Prediction: Nvidia Stock Will Go Stratospheric Driven by an Ultra-Competitive Race to Achieve Artificial Superintelligence

Key Points

• After generative AI -- the type of AI that's now being rapidly adopted -- the next big AI technological leap will be to artificial general intelligence (AGI) and then perhaps to artificial superintelligence (ASI).

• AGI will be achieved by 2030, according to AI entrepreneurs, though AI researchers predict it will be achieved by 2045.

• Nvidia's tech is a must for companies in the race to achieve AGI and ASI.

• 10 stocks we like better than Nvidia ›

Don't fret if you've been eyeing Nvidia (NASDAQ: NVDA) stock and thinking you've missed your opportunity to invest in the artificial intelligence (AI) technology juggernaut. Nvidia stock still has not just great -- but fantastic -- long-term growth potential left.

Nvidia's main growth driver for a while will be the continued strong demand for its graphics processing units (GPUs) and related tech to enable generative AI. (Generative AI is the type of AI that caused a sensation in the tech world when OpenAI released its ChatGPT chatbot in late 2022.) Some specific applications of generative AI that will fuel this growth include customer service operations, driverless vehicles, and the early stages of developing useful humanoid robots.

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But Nvidia's primary growth driver over the long term will be something that gets little coverage: the race to achieve artificial general intelligence (AGI) and then artificial superintelligence (ASI).

Image source: Getty Images.

What are artificial general intelligence and artificial superintelligence?

You can think of there being a continuum from generative AI -- the type of AI that's now being rapidly adopted -- to artificial general intelligence (AGI) to artificial superintelligence (ASI).

Generative AI has amazing capabilities and represents a huge technological leap. It excels at pattern recognition and other forms of concrete thinking. But it can't match human-level critical thinking and true creativity. That isn't surprising since generative AI is trained on data that already exists in this world. Moreover, even the best generative AI models are prone to "AI hallucinations," which are incorrect or misleading results presented with confidence.

Going from generative AI to AGI will be the next huge technological leap. AGI is a type of artificial intelligence that would at least match average human capabilities across virtually all cognitive tasks.

The meaning of artificial superintelligence is easy to grasp from its name. This tech will be super-intelligent, or significantly brainier than even the smartest humans across nearly every cognitive task.

When do experts believe AGI will be reached?

AI researchers generally believe achieving AGI is inevitable. Research firm AI Multiple's recently released macroanalysis found that the average AI researcher prediction for when AGI will be achieved is 2040, or in 15 years.

Prior to the rollout of AI models powered by generative AI (which started in late 2022), the average prediction was 2060. This data illustrates how much the advent of generative AI advanced the capabilities of AI.

Entrepreneurs are even more optimistic, according to the analysis. On average, they predict AGI will be achieved in 2030, or in just five years.

Achieving artificial superintelligence is further in the future, so predictions provide limited value.

Nvidia's tech is a must in the race to achieve AGI and ASI

Currently, Nvidia's dominance in the global AI semiconductor -- or "chip" -- market points to its GPUs and associated technology being must-haves for companies aiming to achieve AGI and ASI. These companies likely include all the big tech leaders (Alphabet, Amazon, Apple, Meta Platforms, and Microsoft), Tesla and other large tech companies, OpenAI, and many other AI native start-ups.

Let's address a topic that Nvidia stock bears like to point out: All the big tech companies and Tesla have developed or are developing their own AI chips. These are for internal use and, in some cases, for use in their cloud computing services, which also offer Nvidia's GPUs. But as suggested by the category name of these chips -- application-specific integrated circuits (ASICs) -- they are only ideal for specific applications.

GPUs -- and Nvidia's GPUs, in particular -- remain the gold standard for the overall training of AI models and deployment of AI applications. And there is no indication that Nvidia's dominance of this humongous and rapidly growing market will end anytime soon.

Nvidia's planned OpenAI investment should accelerate the race to achieve artificial superintelligence, which will benefit Nvidia

On Monday, Nvidia announced that it's investing up to $100 billion ($100 billion!) in OpenAI. The gist of this announcement:

OpenAI and Nvidia ... [plan] to deploy at least 10 gigawatts of Nvidia systems for OpenAI's next-generation AI infrastructure to train and run its next generation of models on the path to deploying superintelligence. [Emphasis mine.]

To support this deployment including data center and power capacity, Nvidia intends to invest up to $100 billion in OpenAI as the new Nvidia systems are deployed. The first phase is targeted to come online in the second half of 2026 using the Nvidia Vera Rubin platform.

Putting $100 billion in context, it's nearly twice as much cash and equivalents as Nvidia had on its balance sheet at the end of its most recently reported quarter. It's also more cash and equivalents than each of the other "Magnificent Seven" companies (Alphabet, Amazon, Apple, Meta Platforms, Microsoft, and Tesla) had on its books. (This doesn't mean Nvidia will be using up all its cash. The OpenAI investment will be over multiple years. Moreover, Nvidia generates powerful cash flows. Over the last year, its cash flow from operations was $77 billion.)

Tech billionaires are an ultra-competitive bunch, so Nvidia's massive planned investment in OpenAI should accelerate the race to achieve AGI and ASI. And this will benefit Nvidia and its stock, as companies ferociously pour even more money into buying Nvidia's AI-enabling infrastructure.

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Beth McKenna has positions in Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia, and Tesla. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.