Here's How Generative AI Factors Into Nvidia's Plan for Growth

Globe and Mail

27-02-2025

A handful of companies seem to be at the center of the artificial intelligence (AI) universe, and Nvidia (NASDAQ: NVDA) is certainly one of them. The company's unique ability to design some of the most advanced processors for AI has vaulted its status, not to mention its share price, over the past several years.
Nvidia's management has talked extensively about generative AI on recent earnings calls, according to research from The Motley Fool. But what, exactly, are Nvidia's long-term prospects from generative AI? Here are three of the biggest opportunities.
1. Data center spending is through the roof
You've probably noticed a lot of technology companies talk about AI spending lately. The figures are often in the billions of dollars, but what is most of that money being spent on? In many cases, data center infrastructure.
The world's largest tech companies are in an AI race and almost all of them have pulled out their checkbooks to try to win it. Nvidia benefits no matter where the money is coming from because it designs processors that work perfectly for training advanced AI models.
To continue developing new AI models and processing all of the requests being made by current ones, companies need to upgrade their data centers to accelerate their computing power. That means, according to Nvidia's earnings calls, that tech giants are transitioning from general-purpose data centers to AI ones.
The opportunity here is massive. Nvidia CEO Jenson Huang thinks AI data center spending will reach $2 trillion in the next five years alone. The spending is already paying off for the company, with Nvidia's data center revenue more than doubling to $30.8 billion in the fiscal third quarter (which ended Oct. 27).
2. AI cloud computing services are on the rise
This opportunity goes hand in hand with data center spending, but I want to break it out into its own category because I think it's important to distinguish between AI data center spending and AI cloud services.
Some data center spending will go to building and training new AI models. But some of it will go to building out new AI cloud services, like conversational AI, enterprise AI services, artificial intelligence agents, and video and image generation.
Global cloud revenue could reach $2 trillion by 2035 because of AI, according to Goldman Sachs, and as more of these AI cloud services come online, they'll likely be powered by Nvidia's processors.
3. The autonomous vehicle market could be huge
Nvidia develops its own technology for autonomous vehicles and has partnered with many automakers to bring its hardware and software components to the road. Most recently, Uber Technologies and Nvidia announced a new partnership that will utilize Nvida's generative AI tech to "supercharge the timeline for safe and scalable autonomous driving solutions for the industry," Uber CEO Dara Khosrowshahi said.
This is in addition to Nvidia's other partnerships, which include Toyota Motor, Volvo, BYD, and others. The market potential for autonomous vehicles is significant, with Move Strategy Consulting estimating it could be worth $2.3 trillion by 2030. And Nvidia is already benefiting. The company's automotive segment generated $449 million in the first quarter of fiscal year 2025 (which ended Oct. 31, 2024), an increase of 72% year over year.
The current autos segment growth gives Nvidia an estimated $5 billion annual run rate for its automotive segment sales this year. And Huang is very optimistic that there's plenty more opportunity. Speaking about autonomous vehicles at the recent CES conference, Huang said, "I predict that this will likely be the first multitrillion-dollar robotics industry."
Nvidia isn't cheap, but its AI potential remains high
Nvidia's stock has a forward price-to-earnings multiple of 32.5, compared to the S&P 500 's forward P/E of 24.5. That means you're not getting Nvidia at a discount if you buy its shares right now, but it's still relatively well priced amid a sea of AI stocks with much less potential.
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