Beyond Nvidia: How the AI Picture Could Evolve for Investors

If you'd asked the average investor in 1996 about internet companies, they might've mentioned Cisco (CSCO) or Sun Microsystems. People knew Amazon (AMZN) as an online bookstore. Some likely thought of Google (GOOG) as a very large number. 

Despite that uncertain landscape, the web represented a vast opportunity, with risks that turned out to be just as vast. The same could be true with artificial intelligence (AI) today, though it's still early. So far, only a handful of firms, including Nvidia (NVDA), Microsoft (MSFT), and Advanced Micro Devices (AMD), have hit AI homeruns, and there is no guarantee those won't strike out. 

More long balls could be ahead, but no one really knows which companies might be the next Nvidia, or even if there will be a next one, or even what the future of Nvidia holds. 

However, many market watchers and commenters expect that AI will soon be everywhere, just like the internet.It's  already making a huge impact on existing applications like cloud storage and data centers, while Microsoft's adoption of Open AI's Chat GPT's AI system into its work software raised the profile of large language models. Those early beneficiaries saw their stocks take off, but what if you chose not to jump in to NVDA or MSFT a few years ago? 

Anyone hoping to add new AI-related investments is likely to face a more surgical hunt for opportunities—possibly finding singles and doubles and strike outs rather than homeruns. And high-profile disruptors are likely going to be part of this story—in late May, Tesla's (TSLA) CEO Elon Musk raised an eye-popping $6 billion for his AI startup xAI.

While Musk has $6 billion to put into AI adventures, most investors don't have similar-sized resources. If you're looking to make sure your portfolio has at least some exposure to this new technology, which allows computers and other machines to learn and even seem to "think" without human input, consider how the internet evolved nearly three decades ago. 

Keep in mind that after the internet boom took place, there was also a bust, as a dizzying array of once high-flying tech and communications stocks crashed, with many disappearing completely. There is no guarantee that an AI stock will thrive or even survive. As businesses and consumers embraced the internet, several types of companies found the most traction, and they tended to fall into one of four categories:

• Pick and shovel makers: Gold can't be mined without the proper tools, and the internet couldn't function without companies building and running the technology. Some chip firms, networking hardware makers, software builders, and information technology service providers thrived as the internet raised their profiles. Company stocks like Oracle (ORCL), Intel (INTC), and Cisco (CSCO) soared during the late 1990s.
• Second chancers: Apple (AAPL) and Microsoft were successful long before the dot-com madness but found ways to recharge their businesses through the internet with technology like iTunes (Apple) and the data cloud (Microsoft). The internet also caused demand to soar for these companies' existing products, such as Mac and Office, as billions of people around the world jumped online.
• Trojan horses: These are companies that weren't necessarily in tech but still were able to revolutionize their businesses using the internet. Think of how Walmart (WMT) used online ordering to grow its reach, or how financial services giant CME Group (CME) took advantage of the internet to dramatically expand trading volume electronically.
• New faces: Companies like online retailers, search engines, and social networking sites wouldn't exist without the internet providing a platform. They formed once the internet became reality and made the technology useful for the average person.

It's the latter categories that will likely require more detective work and possibly more risk for investors. Few if anyone in 1996 would've imagined a Google or a Facebook (META) and the billions of dollars they would make the internet for a platform. With AI, it's possible such companies are in the works or may already exist without investors realizing the opportunity.

Some firms may find success in producing tools and services that bring new technologies to market, but others may recede or fade away completely. Certain companies that provide chip fabrication or produce equipment necessary to create chips might fit into this category and have already rallied over the last year or two thanks to AI. 

The moat is big around some of the specialty chip pick and shovel makers, but there are under-the-radar companies out there, as well. One way to get a sense of which ones might be out there is to check corporate filings from some of the biggest AI firms to see what companies they've invested in and which ones they might be trying to buy.

