Early Tesla and Amazon Investor Says Nvidia Will Hit $50 Trillion Market Cap

“The potential scale of Nvidia in the best-case scenario is both far greater than I have ever seen before and could lead to a multi-trillion market cap,” James Anderson, a former partner at investment giant Baillie Gifford, told the The Financial Times“This is not a prediction but a possibility if AI works for customers and Nvidia’s lead is intact.”

The chipmaker behind OpenAI’s ChatGPT has enjoyed meteoric growth thanks to the AI ​​boom, which has created half a million new millionaires who have invested in the technology that has begun to revolutionize the workplace and media consumption. Nvidia, along with tech giants Amazon, Google, Microsoft and Apple, is worth $14.5 trillion and accounts for about 32% of the S&P 500. With the AI ​​darling’s data center revenue growing at about 60%, Anderson calculated, if the trend continues over the next decade, the company would have a market cap of about $49 trillion. That’s more than the total value of every company in the S&P 500, which is about $45.84 trillion. Anderson put the probability of such an outcome at 10% to 15%.

Anderson’s predictions are ambitious, but his intuitions have already proven correct. With a “go big or go home” mentality, he has been one of the biggest advocates for Amazon and Tesla (Anderson’s investments in the electric vehicle giant were second only to CEO Elon Musk’s). From 2005 to 2021, the Scottish Mortgage Investment Trust, managed by Baillie Gifford, returned 2,240%. He invested in Nvidia in 2016. Lingotto Investment Management, where Anderson is now an investor, has a $650 million fund with Nvidia as its largest holding.

Nvidia didn’t have a clear path to success when Anderson began investing in the company, he said. Whether it would be a gaming, cryptocurrency or AI company remained to be seen. But it had the advantage of early success, unlike Amazon and Tesla, which “didn’t start from a very profitable, dominant position, but had to get there.” In some ways, Anderson still sees Nvidia as a nimble company.

“It’s the long-term development of the use of (graphics processing units) in AI – and not just AI – from excitement, through potential pauses, to transformation of industries that’s most important to us,” Anderson said.

Not so fast

Other financial experts don’t share Anderson’s optimism about Nvidia. Aswath Damodaran, a finance professor at New York University’s Stern School of Business, believes Nvidia is riding a wave of emerging AI optimism.

“The momentum is clearly on Nvidia’s side,” Damodaran said. CNBC in May. “They can do no wrong. Everything they touch turns to gold.”

Damodaran said Tesla experienced a similar recovery in 2020, when its market cap soared to a peak in 2021 of $1.2 trillion, only to fall about 30% this year alone. Meta and Google have also faced increased competition that has loosened their grip on the tech world. While Nvidia has the earnings to back its astronomical valuation, expectations for the company’s future may be too high, he argued. Damodaran said the AI ​​chip market alone is not worth $1 trillion, and the broader AI market is worth about $2 trillion or $3 trillion, meaning Nvidia would need to tap into several large AI markets to maintain and grow its value.

“It’s definitely a possibility,” Damodaran said. “But is it plausible? I don’t think so.”

It’s too early to tell whether Nvidia has what it takes to lead the tech giants in AI in the long run, said Doug Clinton, managing partner at Deepwater Asset Management. Nvidia’s colossal growth may seem daunting, but it’s sustainable, especially as demand for AI is expected to grow.

“While we are all concerned about the potential slowdown in demand for microchips, we have not yet really seen that slowdown,” Clinton said. Yahoo Finance last month. “And it may take longer than we think to slow down.”

With Nvidia accounting for more than 80% of the global GPU semiconductor market, the company is likely to continue to thrive in the near future, Clinton said.

“Can Nvidia maintain its dominance in providing the brains for these AI models?” he said. “I think they can for the next three to five years.”