The past decade has been outstanding for Nvidia (NVDA 1.69%) investors. Shares of the chipmaker have delivered handsome annual gains of more than 60% during this period, turning an investment of just $100 into more than $11,500.

Nvidia's terrific gains over the past 10 years can be attributed to its metamorphosis from a manufacturer of graphics cards meant for gaming personal computers (PCs) into a company whose chips are now used across a wide range of applications including data centers, cars, and digital twins. And now, Nvidia is right in the middle of the artificial intelligence (AI) boom with its chips playing a mission-critical role in the proliferation of this technology.

As such, it won't be surprising to see the next decade turn out to be a rewarding one for Nvidia investors, just like the last 10 years. This article will take a closer look at its key catalysts first and then see how much upside investors could expect from the stock over the next decade.

Nvidia's major growth drivers for the next 10 years

Nvidia pointed out on its investor day in March last year that it has a total addressable market (TAM) worth a whopping $1 trillion, spread across multiple verticals such as automotive applications, AI enterprise software, the omniverse, gaming, and chips and systems. Given that the company has generated just under $26 billion in revenue in the trailing 12 months, it has massive room for growth.

The good part is that Nvidia is on its way to capitalizing on this tremendous opportunity already, especially in three major areas: chips and systems, automotive applications, and enterprise software. These three end markets account for $900 billion of the company's TAM, so progress in these areas will be crucial to its long-term growth. Let's look at how it is progressing in these markets.

The automotive opportunity

Nvidia's automotive business is a market where the company sees a $300 billion revenue opportunity. The demand for its chips in vehicles is growing thanks to their increasing levels of automation and connectivity. For instance, the chipmaker projects that the penetration of vehicles with level 2 and level 3 autonomous driving capabilities could increase from 10% last year to 50% in 2030.

And the growing number of cameras in each vehicle means that the amount of image processing is going to jump substantially. All this indicates that the need for Nvidia's graphics cards in the automotive market should increase because the large amount of data generated by each vehicle will have to be processed quickly to drive autonomous applications and connectivity.

And the company has built a solid ecosystem of customers, including original equipment manufacturers and component suppliers, that have helped it gain robust revenue in the automotive market.

In March last year, Nvidia was sitting on an $11 billion pipeline of automotive revenue. That figure has now increased to $14 billion, and it won't be surprising to see it head higher given the massive addressable opportunity in this space.

The second big catalyst, data centers, is where the company is on track to gain from two applications: enterprise data centers and hyperscale data centers.

The latter are large facilities that big data companies use to process huge amounts of data using fast connections. They are known for being scalable and can tackle intensive workloads. Enterprise data centers, on the other hand, are smaller than their hyperscale counterparts.

Nvidia sees a $150 billion revenue opportunity in hyperscale data centers, driven mainly by the growing adoption of AI. Its graphics processing units (GPUs) are being increasingly deployed in data centers for training large language models and for inferencing purposes. For the record, inferencing is where the deep learning systems of AI meet the real world, making predictions about new, unseen data based on previous training. The chipmaker says that the use of GPUs for inferencing has shot up 9 times in the span of just three years.

Lastly, Nvidia's GPUs are being heavily used for training AI models. The company's graphics cards have been deployed for ChatGPT by OpenAI, and more companies keep joining the fray. Not surprisingly, there is reportedly a waiting period of two to three months for the chipmaker's AI-focused data center GPUs.

The data center business has generated $15.5 billion in revenue in the trailing four quarters, but there is still a massive opportunity in this space.

Terrific earnings growth is in the cards

The substantial growth opportunities discussed above tell us just why Nvidia's revenue and earnings are expected to head significantly higher.

Fiscal Year

Revenue Estimate

Year-Over-Year Growth 

Earnings Per Share Estimate

Year-Over-Year Growth

2024

$42.8 billion

59%

$7.78

133%

2025

$51.3 billion

20%

$9.72

25%

2026

$63.7 billion

24%

$12.33

27%

Source: YCharts.

Analysts also expect 21% annual earnings growth over the next five years, though it could increase faster thanks to the catalysts discussed above. Assuming earnings increase at even 25% a year from fiscal 2027 through fiscal 2033, its bottom line could jump to almost $59 per share after 10 years (using fiscal 2026's projected earnings as the base).

In other words, Nvidia's earnings could multiply by nearly 18 times over the next decade based on its fiscal 2023 bottom line of $3.34 per share. That would be a much faster increase than during the past decade.

NVDA Net Income (TTM) Chart

NVDA net income (TTM); data by YCharts. TTM = trailing 12 months.

The company's improved earnings power over the next decade should have a positive impact on its share price as well. So investors who have held on to this tech stock over the past 10 years should continue to do so.

Investors currently have to pay a premium for Nvidia's stock, given its current price-to-earnings ratio of 205. However, the company's projected earnings growth and strong potential in sectors such as AI, automotive applications, and data centers still make a compelling investment case even at these lofty prices. And Wall Street expects Nvidia's bottom line to bloom -- the forward price-to-earnings ratio of 50 suggests substantial future earnings growth.

Nvidia is not just riding the coattails of technological advances but actively shaping an AI-powered future. With its robust product pipeline, strategic positioning, and solid growth trajectory, Nvidia appears well-equipped for the future, making it an attractive idea for long-term investors.