Nvidia Stock Could Rise 10-Fold On New $10 Billion Growth Vector

Nvidia stock has soared to about $1,200 a share — up 287% since the chip designer’s boffo May 2023 earnings report kindled generative AI fever.

With the stock set to drop to about $120 per share Monday — when the company’s 10-for-1 split goes into effect — will its stock price ever return to $1,200?

Here are four reasons that could happen by 2026 — the first is new, and the last three are still valid since my May Forbes post:

• Governments are afraid of falling behind in the race to master generative AI. Their chip purchases have added to Nvidia’s revenue, according to the Wall Street Journal;
• Nvidia’s great performance and prospects;
• Nvidia’s successful growth investments; and
• CEO Jensen Huang’s leadership — which could also be Nvidia’s biggest investment risk should he leave the job without a more capable successor.

One other risk is business leaders’ bipolar attitude towards generative AI.

How so? CEOs host competing fears. They are afraid of being left behind the generative AI boom even as the potential for AI hallucinations could savage their company’s corporate reputations.

This tension could make it difficult for them to implement high payoff generative AI applications, according to my new book, Brain Rush: How to Invest and Compete in the Real World of Generative AI.

Without that, demand for Nvidia’s technology could be difficult to sustain.

Sovereign AI Added $10 Billion To Nvidia’s Revenue

Were Nvidia stock — in an optimistic scenario — to keep rising at the 287% annual rate it enjoyed between May 2023 and last Friday, the company’s post-split shares could top $1,200 sometime in 2026, according to my analysis.

Here is a new source of growth to fuel that rise: Governments in Asia, the Middle East, Europe and the Americas are buying GPUs en masse as they build domestic computing facilities for artificial intelligence, noted the Journal.

What is driving this spending? The desire by countries to develop sovereign AI by training large language models in their own language with citizens’ data. Underlying this imperative is “a quest for more strategic self-reliance amid rising tensions between the U.S. and China,” the Journal wrote.

Nvidia expects sovereign AI spending to account for $10 billion in 2024 revenue, the company said last month. If demand by countries to build their own generative AI capabilities continues to expand, such spending could help Nvidia to diversify its revenue sources.

Angelo Zino, an analyst at CFRA Research, said this revenue stream could help Nvidia continue to profit from the AI boom. “The question has been, how can they continue this momentum?” he told the Journal. “Sovereign AI is a new lever out there in terms of generating higher revenue.”

Three Nvidia Growth Drivers

In addition to sovereign AI demand for Nvidia chips, other drivers of Nvidia’s growth, about which I wrote in my May Forbes post, include:

• Expectations-beating first-quarter results and forecast. In the first quarter of the company’s fiscal year 2025, Nvidia beat expectations for 237% revenue growth by $1.78 billion and reported a higher-than-expected gross margin of 78.4%, noted Yahoo! Finance. The company also forecast 197% revenue growth for the current quarter — exceeding analysts’ expectations, the Journal wrote.
• Nvidia’s growth investments. Nvidia’s aggressive pace of new product introductions will drive future growth. Examples include Blackwell chips which Huang said would generate “alot of revenue” for Nvidia in 2024 along with the company’s fast-growing InfiniBand line, as I wrote in May. Nvidia’s 427% increase in revenue from cloud service providers — which accounted for $22.6 billion in revenue, noted the New York Times, could slow down in the future. Fortunately for Nvidia, demand from sovereign AI customers could help offset the inevitable maturation of GPU demand from cloud services providers.
• Huang’s world-class leadership talent. Huang is at the top of a very elite class of leaders who founded a company that went public and maintained control more than three years after the company’s IPO, I noted in May. His ability to introduce and sell industry-leading GPUs while surfing new waves of demand is exceptionally valuable. The company’s ability to sustain expectations-beating growth depends on him remaining CEO — and ultimately appointing a successor at least as talented as Huang.

Can Companies Find High Payoff Generative AI Applications?

Based on my interviews with dozens of business leaders, generative AI in companies is caught in a bipolar battle, Brain Rush noted.

Peer pressure forces CEOs to tell Wall Street how generative AI will transform their business. At the same time, CEOs are terrified the AI chatbots will hallucinate — thus damaging their company’s reputation.

This fear is based in reality. For instance, Google’s AI advised people to add glue to pizza. And Air Canada’s AI chatbot made up a refund policy for a customer — and a Canadian tribunal forced the airline to issue a real refund based on its AI-invented policy.

This bipolar battle has significant implications for business. Of 200 to 300 generative AI experiments companies are developing, they have rolled out only 10 to 15 internally, and released perhaps one or two to customers and other stakeholders, according to my June 3 interview with Liran Hason, CEO of Aporia, a Manhattan-based startup offering guardrails to protect companies from AI hallucinations.

Unless high payoff applications emerge from this process of generative AI experimentation, the wave of demand for Nvidia’s GPUs could taper off over the long run.

In the meantime, business and political leaders’ fear of falling behind in the generative AI race could drive high demand for Nvidia’s chips — and the company’s stock.