Nvidia Forecasts 70% Revenue Growth as AI Demand Continues to Surge

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Nvidia just gave investors a number that was almost impossible to ignore: 70%.

The chipmaker expects revenue to grow by about 70% in fiscal 2028, far above the roughly 44% growth analysts had been expecting, according to LSEG estimates.

The forecast came after Nvidia had already delivered quarterly results that exceeded Wall Street expectations, reinforcing just how rapidly demand for its artificial-intelligence processors continues to expand.

$673 Billion Revenue Target

Wall Street currently expects Nvidia to generate about $396 billion in fiscal 2027 revenue, with the year ending in January.

If the company’s 70% growth forecast materialises, that would put fiscal 2028 revenue at roughly $673 billion.

At that level, Nvidia would surpass projected annual revenue for companies such as Apple and Alphabet and rank behind only Amazon among major U.S. technology companies.

That would be an extraordinary transformation for a company that was once best known primarily for graphics chips.

From Niche Chipmaker to AI Powerhouse

Nvidia’s rise has been closely tied to the explosion in generative AI.

Its GPUs have become critical infrastructure for companies building and training advanced AI models, turning the chipmaker into one of the most valuable companies in the world.

The growth has been staggering.

Nvidia’s revenue doubled year over year in its latest quarter.

And Jensen Huang believes demand could be considerably stronger than the company’s new forecast suggests.

Demand Is Bigger Than Nvidia Can Supply

Nvidia CEO Jensen Huang told investors that actual demand is running well above the 70% growth level the company expects to deliver.

The limiting factor is supply.

The AI infrastructure boom has created shortages across the technology supply chain, including memory and other components required to build increasingly powerful computing systems.

Huang said Nvidia’s current supply position gives the company confidence in its 70% projection, while emphasising that it is working with suppliers to increase output.

That distinction is crucial.

Nvidia isn’t saying customers suddenly need less. It’s saying the company can only forecast what its supply chain can realistically deliver.

Why Nvidia Is Forecasting So Far Ahead

The company has rarely provided investors with such a detailed outlook this far into the future.

Huang explained that Nvidia now has unusually strong visibility into the amount of computing capacity customers are likely to require next year.

That visibility also matters beyond Nvidia itself.

The company’s rapid expansion is influencing decisions about data-centre sites, electricity generation, construction and other infrastructure.

By providing a longer-range forecast, Huang said Nvidia can give its partners more confidence as they commit capital to the enormous infrastructure needed to support AI computing.

The Hyperscaler Question

There is still a major concern hanging over Nvidia’s extraordinary growth.

Much of the company’s AI business is ultimately connected to a relatively small group of enormous technology companies.

These hyperscalers are spending hundreds of billions of dollars building data centres, with much of that infrastructure supporting a handful of leading AI developers.

That concentration has prompted investors to question how sustainable Nvidia’s growth would be if hyperscaler spending eventually slows.

For now, however, Nvidia’s latest forecast suggests the company sees no immediate sign of that happening.

The Bigger Bet on AI

The numbers point to something much larger than a semiconductor boom.

Nvidia is effectively betting that the world will continue pouring capital into AI infrastructure at an extraordinary rate—and that its processors will remain central to that buildout.

The company’s biggest challenge may not be finding customers.

It may be producing enough chips to satisfy them.

And if Huang is right that demand is already well above the company’s 70% supply-constrained forecast, Nvidia’s next challenge could be figuring out how much bigger the AI boom can become.

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