Where Will Nvidia Stock Be in 10 Years?

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Long-term investing is the key to sustainable returns in the stock market because it smooths out short-term volatility and allows a company's fundamental value to shine through. Tech giant Nvidia (NASDAQ: NVDA) has been at the forefront of generative artificial intelligence (AI) growth. But as the hype inevitably fades and new opportunities like robotics and self-driving cars potentially have their turn in the sun, how will Nvidia respond?

Nvidia has a history of reinventing itself

With roughly 88% of revenue ($30.8 billion) coming from its data center segment, Nvidia is very overexposed to the market for generative AI hardware. This under-diversification puts the tech giant in a perilous position, especially as clients continue to lose money on their AI projects and new low-cost rivals like China's DeepSeek cause shareholders to question the industry's long-term profit potential.

The growing popularity of custom chips also allows key AI clients like OpenAI to bypass Nvidia and design their own hardware through partnerships with fab companies like Taiwan Semiconductor Manufacturing.

But while generative AI now dominates Nvidia's narrative, it wasn't always like this. The company has a history of shifting focus to tackle emerging trends. As recently as fiscal 2022, video game and crypto mining hardware (Nvidia's gaming segment) represented around 46% of total sales ($12.46 billion) compared to just 9.4% today as AI-related growth has overshadowed these once crucial opportunities.

Nvidia's rapid business transformation highlights the versatility of its core technology, the graphics processing unit (GPU), a type of computer chip that uses parallel processing to perform multiple calculations simultaneously. And over the next 10 years, investors should expect GPUs to continue finding new uses, even if demand related to generative AI slows down. Robotics and autonomous vehicles look promising.

Self-driving cars and robotics?

According to analysts at McKinsey & Company, autonomous driving could create $300 billion to $400 billion in revenue by 2035 as automakers take advantage of the technology for software as a service (SaaS). And just like generative AI, self-driving cars need to process large amounts of data quickly and accurately, making this industry a potential gold mine for Nvidia and its industry-leading GPUs.

Tesla is a good example of the potential scale of the opportunity. Despite not offering a well-known generative AI large language model (LLM), the automaker is one of Nvidia's key customers. It is accumulating tens of thousands of GPUs to build its Dojo supercomputer, which is designed to be the brain behind its full self-driving (FSD) platform.