Artificial intelligence (AI) has moved from speculative buzz to a transformative force reshaping the industry, with Nvidia Corporation (symbol: NVDA) leading the charge. As the driving power behind generative AI—a burgeoning subset that processes raw data to create predictive outputs—Nvidia has dominated the GPU market and achieved unprecedented stock performance. With the generative AI market projected to grow from $40 billion in 2022 to $1.3 trillion by 2032, Nvidia’s meteoric rise sparks optimism and caution. While some investors see it as the cornerstone of future growth, others question whether its valuation already accounts for its potential.
Probably the most effective way to value AI stocks is to look at their earnings, growth prospects, and stock prices. The largest and most heavily traded AI stock, with a gigantic price movement, is that of Nvidia Corporation (symbol: NVDA). Part of this sector is the generative AI subset, which had limited activity a year ago and now is an important market. Generative AI, simply put, takes raw data and generates statistical probable outputs. It is constantly developing, and there are countless possibilities for its use. (Disclosure: my clients own NVDA)
Graphics Processing Units (GPUs) handle graphics-related work such as graphics, effects, and videos. According to a report from IoT Analytics, “NVIDIA leads the data center GPU segment with a 92% market share, while OpenAI and Microsoft have a combined share of 69% in the foundational models and platforms market. The services market is more fragmented, with Accenture currently seen as the leader with a 6% market share.”
Bloomberg Intelligence Weighs In On Growth Prospects
According to a new report by Bloomberg Intelligence (BI) “the generative AI market is poised to explode, growing to $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022. Growth could expand at a CAGR [compound annual growth rate] of 42%, driven by training infrastructure in the near term and gradually shifting to inference devices for large language models (LLMs), digital ads, specialized software, and services in the medium to long term, BI’s research finds.”
NVDA Is Reasonably Priced, Considering Earnings Expectations
The price/earnings to growth ratio (PEG) is calculated by dividing a company’s P/E by its growth expectation; it allows an analyst to value a company based on the price/earnings multiple and its growth factor. Using Yahoo Finance’s current year’s average earnings estimates, its next year’s (the year 2026) average earnings estimates, and its trailing 12-month price/earnings multiple, NVDA has a PEG ratio of 1.65 (in early November 2024). This is a relatively high ratio, but not when considering the company’s growth.
For comparison, Morningstar.com, using its long-term earnings estimates and present P/E earnings for the SPDR S&P 500 ETF Trust (symbol: SPY), shows a 1.82 PEG ratio for SPY. SPY is the broad-based index that many money managers use as their big-cap benchmark.
NVDA soared 223 percent over the last year and 858 percent over the last two years for the period ending 11/01/2024. Although its future is promising and its valuation reasonable, some investors think that its outlook is already reflected in its market price. Other investors and analysts think otherwise. There are reservations about how big AI will become and regarding the costs involved in operating in the AI market.
One early NVDA investor, Scottish Mortgage Investment Trust, Edinburgh, Scotland, has sold about 866 million GBP worth of its NVDA over the last 6 months for just this reason, according to The Times of London. The Times quotes Tom Slater, lead manager of the trust, saying,
“The primary challenge hindering large-scale AI adoption remains the high cost … This raises concerns about the sustainability of current capital equipment spending, including Nvidia chips.”
NVDA still remains the trust’s fifth-largest single holding.
A differing opinion comes from a Senior Analyst at Bank of America, Vivek Arya, who thinks the stock should be bought for growth. On CNBC Television in October, he said about NVDA that “the opportunity is much larger, and their competitive position is much stronger, and finally we look at the stock. We have a stock that is trading less than 1 times earnings growth, and if you were to take an average of the other so-called Mag 7 stocks, they are trading at less than 1.9 times their average earnings growth for next year.” That is why Arya says, “There is a large opportunity, even at these levels: the company is executing well, and the valuation is very compelling, even at these levels.”
How About Buying ETFs for a Basket Representation in the Chip Sector, Including NVDA?
Buying sector representation might be a good strategy so that an investor can own some NVDA as well as other companies in the semiconductor sector. Owning other companies offers diversification. But often, sector exposure through funds or ETFs does not give spectacular results that some of the individual issues in that sector will return.
Consider the VanEck Semiconductor ETF (symbol: SMH), for example. As of the time of this writing and using Yahoo! Finance as a source, NVDA comprises about 20 percent of the SMH portfolio. That is a large holding of one stock. Over the two years ending 10/31/2024, SMH is up about 150 percent, a great return, but NVDA is up about 868 percent. Over five years, SMH had a return of 285 percent, beating the S&P 500, which was up about 90 percent in that period, which is also good but not as good as NVDA’s performance.
