Jensen Huang has never been shy about making bold calls. But when he first stood on the Goldman Sachs Communacopia stage exactly one year ago and predicted the AI market would reach $3 trillion to $4 trillion by 2030, plenty of people raised an eyebrow.

Twelve months later, he’s back — and he’s not backing down. Not even a little bit.

The Prediction, Restated

Speaking at the same Goldman Sachs Communacopia & Tech conference on Thursday, the Nvidia CEO reiterated his expectation that the size of the AI market will hit $3 trillion to $4 trillion by 2030.

His reasoning? Two fundamental shifts in computing.

“The semiconductor industry is going to just keep getting larger and larger, which is what we’re seeing now [with] these two fundamental ideas, that we have a new layer of computing with a new application and the end of Moore’s law,” Huang said. “Meanwhile, people are expecting these AI models to be smarter and smarter because they don’t like wrong answers. Then the compounded result of that should result in a very large industry”.

In plain English: we’ve moved from a world where computers retrieve information to one where they generate it. That’s not an upgrade — that’s a completely new computing paradigm. And according to Huang, it’s only just getting started.

The Earnings Report That Proves His Point

If you want evidence that Huang isn’t just talking his own book, look at Nvidia’s latest quarterly results.

The company posted adjusted earnings per share of $2.22 on revenue of $96.2 billion — both comfortably ahead of Wall Street’s expectations of $2.09 per share and $92.3 billion in revenue. Revenue more than doubled year-over-year, up 106% from $46.7 billion a year earlier.

The Data Center segment — which includes hyperscalers, AI clouds, industrial, and enterprise — brought in $89 billion, beating projections of $85.8 billion. Edge Computing, which covers physical AI and gaming, contributed $7.2 billion, also above estimates.

But here’s the number that really turned heads: Nvidia said it expects 70% revenue growth for fiscal year 2028. Analysts were forecasting just 45%. That guidance, if met, would put Nvidia on a path to pass both Apple and Alphabet in annual revenue.

The Catch: They Can’t Make Them Fast Enough

There’s a problem with all this explosive growth, though. Nvidia isn’t supply-constrained by demand — it’s supply-constrained by reality.

The sales gain would actually be larger than 100% if not for memory chip shortages, according to Huang. In other words, Nvidia could be growing even faster, but it physically can’t produce the chips quickly enough to meet the insatiable appetite for AI compute.

You don’t have to take Huang’s word for it. Michael Intrator, CEO of AI cloud provider CoreWeave, put it bluntly at the same conference:

“We are struggling to meet demand every day. Every GPU we have could be sold to multiple different clients. It is a unique moment, and it continues to be”.

CoreWeave’s numbers tell the same story. The company raised its full-year 2026 revenue guidance to $12.4 billion to $13.2 billion, driven by a massive $104 billion total revenue backlog.

The CoreWeave Connection

The relationship between Nvidia and CoreWeave is worth understanding, because it illustrates just how deeply embedded Nvidia is in the AI ecosystem.

Nvidia supplies 100% of the advanced GPUs powering CoreWeave’s specialized AI data centers. But it’s not just a supplier — it’s also a major strategic shareholder, holding an 11.5% equity stake in the company.

That kind of vertical integration is exactly why Huang is so confident. Nvidia isn’t just selling shovels in the AI gold rush — it’s also invested in the mines.

The Bottom Line

When Jensen Huang makes a prediction, he tends to stick with it. And this time, the numbers are on his side.

A $96.2 billion quarter. A 70% growth forecast for fiscal 2028 that dwarfs analyst expectations. A $104 billion backlog at one of its biggest customers. A memory chip shortage that’s actually limiting growth rather than demand.

Huang sees a $3 trillion to $4 trillion AI market by 2030. Based on everything we’re seeing right now, that might be conservative.