AI Data Centers Will Consume 70% of All Memory Chips in 2026. Here Are the Only 2 Stocks That Matter.
Seventy percent. That’s the share of global memory chip production that artificial intelligence (AI) data centers are expected to absorb in 2026. Set aside what that means for the companies supplying it for a moment and consider what it means for everything else in the tech realm. Smartphones, laptops, cars, medical devices, and televisions are all competing for the remaining 30% of a supply base that used to be far closer to balanced with demand. Market research firm IDC is forecasting that smartphone unit sales will fall by as much as 5% and that PC unit sales will shrink by up to 9%, specifically because of this reallocation. This is a transfer of component manufacturing capacity that is reshaping an entire industry in real time.
Three companies manufacture most of the world’s high-bandwidth memory. One of them, South Korean giant Samsung, is not traded on U.S. exchanges. For most domestic investors seeking direct exposure to the most constrained slice of the technology supply chain, that leaves two stocks: Idaho-based Micron Technology (MU +14.50%) and South Korea’s SK Hynix (KOSE: A000660), which is preparing to list in the U.S. via a secondary offering on the Nasdaq next month.
Today’s Change
(14.50%) $152.00
Current Price
$1200.51
Key Data Points
Market Cap
$1.4T
Day’s Range
$1136.43 – $1254.64
52wk Range
$103.38 – $1255.00
Volume
44.4K
Avg Vol
51.6M
Gross Margin
72.60%
Dividend Yield
0.04%
High-bandwidth memory, or HBM, is not standard random access memory. It stacks dynamic random access memory (DRAM) dies vertically and connects them via microscopic silicon channels called through-silicon vias, delivering data bandwidth that flat memory architectures cannot physically match. Every Nvidia Blackwell graphics processing unit requires HBM. Every hyperscaler building the next generation of AI training infrastructure requires it — and building 1 gigabyte of HBM consumes 4 times the wafer capacity of standard DRAM. When memory manufacturers shift capacity toward HBM, they disproportionately tighten supply for every other memory product on the market.
That dynamic is already visible in pricing. In Micron’s fiscal second quarter alone, average DRAM selling prices rose by a percentage in the mid-60s sequentially. NAND prices jumped by 70% in the same period. Memory, historically the most volatile commodity in the semiconductor sector, has transformed into a contracted infrastructure product — Micron signed its first five-year customer supply agreement in early 2026. Contracts with terms that long have almost no precedent in this industry.
Image source: Getty Images.
Micron Technology
Micron Technology’s entire 2026 HBM4 production capacity is already sold out under binding multiyear contracts.
Speaking at COMPUTEX 2026, a major information technology trade show in Taipei, Micron Chief Business Officer Sumit Sadana explained the demand math: AI context lengths are growing by a factor of 30 every year, and memory content per server has doubled in the past three years. Those two numbers increase in tandem. Larger models need more context. Longer context requires more memory per inference, and that requires more HBM per server rack. And rising inference workloads demand more of those servers.
Micron is shipping HBM4 chips that can move data at bandwidths greater than 2.8 terabytes per second — roughly 2.3 times the bandwidth of its previous generation HBM3E chips — with 20% better power efficiency. Those are the specs that determine which chips get designed into the next generation of AI systems.
Micron is also in the midst of a $200 billion expansion of its U.S. manufacturing capacity, a number that signals where it believes demand is headed through the end of the decade.
With sales of much of its memory supply locked in under multiyear contracts, AI data center demand still growing, and HBM supply structurally constrained, Micron stock looks less like the cyclical semiconductor bet that it used to be, and more like a long-term AI infrastructure asset. That makes it a compelling candidate for investors to steadily dollar-cost average into over time.
SK Hynix
SK Hynix holds an estimated 60% to 70% of HBM4 volume allocated to Nvidia’s Vera Rubin platform. On June 6, Nvidia and SK Hynix formalized a multiyear co-development agreement covering not just the supply but also the actual design of next-generation AI memory. That’s a distinction worth understanding: SK Hynix is not simply a vendor filling purchase orders. It is collaborating with the designer of the world’s most advanced AI systems to engineer the memory architecture that those processors will run on for the next several years.
SK Hynix’s leading share of the HBM market — which estimates place between 57% and 62% — reflects the technological lead it has held since the debut of HBM3E chips, and that it is now extending with the current top-of-the-line HBM4 standard. Bank of America named SK Hynix as its global memory “top pick” and estimated that in 2026, the HBM market would grow by 58% to $54.6 billion. The bank also described the current environment as a “supercycle similar to the 1990s semiconductor boom.” SK Hynix also projects that the HBM market will grow at a 30% annualized rate through 2030.
SK Hynix trades on the Korea Stock Exchange, but it’s about to become more accessible to U.S. investors. Its upcoming offering of American depositary receipts (ADRs) on the Nasdaq appears to make the stock a compelling candidate for a dollar-cost averaging strategy, given the company’s leadership in HBM memory, its deepening partnership with Nvidia, and the central role it’s playing in the AI semiconductor supercycle.
