If the stock market’s artificial intelligence winners were in a police lineup, the usual suspects would not be hard to identify.
AI chip designer Nvidia would jump out. So would data center operators and machine learning infrastructure plays such as Microsoft, Amazon.com and Alphabet. Software providers Oracle and Salesforce, which offer AI-powered features, would stand out, too.
The problem? They’ve been analyzed to death by Wall Street. And to borrow from the theme song of the TV sitcom Cheers, everybody knows their name.
Sign up for Kiplinger’s Free E-Newsletters
Profit and prosper with the best of expert advice on investing, taxes, retirement, personal finance and more – straight to your e-mail.
Profit and prosper with the best of expert advice – straight to your e-mail.
“This cast of characters is pretty well understood,” says Andrew Choi, manager of the Parnassus Core Select exchange-traded fund.
But an emerging group of AI stocks doesn’t fit the typical profile and is flying under the radar. It’s possible to invest in the artificial intelligence–amplified digital revolution via less-obvious companies, such as so-called adopters, or beneficiaries of AI automation.
“You have to think a little bit out of the box,” says Robert Ruggirello, chief investment officer at Brave Eagle Wealth Management.
A good example is language-learning platform Duolingo (DUOL, $390), which uses an AI-powered chatbot and app-friendly purple-haired teen character named Lily to help people learn up to 40 languages by having interactive, real-time chats with her.
Or HVAC systems maker Trane Technologies (TT, $383), which uses AI to identify performance issues, better predict servicing needs and energy usage, and help systems work more efficiently. (Prices are as of April 30; names we recommend are in bold.)
AI, at its core, is a business productivity enhancer. So-called “reinvention-ready” companies that use generative AI (a type of artificial intelligence that enables machines to respond naturally to human conversation) show 2.4 times greater improvement in productivity and 2.5 times higher average revenue growth, according to a study by consulting firm Accenture.
But getting exposure to stocks benefiting from the use of AI is tricky.
There are dozens of mutual funds and ETFs with “AI” or “artificial intelligence” in their names, but they invest mainly in tech firms focused on the infrastructure build-out phase of this technology, such as makers of semiconductors, chip manufacturing companies, cloud computing and data center stocks, and software firms writing code.
A challenging adolescence
And with AI still in its adolescent stage (just 16% of organizations in 2024 had fully modernized, AI-led processes in place, Accenture found), pure-play funds focusing on the AI productivity investment theme don’t exist.
“There’s really no portfolio specific to that theme,” says Bryan Armour, director of passive strategies research for North America at fund-tracker Morningstar.
The still-young AI industry also makes it tough to precisely quantify the efficiency benefits and cost savings companies derive.
Analysts say AI has the potential to be transformative in some areas but provides just incremental benefits in others.
Investors, therefore, must do their own detective work to ferret out so-called AI 2.0 companies, or those benefiting most from AI-driven productivity gains and product breakthroughs.
A good starting point is to identify companies in sectors and industries outside technology that can benefit from AI automation-driven cost savings on a large scale or use machine learning to boost product innovation that spurs sales.
You’ll want to home in on companies boosting productivity and profit margins with the help of AI-driven efficiency gains and cost savings.
Just as Wall Street looks at same-store sales to gauge a retailer’s true strength, or customer acquisitions for clues about a streaming service’s growth, investors hoping to identify AI winners can measure progress by analyzing key metrics that measure efficiency gains. One gauge to focus on is revenue per employee.
“For a positive AI impact, revenue per employee should increase over time,” says Ulrike Hoffmann-Burchardi, head of the chief investment office, global equities, at UBS Financial Services.
AI can boost efficiency (especially in businesses that rely on human workers who perform repetitive manual tasks) by increasing worker output or by reducing costs via headcount reductions.
A second data point to watch is profit margins. “AI should help drive margin expansion,” says Jeremiah Buckley, portfolio manager at Janus Henderson Investors, meaning a greater percentage of each sales dollar is retained as profit.
Other key measures to track are employment headcounts and costs (are they falling?); customer-service efficiencies (are phone, online, or chat wait times shrinking?); and, of course, sales (are they increasing?).
“AI is just one more compelling rationale to consider when picking stocks,” says Choi of Parnassus Funds.
Beyond the Magnificent Seven
AI-driven productivity is the next long-term propellant of stock prices, as the internet was 25 years ago, according to Janus Henderson Investors, with the technology seen as infiltrating every sector, industry group and business.
One investment approach, therefore, is simply to buy a broad, low-cost index fund. For another approach, Ed Yardeni, president of Yardeni Research, touts the “S&P 493” — a reference to the stocks in the S&P 500 index other than the Magnificent Seven — as “big beneficiaries” of the expected AI productivity boom.
Exposure to those 493 large-cap stocks is available via Defiance Large Cap ex-Mag 7 (XMAG, $20), a $32 million ETF that just opened in October — so it doesn’t have enough of a track record to recommend it. The fund tracks an index of all S&P 500 stocks except for the Magnificent Seven.
