Eric Fry
Editor, Smart Money
DAILY ISSUE
No Memory, No AI – How to Play the Shortage
Hello, Reader.
Micron Technology Inc. (MU) and elephants seem to have as little in common as, well, a semiconductor manufacturer and a several-ton land mammal.
But they do share one common trait: celebrated memory.
Elephants, of course, store memory cerebrally. Micron, on the other hand, designs and produces computer memory and storage chips, including…
- DRAM (dynamic random access memory) – the fast, temporary memory that computers use to think and work in real time.
- NAND (short for “NOT AND”) – the nonvolatile storage technology that can retain data without a power source. It is a type of flash memory used for long-term storage.
Micron’s memory technology is used, among other places, in artificial intelligence, data centers, computing, autos, and mobile devices.
Today, the company is rallying as demand for its memory chips soars, driven in large part by shortages caused by heavy use of memory in Nvidia Corp. (NVDA) chips.
The company is up around 14% over the past five days, ahead of its second-quarter earnings report later today, and 48% so far in 2026. The rally has elevated Micron’s market cap to $525.4 billion, surpassing Oracle Corp. (ORCL), which is now worth $440.6 billion.
Micron CEO Sanjay Mehrotra told CNBC in January…
Memory is a key enabler of AI. It is a strategic asset today, not like just a component in the system. And so we need it. Just like your brain, you need more memory. You need faster memory.
And the memory-chip shortage shows no signs of easing, with the tech industry’s top players spending record sums to stay competitive in the AI race.
That means memory companies could be among the next wave of AI stock winners.
At the moment, Micron is one of the main beneficiaries of AI’s second wave. But I expect that a smaller set of asset-heavy companies will be the biggest winners.
Today, I’ll detail why memory is quietly becoming a critical AI chokepoint. Then, I’ll share how you can capitalize on the opportunity.
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AI Needs Memory
All memory chips and data storage are critical to the AI Revolution, but the demand for DRAM is skyrocketing specifically because modern AI workloads are extremely memory intensive.
And DRAM is the only type of memory that can keep up.
Large language models (LLMs) and other generative AI models have billions, or even trillions, of settings that the system needs to keep in memory. DRAM stores all these settings and the temporary calculations the model makes while running.
For example, training ChatGPT-sized models can require tens to hundreds of terabytes of DRAM across graphics processing units (GPUs).
In a world without enough DRAM, the AI Revolution hits a hard ceiling because it runs out of space to think.
No memory means no intelligence.
Nvidia CEO Jensen Huang first raised the alarm bells on DRAM earlier this year, saying the “memory bottleneck is severe.”
There have even been media reports that representatives from AI companies have moved into long-term stay hotels in South Korea, desperately “begging” for DRAM allocation from the other two suppliers: Samsung Electronics and SK Hynix.
These purchasing managers from Silicon Valley have actually been nicknamed “DRAM beggars.” And the big DRAM manufacturers in South Korea have had to police their customers’ purchases to prevent hoarding.
Moreover, this DRAM shortage has no end in sight.
Nearly 100 gigawatts (GW) of new data centers are scheduled to come online over the next four years. So, we can estimate that means about 50 GW over the next two years.
However, there’s only enough DRAM to support the build-out of about 15 GW of AI data centers over the next two years.
That’s a big supply problem.
In early February, market researcher TrendForce raised its chip price forecasts, projecting that conventional DRAM contract prices will surge 90–95% in the first quarter of 2026, compared to the fourth quarter of 2025.
This is one of the fastest pricing spikes the memory industry has ever seen.
The DRAM beggars will continue to bid the price up, making certain suppliers the potential beneficiaries of this high-stakes bottleneck.
This is a pricing power story, and that means it’s important to get in on the opportunity early.
Here’s how…
Own the Bottlenecks
Just a couple of hours ago, I held my FutureProof 2026 special event. And I want to thank all of you who joined me there.
My message was a simple one: AI demand continues to explode, but it is constrained by real-world physical bottlenecks in energy, raw minerals, and memory.
Micron’s spike on memory demand couldn’t be more pertinent.
So, here’s my actionable advice: You want to own the bottlenecks, not the hype.
Micron sits at the center of one of those bottlenecks. But that doesn’t automatically make it the best investment. The company is already widely followed, heavily owned, and priced as an AI beneficiary.
Instead, I believe the biggest winners in the memory bottleneck will be those with heavy assets – not the memory-chip makers themselves, but the suppliers of the infrastructure required to produce the chips – and the least competition.
At my FutureProof 2026, I shared five tickers – free of charge – that meet these criteria. I believe these are companies to watch in the memory space.
You can watch a replay of my broadcast here and get immediate access to those names.
I also detail two other major bottlenecks affecting the AI buildout: raw materials and energy. And I share five more companies for each corresponding bottleneck.
To watch my free event, simply click here.
Regards,
Eric Fry
Editor, Smart Money
RJ Hamster 