In this piece, we will take a look at Wells Fargo’s top technology stocks that can beat the flagship S&P index over the next 12 months.
As 2024 heads to a close, investors are now focused on the state of the economy, its influence on the Federal Reserve’s interest rate reduction cycle, and the potential offered by the technology industry. They beckon 2025 with a rather historic run on the stock market that has seen several high-growth technology stocks flourish despite the fact that until September, interest rates in the US were at a two-decade high level.
Driving the bullishness behind technology stocks is artificial intelligence. The revolutionary new technology that relies on high-end GPUs to run advanced mathematical techniques and infer new conclusions from existing data sets has been the focus of Wall Street and big technology companies. So far, most of the AI-related stock gains have been limited to the shares of Wall Street’s favorite graphics processing unit (GPU) company whose stock is up by more than 700% since OpenAI publicly released ChatGPT.
However, the gains have to broaden out to other stocks for the AI wave to continue. This broadening is dependent on the use of AI increasing among businesses and consumers. On this front, investment bank Wells Fargo has some insights to share. In its report titled ‘Generative AI — Potential pitfalls, challenges, and risks the bank outlines that while AI “has the potential to be broadly transformative,” there are several “outstanding questions and concerns that need to be addressed before it is widely accepted on a larger scale.” Quoting its ‘The AI Index 2024 Annual Report,’ the bank points out that from 2012 to 2023, the number of AI incidents has jumped more than tenfold from sitting at roughly 10 to ~122. These incidents cover the ethical misuse of AI such as the wrong detection of criminals stemming from facial recognition systems.
WF points out that while these incidents are concerning, other factors will also determine AI’s wider acceptability and use. Broadly speaking, these factors are growing energy requirements and capital expenditure costs, global geopolitical tensions, model inaccuracies, and regulatory constraints. The bank adds that these factors are also accompanied by the potentially transformative effect of AI on the labor market. Starting from its beliefs about the labor market, WF believes that generative AI, which is different from other AI systems such as machine learning, will have a more “nuanced” impact on the labor market compared to traditional AI. Commenting on common worries of AI taking jobs away, the bank outlines that the jobs that AI will replace will in turn be replaced by new jobs created by AI. To quote WF, it believes “generative AI’s disruptive effect on the labor market to mirror other forms of automation — as in the past, its impact likely will be mitigated over time by new occupations spawned by the innovations themselves.”
To help bolster its claim, WF shares data from MIT. It points out that MIT’s estimates show that “60% of U.S. workers are now employed in occupations that did not exist 84 years ago.” As for which job functions might give way to AI, these include knowledge-based roles such as those found in financial services and support roles such as those performed by customer support agents.
Two additional key disruptive AI effects that Wall Street in particular is keenly aware of are its rising costs and the effect on the utility industry. The S&P’s utility sector is up by 28.36% year-to-date which leads the broader index’s 26.48% in gains by nearly two percentage points. Commenting on this, the bank believes that “there will be a significant increase in hardware demand, notably within the data-center environment, to accommodate the substantial increase in AI workloads,” adding that “it may take a number of years to increase the operational efficiency of various large language models and decrease costs to a level more in-line with existing search engines.” WF also shares that while existing opportunities to expand data center footprint to accommodate AI are present, as they “diminish, companies may revisit existing data-center locations to retrofit and upgrade hardware and infrastructure in support of the power and data-consumption needs of new AI technologies.”
Given the criticality of the data center space to AI, WF expands on this sector in another report. Titled ‘Generative AI transforming data center landscape” it comments on the capital expenditure required to set up data centers, future trends for data centers, and the stock market sectors that might benefit from growing interest and focus on the data center industry. According to its analysis, investor attention is mostly focused on AI-related investments in semiconductors and cloud computing.
However, other sectors, such as “cabling; steel racks; cooling (liquid and air); electrical equipment (both inside and outside the box); and backup generators” are also important. WF quotes a utility company to explain why these tertiary sectors are critical in the AI wave. It shares that utility company believes that “the server rack power density required to train a generative-AI-based large language model can require up to five to seven times more power than server racks used for traditional IT workloads in a data center.”
While semiconductor companies are natural beneficiaries of the AI boom, some oft-ignored sectors that WF mentions are industrials and materials. It outlines that when it comes to building massive data centers, estimates suggest “that approximately 35% – 45% of the cost is related to land, building shell, and basic building fit-out. These areas are addressable by companies who supply steel, aggregates, cement, and water equipment and, by extension, construction and engineering firms as well as broad non-residential construction suppliers (such as industrial distributors).” Additionally, “40% – 45% and 15% – 20% of the remaining cost can be attributed to electrical and HVAC systems respectively,” according to Wells Fargo. AI is having an effect on materials, as per the bank, in the form of “increased demand for materials that are used in the production of semiconductor chips, water handling and recycling within data centers, and steel and construction materials to build data centers.”
