Editor’s Note: The biggest gains in any tech cycle don’t come from what everyone already understands.
They come from spotting the next constraint before it shows up in the data… before it hits earnings calls, before it becomes consensus.
That’s exactly what we’re starting to see right now coming out of Nvidia’s GTC conference.
In today’s issue, I’ve invited Eric Fry to break down a subtle but important shift inside the AI stack… one that could define where capital flows in the next phase of this boom.
It’s the same pattern we’ve seen play out again and again: AI runs into a bottleneck… and the companies solving that constraint become the next big winners.
Eric has built a career around identifying these inflection points early. And right now, he believes a new set of constraints is forming… ones most investors aren’t paying attention to yet.
He walks through the full thesis, and the specific opportunities tied to it, in his FutureProof 2026 presentation, now streaming.
You can watch it here.
Now, take it away, Eric…
Where will the next big gains in AI stocks come from?
That’s the question every investor is trying to answer right now. And some of the most important clues for anyone tracking artificial intelligence stocks are emerging this week — not on Wall Street, but in Silicon Valley.
At Nvidia’s GTC 2026 conference.
Every year, thousands of engineers, developers, and executives gather to hear Nvidia Corp. (NVDA) CEO Jensen Huang outline what’s coming next. But GTC has evolved into something much bigger.
It’s where the AI industry telegraphs its next move — and where investors hunting for the best AI stocks often get their earliest signals.
This year, one message is coming through loud and clear.
While NVDA stock built its dominance on GPUs, Nvidia is now turning its attention to something far less glamorous… but potentially far more important to the future of AI infrastructure.
The central processing unit — or CPU.
It may not sound exciting. But this shift could define the next wave of leadership in artificial intelligence stocks to watch.
The Chip That Built the AI Boom
For the past several years, GPUs have been the backbone of the AI boom — and the driving force behind the surge in AI stocks.
These chips excel at parallel processing, making them ideal for training and running large AI models.
That advantage created one of the biggest supply squeezes in semiconductor history.
Tech giants raced to secure GPUs. Data centers expanded at breakneck speed. And NVDA stock became the single biggest winner in the artificial intelligence trade.
In its most recent quarter, Nvidia generated more than $60 billion in data-center revenue — up roughly 75% year over year.
Its market cap surged past $4 trillion, cementing its place at the center of the AI economy.
But the next phase of AI — and the next leadership group in AI stocks — may require something different.
The Rise of Agentic AI
Until recently, most AI applications behaved like chatbots.
You ask a question. The system responds.
But the next evolution — agentic AI — is already here.
These systems don’t just answer prompts. They coordinate tasks, retrieve data, make decisions, and collaborate across networks of AI agents.
In other words, they don’t just respond.
They act.
And that shift is reshaping the demands placed on AI infrastructure.
GPUs still handle the heavy lifting of model training and inference.
But in an agentic AI world — where multiple systems are communicating, coordinating, and moving data in real time — something else becomes critical.
General-purpose compute.
That’s where CPUs come in.
GPUs run the models.
But CPUs increasingly run the system that manages the models.
And that distinction could matter a lot for investors looking beyond today’s winners in AI stocks.
Nvidia’s Quiet Pivot
Nvidia clearly sees this shift coming.
Years ago, it introduced its Grace CPU platform. Now, its next-generation system — Vera — is moving toward broader deployment.
The company recently signed a multiyear deal with Meta Platforms (META) to deploy Grace CPUs at scale inside its data centers.
And Nvidia-powered CPU systems are already running at major research institutions.
Why does this matter for AI stocks?
Because the explosive growth in GPUs has exposed a new bottleneck.
CPUs.
In today’s AI data centers, racks are filled with incredibly expensive GPUs.
But if the CPUs feeding those GPUs can’t keep up…
Those GPUs sit idle.
And idle GPUs are unacceptable in a world where demand for AI infrastructure is still accelerating.
A Quiet Supply Crunch
We’re already seeing early signs of strain.
Server CPU delivery times are stretching toward six months. Prices are rising. And chipmakers are warning about tightening supply.
AMD has described demand as “unprecedented.”
Intel has warned inventories could fall to unusually low levels.
The problem is straightforward.
Semiconductor capacity takes years to expand.
And as demand for AI infrastructure surges — driven by both traditional models and agentic AI systems — supply is struggling to keep up.
Some analysts now expect the global CPU market to more than double by 2030.
That’s a major shift — and one that could reshape the landscape of artificial intelligence stocks to watch.
The Next Opportunity in AI Stocks
Right now, most investors are still focused on the obvious winners.
Names like NVDA stock dominate the headlines — and for good reason.
But the biggest gains in AI stocks rarely come from what’s already obvious.
They come from bottlenecks.
Because when a system hits a constraint, capital flows toward the companies solving it.
We’ve seen this before.
In the early internet era, the biggest gains didn’t just come from software companies. They came from the firms supplying the raw materials behind the buildout.
Companies like Freeport-McMoRan (FCX), Cameco (CCJ), and others delivered massive returns as supply struggled to keep up with demand.
Today, the same dynamic is emerging in AI.
Because artificial intelligence doesn’t just require software.
It requires infrastructure:
- Chips
- Energy
- Memory
- Data centers
And across this entire stack, new constraints are forming.
That’s why the next wave of winners in artificial intelligence stocks may look very different from the first.
Preparing for the Next Phase
When bottlenecks emerge, money moves.
Often quickly.
And the investors who recognize those shifts early are the ones who tend to outperform.
That’s exactly what I break down in my new presentation, FutureProof 2026.
Inside, I explain why multiple constraints are forming across the AI economy — and highlight several AI stocks positioned to benefit as the next phase of AI infrastructure investment unfolds.
If you’re looking for the next generation of best AI stocks, this is where to start.
You can watch it here now.