And while companies like NVDA and AMD appear to have large moats now, the history of the internet shows how things can rapidly change. Think, for instance, about internet search, where several well-known leaders in the 1990s gave way to Google. Companies can seem far behind in a business field, but they may end up outpacing those that enjoyed the first wave of success. This can happen in any industry, including AI.

Some of the largest companies of the internet age gained new life in AI. For example, take notice of how AI is transforming the cloud industry and helping fuel better profitability there.

Companies that made their names on cloud computing, software, cybersecurity, and electronic devices all have been crowing about how much AI can help their businesses, and it doesn't take much digging to find which old-line companies might benefit. They talk about it on almost every earnings call. The challenge for investors is to separate companies that really can find traction from AI and those that just want to get that message across without much beef behind it. 

Upgrading an old business with the new technology carries opportunities but also risks. For instance, it may be tough for certain traditional semiconductor firms to immediately serve the needs of customers that want AI-powered chips. We're already seeing some firms face these challenges, and their stock prices tell the tale. Strong corporate management and deep pocketbooks are among the advantages to look for when assessing how nimble a company might be at making these changes.

Transformation is also an expensive process and doesn't promise success. Several large tech companies are touting plans for vertical integration, meaning they'll build their own chips. This hasn't always worked in practice. If one does succeed, it would potentially save the costs of going to Nvidia or AMD for their hardware.

Also, for companies with cloud software, integrating AI has its advantages and disadvantages. The process is extremely costly, but it may get cheaper as more chip firms find ways to compete with Nvidia's early lead and if vertical integration gets traction. Each quarter, check earnings from the cloud companies to see which ones show solid results improving margins thanks to AI and which seem to be struggling with rising costs and less return on investment.

You don't always have to be a tech firm to grow like one. Similar to the internet, AI could give investors potential opportunities beyond pure tech.

While it's not a done deal, don't count out AI's impact on utility and energy companies that produce and provide the power to run AI. 

Farther out, AI technology might itself help energy companies deliver energy more efficiently, perhaps by identifying demand patterns and finding areas of inefficiency at plants. Or by getting applied to the nearly century-old goal of harvesting fusion to create usable power.

Even one of the world's oldest industries, agriculture, could present AI opportunities. There's U.S. government funding for crop and soil monitoring systems that leverage machine learning. AI can help farm and ranch managers enhance sustainability and economic efficiency, reduce food waste and loss, and reduce crop losses caused by pests and weeds. 

For instance, one firm builds a device that traps and identifies pests. It uses pheromones to attract pests, which are photographed by the device. AI identifies different pest species and uses location and weather data to map out the likely impact. The findings are sent to farmers. AI and beetles? You bet.

The list goes on. AI could help provide financial companies improved data analysis to narrow down lists of companies to invest in. It could speed drug development for biotech and pharmaceutical companies, helping them better identify which patients might benefit most from a particular treatment or establish which combinations of doses could work best in clinical trials. Food and beverage companies could use AI for quality control and to automate manufacturing tasks. 

Other potential trojan horses are companies often flying under the radar with businesses that might benefit from AI demand. For instance, AI could be used in the manufacturing process to help companies across many industries improve product quality, eliminate production errors, scan bar codes, and guide assembly robots to do tasks like filling bottles more efficiently.

Mention the word "mining" and it may conjure up the notion of solving a cryptographic problem to earn bitcoin—but old school mining may also benefit from AI. Nvidia's pivot to copper cables from optical fiber for data transmission over short distances in AI data centers signals the potential for a major increase in copper demand. AI demand for precious metals may also affect the silver market because the gray shiny metal has the lowest electrical resistance among all metals at standard temperatures and is increasingly used in AI components.

If you didn't connect scanning bar codes and filling bottles as tasks for AI, you're not alone. But how do you find which companies can harvest and use AI to the best advantage in ways that might improve margins? That's the trickier part. As with the internet, certain companies will likely make fast and dramatic progress while others get left behind. There's no sure thing.