San Francisco, the AI Industry’s Home
In SMH’s portfolio, 7 of the top 10 companies have their headquarters in the San Francisco Bay Area. This is not by happenstance. A Brookings Institution report in July 2023 stated that “AI activity, even more than most digital technologies, remains heavily concentrated in a short list of “superstar” tech cities.” And that “Generative AI activity specifically also appears to be highly concentrated so far, as nearly half of generative AI job postings of the last year were published in just six AI-leader metro areas (San Francisco, San Jose, New York Los Angeles, Boston, and Seattle).”
The report further stated that, “Among these hubs, San Francisco and San Jose, Calif.alone accounted for about one-quarter of AI conference papers, patents, and companies in 2021. These Bay Area metro areas also boasted about four times as many AI companies, job postings, and job profiles as the average values of the next tier of 13 early adopter metro areas. Central to their success are the world’s two top universities in AI research (Stanford and the University of California, Berkeley) as well as many of the world’s leading investors in AI research and development, including Alphabet, Facebook, Salesforce, and NVIDIA.”
Importantly, the area contains an already developed private and public donor and “angel investing” base, as well as a legion of early-stage company backers. The top universities in this Area are impressive, including Stanford University, the University of California, Berkeley, and others. Google, Salesforce, and many other leading tech giants started and have their headquarters in the area, with their army of trained technicians and executives.
The Hiring Market Suggests AI is Booming
AI-skilled people are already in San Francisco, and many more are arriving as the industry grows. Determining the ultimate size and calculating the cost to the tech industry of AI varies between industry professionals and investors: some think AI will continue growing exponentially, and those who believe that the whole thing is overblown and that it is not such a big deal. No matter what the outcome, San Francisco has the infrastructure to supply it with money and people, and if more is needed, people will flock to the area to participate in more growth.
Much of the funding for the AI boom started back in 2022 and 2023 and came from big tech firms. Among other announcements, Meta completed more Bay Area-based venture capital investments than ever, largely focused on AI. And Microsoft announced spending billions of dollars on AI in Australia, just as a starter.
2023 was an off-year for financing and startups, but AI remained strong. According to Alan Wink of the EisnerAmper Accounting firm, “I think the one that everyone is excited about, and I think it’s going to drive activity in the next three to five years, is the AI space. AI and machine learning are driving the venture capital community right now. I think 20% of VC deals were in AI or machine learning deals, and almost a third of the dollars were in AI. So, it’s an active space right now. Not as active as ai, but I think health tech investing, biotech investing, cybersecurity deals, I think are also gathering a lot of attention.”
It’s hard not to get positive about the growth of AI, especially when considering the hiring that is going on in San Francisco and in the Bay Area. Chevas Balloun writes for Nucamp Coding Bootcamp, and wrote that, “In just the past year, jobs in the AI sector have increased by a staggering 35%! Additionally, investors are actively supporting AI startups in the city, with these startups raising over $1.6 billion in 2022 alone! The AI industry in SF is becoming even more dynamic with companies like Cruise Automation working on self-driving cars and creating numerous engineering and product development jobs.”
San Francisco Has an Active AI Community
There are many networking sites in the Bay Area, and one is in Hillsborough, a mansion called the AGI House. It is only thirteen miles from Facebook and eighteen miles from Google’s headquarters. It features a pool and a Zen garden, the setting making it a good meeting place for technology company founders, engineers, workers, and others involved in the AI industry.
Events, often called hackathons, are held at the AGI House and elsewhere. They are usually short, informative meetings that examine recent trends and developments in the AI world, keeping AI people up to date. Professionals who want to attend can visit the AGI House website and sign up.
San Francisco has welcoming communities of tech workers and company developers. For instance, the Mission, a colorful, active community, is bursting with activities for AI people. Last September, seventy-five events were held across San Francisco. One event was held at the Commons, a social club in a college-type room where many AI people congregate. The events are posted, and many are open to the public.
Driverless Cars, Another AI Development in the Bay Area
Another connection between the Bay Area and AI is the driverless cars, which are all over the Bay Area. These white cars, with no one behind the wheel, share the highways and streets around the Bay Area with real people driving. The Waymo driver, unlike humans, sees and perceives the world through its many sensors, including cameras placed outside of the car, and utilizes special AI software.
The service is growing, with plans to offer more rides in the San Francisco Bay Area and Los Angeles County. Starting in August, Waymo One added service in the San Francisco Peninsula, adding Daly City, Colma, and other cities to its round-the-clock public ride-hailing service. Service was also added in the Los Angeles area, including Hollywood, Chinatown, and Westwood.
Nvidia’s role in the AI revolution is emblematic of the industry’s promise and reflects its challenges. As a dominant player in GPUs and generative AI, the company has delivered remarkable growth, drawing investor enthusiasm and skepticism. While its valuation appears justified by its innovation and market leadership, AI’s high costs and competitive pressures remain hurdles. Whether through direct investment in Nvidia or broader exposure via ETFs, the decision ultimately hinges on an investor’s confidence in AI’s long-term trajectory and Nvidia’s ability to remain at the forefront of this technological revolution.