Certain sectors stand out in the search for AI 2.0 winners. We zero in on three below.
A good fit for finance
One place to look for AI adopters with upside potential is your local bank, where many tasks and client dealings once performed by humans are now handled by AI-powered tools, such as chatbots and virtual assistants.
That frees employees to focus more time on products and customer touchpoints that drive revenue. Big banks have tens of millions of customers, countless daily customer service interactions, mountains of personal and financial account data, and a huge responsibility to spot and fight fraud, and are poised to profit from machine-driven efficiency gains on a massive scale.
“Big banks,” says Yardeni, have “the most potential for bang-per-buck productivity gains.”
Erica, an AI-driven virtual financial assistant created by Bank of America (BAC, $40), for example, has interacted with customers more than 2.5 billion times since its 2018 launch. Last year, it helped 2 million customers a day, the bank says.
At JPMorgan Chase (JPM, $245), the nation’s biggest bank, most employees have access to large-language-model tools that enable them to use generative AI to interact with customers and assist with various work tasks.
JPMorgan is also adding generative AI to call centers to help agents more quickly answer questions about car loans, mortgages, credit cards and deposit accounts. AI also helps detect fraud, which minimizes write-downs for theft-related losses.
“JPMorgan has been out in front of this,” says Brave Eagle’s Ruggirello.
Investors betting that AI will boost the U.S. banking industry broadly might consider Invesco KBW Bank ETF (KBWB, $61), which invests in two dozen banks and sports a yield of 2.9%.
Insurance, a data-processing-intensive business, is another beneficiary of AI. Property and casualty insurers such as Allstate (ALL, $198) and Progressive (PGR, $282) are using AI to enhance underwriting and claims processing, refine risk assessments related to weather, and improve pricing strategies.
Handling claims for a car totaled on a highway or a home damaged by a hurricane, for example, can now be done in large part using AI tools.
“A lot of this work is becoming more and more digital,” says Choi.
Modernizing industry
Efficiency, precision and cost savings are the hallmarks of industrial businesses, and AI could do for manufacturing companies today what the assembly line did for autos a century ago.
Machine learning is already making an impact on product designs, predictive monitoring technologies, and energy and operational efficiency, as well as lowering costs through automation and advanced robotics.
Gregg Fisher, founder of Quent Capital, is bullish on German-based tank manufacturer Rheinmetall (RNMBY, $339). It offers an AI-supported navigation system that enables tanks to maneuver complex terrains autonomously, reducing the need to put human operators in dangerous wartime situations. The system can be installed in existing and new tanks.
“Because of the war in Ukraine and what’s happening in Europe, the Middle East and the rest of the world, [Rheinmetall] can’t keep up with the orders they’re getting,” says Fisher.
Another industrial stock with AI chops is Axon Enterprise (AXON, $613), the maker of non-lethal Taser stun guns and a suite of AI-enhanced public safety tools, says Bryan Wong, manager of Osterweis Opportunity Fund. Axon’s AI tools can auto-generate police reports — which can eat up 40% of an officer’s day — in half the time by transcribing audio from officers’ body-worn live-streaming cameras.
The technology can create court-ready documents in minutes and scan license plates of vehicles traveling 140 miles per hour, across three lanes of highway, to search for suspects.
“Think about the cost of an officer’s time,” says Wong. “If you can save even one hour, you can redeploy the officer back toward policing.”
Axon is the market leader in body-worn cameras, according to market-research firm Mordor Intelligence. Still, Axon’s growth runway is long, as its market penetration of law enforcement is less than 15%.
Agriculture heavy-machine maker Deere (DE, $464) is using AI for precision farming, using machine vision to distinguish weeds from crops.
“This See & Spray system only sprays herbicide on the weeds,” says Ruggirello, saving farmers time and money by significantly reducing the amount of herbicide they have to put down.
A prescription for health care
AI can speed up drug development by pharmaceutical and biotech companies, and it can be a boon to health insurers such as Cigna Group (CI, $340) that are looking to automate and better analyze claims processing and improve customer service. The technology can also assist doctors with data-driven health decisions and earlier disease detection.
Intuitive Surgical (ISRG, $516) uses AI technology in its surgical robotics systems. Intuitive, best known for its minimally invasive procedures, draws on its database of more than 10 million procedures to provide insights that help speed surgeon training, assess patient risk factors and predict potential complications, not to mention improve patient outcomes.
“You can learn quite a bit from that huge collection of data,” says Choi.
When it comes to AI, the early adopters are the ones to watch. As the AI rollout matures, says Jay Jacobs, U.S. head of thematic and active exchange-traded funds at money management firm BlackRock, the focus will shift from whether it’ll have a big impact (it will).
Now, “it’s more about who’s going to adopt it early and use it effectively, versus the companies that are going to fall behind,” he says.
Note: This item first appeared in Kiplinger Personal Finance Magazine, a monthly, trustworthy source of advice and guidance. Subscribe to help you make more money and keep more of the money you make here.