Everyone loves a winner, and in this case, it means companies that form after AI and wouldn't exist without it, as was the case with Google and the internet (Google was founded in 1998, several years after the internet became popular). Facebook wasn't founded until 2004. 

Finding new faces could be the hardest thing for investors, because few in 1996 could've looked at the early internet and determined that a site allowing people to share photos of their cats would ultimately become one of the world's highest-revenue companies. Still, there are breadcrumbs to follow in these early AI days that might help investors figure out where such opportunities might lie. 

The AI startup field is likely to get lots of attention, and one way to follow it would be to pay attention to Musk's startup to see what sorts of technology the EV pioneer is investing in. Monitor incoming initial public offerings (IPO) for clues, too.

Also, consider bookmarking the U.S. Securities and Exchange Commission (SEC) EDGAR database to see where AI innovators, their customers and other major sector companies are investing in AI. In February, Nvidia included details in a quarterly filing on how it was evaluating opportunities in autonomous driving, medical imaging and drug discovery, among other areas. 

Speaking of Nvidia, anyone who listened to its May 2024 earnings call heard CEO Huang spotlight a couple of companies that appear to be making novel use of AI and may be worth watching. 

That's not to say investors should blindly invest in whatever Nvidia thinks is a good company. However, it could get you started in the research process and indicate which industries might ultimately see paradigm-changing AI impacts. 

If you think it's hard as an individual investor to figure out how all this might determine winners and losers, consider looking to Wall Street managers that put together investment portfolios of AI firms. There's more than a handful of so-called "thematic" ETFs focused on AI. See what they've invested in and read their prospectuses to see if you agree with their thinking. Also, remember that ETF investing has its own set of risks and rewards, and investing in general sector ETFs is a choice retail investors might want to consider. 

Almost any industry can and does promote AI-related improvements or benefits, and headlines soon follow. The number of AI mentions on recent earnings calls is immense and across all industries. The trouble is learning what might stick and what's just hopes and dreams. 

That brings up a risk that also dates back to the heady dot-com days when companies like pets.com soaked up investor dollars and ground them into dog food and cat litter. Investors hoping to jump on the AI bandwagon should avoid letting emotion and big headlines determine their choices. Know what you're getting into, study business plans, and make sure the executives seem trustworthy as they make their elevator speeches.

There's also the more fundamental risk that AI might not pan out as the world-changing trend many expect it to be. You can find plenty of skeptics on Wall Street and elsewhere who say the jury is still out on whether companies now making big bets on AI will enjoy adequate return on investment. Prices for AI chips and other equipment aren't cheap either, meaning a recession could likely hurt demand.

In addition to the specific risks related to individual stocks, AI stocks broadly may face tougher regulation and legislation as agencies and lawmakers work to put safety boundaries on the development and uses of AI. The Federal Trade Commission is investigating recent investments and partnerships involving generative AI companies and major cloud service providers. The use of intellectual property for generative AI companies is also an issue.

Geopolitical risk is also out there. Even before AI, many investors were likely aware that the chip industry relies mainly on one company, Taiwan Semiconductor, to make its products. Any sign of China flexing its muscles against Taiwan could raise concerns.

To avoid tying up too much money in a handful of companies that may or may not be AI winners, any investor convinced AI could have planetary-wide impacts might just want to make sure they have exposure to a wide group of stocks spread across many industries and regions. If you're hoping to find the next Nvidia needle in the AI haystack, you might end up disappointed.

To narrow it down, investors might consider thematic investing available through Schwab. Thematic investing uses research to identify companies relevant to a particular theme and then group them into lists you can invest in. In contrast to sector investing, themes can include investments that span many industries. AI is one of the available Schwab Investing Themes™. 

For investors, the advancement of AI will likely be about fast and sometimes unexpected developments. Remember, until early 2023, Nvidia was mainly known for its video game chips, and that changed in a hurry. Investors will likely have a lot to study and may need to pivot or revise their plans as this technology evolves.