It’s clear that Nvidia(NASDAQ: NVDA) has been the biggest winner of the artificial intelligence (AI) infrastructure boom. Its graphics processing units (GPUs) have become the go-to chips for running AI workloads in data centers, thanks to their parallel processing capabilities. Parallel processing allows chips to perform many calculations all at once, which is essential for both training large language models (LLMs) and running AI inference.
Just as important is Nvidia’s CUDA software platform, which makes it easy for developers to build and optimize AI models on its hardware. The combination of best-in-class GPU performance along with a sticky software platform has helped cement the company’s lead in the data center space.
At the same time, this has been an explosive market. Over the past two years, its data center revenue has gone from $4.3 billion in the fiscal first quarter of 2024 (ended April 30, 2023) to $39.1 billion in fiscal Q1 of 2026 (ended April 27, 2025). That’s a nearly 10 times increase in just two years.
Nvidia sees data center capital expenditures (capex) rising to more than $1 trillion by 2028. Not all that spending will go toward GPUs, but with its more than 80% market share in the GPU space, Nvidia is well positioned to capture a sizable chunk of that overall data center spending growth.
However, that is not the only potential huge market that Nvidia is eyeing.
While AI data center spending is Nvidia’s largest market by far, it’s certainly not the only end market it participates in. The GPU was originally created to speed up graphics rendering in video games. The company later created CUDA as a way to expand beyond this market, giving developers an easy way to program its GPUs for other tasks.
However, the market for GPUs outside of video games was slow to develop. Around the same time CUDA was introduced, Advanced Micro Devices bought rival GPU maker ATI Technologies. With integration a top priority and not a lot of early traction outside of video games for GPUs, AMD was in no rush to create a competing software platform. Despite the slow uptake, Nvidia smartly began pushing CUDA for use in universities and research labs, which helped make it the default software program that developers were taught to program GPUs. Today, that is why Nvidia’s GPUs have a dominant place in the data center.
At this same time, though, Nvidia was also edging into another market: automobiles. In fact, Audi was one of its first big customers outside of the video game space. The German luxury carmaker began using Nvidia’s GPUs in its infotainment and navigation systems, and Nvidia later built a full automotive platform called DRIVE, which is a family of hardware and software tools developers need for advanced driver-assistance and autonomous vehicle development.
Image source: Getty Images.
While long promised, autonomous driving is finally here. Alphabet’s Waymo, for example, is now providing more than 250,000 paid robotaxi rides per week in the U.S. It’s currently only in a few cities, but it’s expanding rapidly. According to reports, Waymo uses Nvidia’s GPUs in its vehicles.
Waymo is not Nvidia’s only automobile customer — far from it. Mercedes, Volvo, and Hyundai all use Nvidia’s DRIVE platform and GPUs to power self-driving technologies, while Toyota announced it would use Nvidia’s platform and chips for advanced driver assistance features in its next-generation vehicles. Meanwhile, General Motors and Hyundai will use Nvidia technologies to improve their manufacturing with “smart factory” initiatives.
Last quarter, Nvidia saw its automobile revenue surge 72% to $567 million. However, more growth is in store, with the company forecasting its auto revenue to rise to approximately $5 billion this fiscal year. The growth will come as new vehicles using its technology begin to hit the roads. Mercedes’ new CLA sedan is the latest vehicle with its technology.
It’s easy to dismiss a segment that was only a fraction of its data center revenue last quarter, but with the data center, Nvidia showed how quickly end markets can ramp up. The autonomous driving market is still in its infancy, so the opportunity is just massive. With Waymo having just around 1,500 robotaxis now, it’s easy to see that this could scale to 100x or more vehicles when it reaches scale.
Meanwhile, Nvidia CEO Jensen Huang has predicted that every car on the road will eventually be robotic. With more than 1 billion cars on the road, that’s a huge opportunity. At its investor day in 2022, Nvidia estimated the auto market could be a $300 billion opportunity.
With Nvidia’s stock trading at a forward price-to-earnings ratio (P/E) of 33 times this year’s analyst estimates and a 0.7 price/earnings-to-growth (PEG ) ratio, with numbers below 1 considered undervalued, the stock is currently not pricing in any potential upside from its next big potential market opportunity.
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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Geoffrey Seiler has positions in Alphabet. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, and Nvidia. The Motley Fool recommends General Motors. The Motley Fool has a disclosure policy.