For some materials stocks and a primer on how they are reliant on the broader economic activity, you can check out 10 Best Materials Stocks to Buy According to Hedge Funds.
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Our Methodology
To make our list of Wells Fargo’s top AI & non-AI stocks that can outpace the flagship S&P, we selected technology-focused stocks from the bank’s recent Focus List and ranked them by their consensus next twelve-month EPS estimates.
For these stocks, we also mentioned the number of hedge fund investors. Why are we interested in stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points. (see more details here).
14. Amphenol Corporation (NYSE:APH)
Number of Hedge Fund Holders In Q3 2024: 69
NTM EPS Estimate: $2.05
Amphenol Corporation (NYSE:APH) is an American computer hardware company that sells cable assemblies, harnesses, fiber optic cables, and other associated products. Its product portfolio provides the firm with wide exposure to the growing data center industry. Consequently, the fact that Amphenol Corporation (NYSE:APH)’s shares have gained 50% year-to-date is unsurprising despite the fact that non-AI IT spending has been muted in a tight capital and credit environment. The firm has also benefited from the fact that it has outperformed analyst estimates in its quarterly earnings. Amphenol Corporation (NYSE:APH)’s third-quarter earnings saw the firm post $4 billion in revenue and $0.50 in EPS which surpassed analyst estimates of $3.81 billion and $0.45. Crucially, the firm’s fourth-quarter midpoint guidance of $4 billion also beat analyst estimates of $3.94 billion. However, 43% of Amphenol Corporation (NYSE:APH)’s H1 2024 came from outside the US and China, so the global economy and IT infrastructure spending have to remain robust for the firm to generate continuing tailwinds.
During the Q3 2024 earnings call, Amphenol Corporation (NYSE:APH)’s management shed light on the industrial segment which is another driver of its hypothesis:
“The industrial market represented 23% of our sales in the quarter. And sales in the quarter grew by 24% in US dollars from prior year, as we benefited from acquisitions. On an organic basis, our sales were flat, as growth in alternative energy, instrumentation, medical and rail mass transit solutions was offset by reduced demand in factory automation, heavy equipment, transportation and oil and gas. Sequentially, our sales did increase by 9% and from the second quarter and were up by 3% organically, which was somewhat better than our expectations coming into the quarter. While we are encouraged to see stronger growth in North America and Asia, demand in Europe did again slowed this quarter. Accordingly, looking into the fourth quarter, we do expect sales to moderate from these third quarter levels.”
13. NVIDIA Corporation (NASDAQ:NVDA)
Number of Hedge Fund Holders In Q3 2024: 193
NTM EPS Estimate: $3.42
NVIDIA Corporation (NASDAQ:NVDA) is Wall Street’s favored AI GPU stock whose shares are up by more than 700% since OpenAI publicly released ChatGPT. Consequently, its hypothesis is exclusively dependent on its GPUs. When it comes to these products, not only does NVIDIA Corporation (NASDAQ:NVDA) have to ensure that they offer the best market performance, but it also has to manage its supply and keep costs manageable to manage margins. Therefore, not only does big tech’s GPU spending have to remain robust for NVIDIA Corporation (NASDAQ:NVDA) to maintain its share price tailwinds, but in-house AI processors developed by the likes of Amazon and others have to prove to be inferior to the benefits offered by the firm’s chips. The firm also benefits from its CUDA software which allows users to tightly control the performance of NVIDIA GPUs to suit their individual needs. NVIDIA Corporation (NASDAQ:NVDA) is also trying to capture tertiary AI markets such as those for interconnects, which underscores the criticality of AI and data center spending for its hypothesis.
Polen Capital mentioned NVIDIA Corporation (NASDAQ:NVDA) in its Q3 2024 investor letter. Here is what the fund said:
“In a reversal from the past two quarters, NVIDIA Corporation (NASDAQ:NVDA) represented our top relative contributor this quarter, despite the modest underperformance, declining -1.7%. In many ways, NVIDIA was a microcosm of the broader market’s heightened volatility. Beneath the placid surface, the company experienced a 27% drawdown followed by a +31% rally, only to repeat the cycle with a -21% drawdown followed by a subsequent 20% rally to finish the quarter. In our view, the stock’s volatility goes beyond fundamental business drivers, but the company in turn benefitted from increasing capital spending budgets from cloud service providers and large enterprises for generative AI (“GenAI”) infrastructure spending. Simultaneously, the stock endured weakness related to the delayed next-generation Blackwell chip, and an earnings forecast that exceeded expectations, albeit not as much as some investors hoped. While we continue to believe NVIDIA is a highly advantaged business, with significant demand for their chips and servers ahead of the need for that hardware from real-world businesses, we are cautious about its growth sustainability since it lacks recurring revenue.”
