a stir in the HBM world. The company was already mass producing its HBM3E semiconductors for use in Nvidia's (NVDA) H200 AI chip. And now its HBM4 samples, which surpass industry standards, are breaking performance records. Micron is also teaming up with Taiwan Semiconductor Manufacturing (TSM) to create next-generation memory that should take AI accelerator performance to another level.

Micron's focus on HBM is paying off. CEO Sanjay Mehrotra announced that Micron's expected HBM revenue will exceed $8 billion for 2025 thanks to increased market share and high product margins. For a bit of context, Micron's revenue for fiscal year 2025 was $37.38 billion. So, this is a sizeable chunk of business for the company.

SK hynix

SK hynix is another thriving HBM company. The South Korea-based HBM pioneer is the current global leader in high-bandwidth memory technology by market share (64%). This year, it finished development on its high-performance HBM4 chip and is preparing it for mass production.

The company also expects to create custom HBM4E products for Advanced Micro Devices (AMD), Nvidia (NVDA), and Broadcom (AVGO), tailoring the chips' architectures for the specific AI workloads of each client.

SK hynix, which trades on the Korea Stock Exchange, posted some very impressive quarterly financials in September 2025. As a Korean company, its results are reported in won (₩). Its ₩24.45 trillion revenue increased over 39% year over year ("YOY"), net income grew by more than 119% YOY to ₩12.6 trillion, and its net profit margin soared by 57.54% to 51.53% YOY.

Power, Energy, and the Economics of Memory Bandwidth: Why High-Bandwidth Memory Stocks Are in Demand

The AI boom is not slowing anytime soon. Projections show that more than 8,300 AI data centers will be up and running globally by 2030... up from around 6,100 today.

As more AI data centers pop up around the world, and as new AI innovations roll out, HBMs will remain in high demand. And not just because of HBM's ability to ease the AI memory bottleneck. They also reduce energy consumption.

This is critically important because AI data centers generate massive amounts of power. A typical hyperscaler center requires around 100 megawatts of power. That figure is expected to soar to around 1 gigawatt ("GW") or more. And 1 GW of power is enough to satisfy the peak power demand of a city the size of San Francisco.

It's a lot, and it's going to keep growing.

By 2035, the power demand from AI data centers in the U.S. alone could grow more than 30 times to 123 GW. That's enough to provide electricity to around 92 million average homes in America.

Right now, power grids simply can't handle that kind of energy demand. HBM, however, can help ease the strain.

HBM chips can reduce energy consumption by up to 70% for certain AI workloads, compared to standard memory systems. That's the type of efficiency AI data centers need as they search for energy savings. And it's one reason why HBM chips are such high-demand components.

As we covered, only three companies are primarily responsible for the development and manufacturing of most of the world's HBM chips: SK hynix has 64% market share, followed by Micron at 21% and Samsung at 15%. So, this is a mostly consolidated market.

And the companies making the GPUs and AI processors and accelerators – like Nvidia and AMD – need a steady stream of HBM chips to build their in-demand, next-generation AI chips.

HBM chips are so in demand that Micron, SK hynix, and Samsung's HBM capacity sold out through the rest of 2025 and into 2026. That sort of demand means one thing – pricing power. Those simple supply-and-demand economics make HBM manufacturers a very intriguing play for investors.

Bottom Line: Why Investors Should Watch HBM Stocks

As we mentioned, the demand is high for high-bandwidth memory chips. And so, HBM stocks have climbed higher this year. Micron has soared approximately 200% so far this year. MU hit a new high of $253.30 just this month.

But what about Micron's prospects moving forward? For that, we turn to our proprietary Stansberry Score, which awards Micron a solid B.

Micron gets outstanding marks for financials and a respectable C grade for capital efficiency. Micron gets dinged on valuation, though. And looking at the stock, we have to agree. Micron reported fiscal year 2025 earnings per share of $8.29. With shares in the ballpark of $230, it implies a price-to-current-earnings multiple around 27. But remember, markets are always forward looking. And Micron is expected to do very well going into 2026. But make no mistake, you're paying up for that growth at current levels.

SK hynix follows the same pattern. Its stock reached a 26-year high in November 2025, thanks to its HBM market share domination. Since January of this year alone, SK hynix stock gained 96%.

Analysts are noticing. Goldman Sachs upgraded its rating for SK hynix to "Buy" with a doubled price target in late October 2025. And SK hynix's CEO believes the HBM market will grow by an annualized rate through 2030. If that's accurate, the company figures to wildly outperform market returns.

For American investors, buying shares of SK hynix will likely require an extra step. The stock does not trade on American exchanges like the New York Stock Exchange or Nasdaq Composite Index. You'd have to go over the counter (OTC) or have a brokerage with access to the Korean Exchange.

Though Samsung currently trails Micron and SK hynix in HBM market share, the company is still a major player. The global electronics giant is zeroing in on mass production of its next-gen HBM4 chips. Samsung expects the shipment of these chips to close the gap with its HBM competitors. But remember, as a massive consumer electronics company, Samsung is not a pureplay memory company like Micron or SK. Samsung also trades on the Korea Stock Exchange, so the same extra steps would be required for any American investors looking for exposure.

The AI boom has seen many winners. HBM stocks are already clear victors. And, as Micron and SK hynix continue expanding their chip production and grow their partnerships with semiconductor titans like Nvidia and AMD, as well as cloud-services providers, the future looks even brighter.

Regards,

David Engle