3 Great AI Stocks to Own in 2024

2024 is expected to be a landmark year for investors looking at the artificial intelligence (AI) sector. Now is the time to prepare your portfolio for the new year, and you don’t have to do it alone.

Three Motley Fool contributors put their heads together to come up with the best AI investments for the new year.

In the resulting discussion, you’ll discover three standout AI stocks with prospects to outperform the market in 2024 and beyond. international business machine (IBM -0.12%) We have made a strategic shift towards AI and cloud computing. nvidia (NVDA) A pioneer in professional hardware and generative AI systems. ASML Holdings (ASML -0.12%) It forms the backbone of AI chip manufacturing.

These companies not only represent the pinnacle of AI innovation, but also offer unique investment opportunities.

Don’t Underestimate the Brilliance of This AI Pioneer

Nicolas Rosolillo (NVIDIA): It might sound like a “too easy” choice or an overrated one, but after Nvidia’s last earnings update, there may be plenty of room for the generative AI systems pioneer to climb even higher in the new year. how?

During its third quarter fiscal 2024 earnings call (for the period ending October 2023), revenue surged 206% from the previous year to $18.1 billion, driven by its data center segment (where the majority of generative AI chip and system sales come from). registered). Surprisingly, another sequential increase is expected in the fourth quarter, with management forecasting $20 billion in revenue.

But here’s where things get interesting and the debate begins (as Anders, Billy and I wrote about a few months ago). CEO Jensen Huang and his top team have made it clear that they expect data center sales (80% of revenue). (total revenue last quarter) will continue to grow in 2024 as more supply of AI chips enters the market to meet insatiable demand. The market appears to be moving around this. The consensus among Wall Street analysts for next year’s revenue is pegged at nearly $91 billion, which would represent an increase of more than 50%.

However, semiconductor sales tend to be cyclical. A surge in profits is often followed by a slump. Now all eyes are on what will happen in 2025. But for reference, in the last earnings call, Huang said, “We absolutely believe that data centers can grow by 2025.”

Of course, the jury is still out on this one. At some point, it is expected that the world will take a break from building new AI computing infrastructure. Perhaps it may finally arrive in 2025, or it may be delayed until 2026 or later.

But if Huang is right, and the roughly $1 trillion global AI data center opportunity continues to expand unabated over the next few years, Nvidia looks like a reasonably valued semiconductor stock. The stock trades at 25 times expected earnings per share for next year (2024). With another busy year coming up, I have no plans to sell my position in Nvidia just yet.

Now is the time to dive into Big Blue’s AI waters.

Anders Weiland (IBM): The IBM you see today is miles away from the one-stop IT shop of the turn of the millennium. In a sharp and painful strategy shift that began in 2012 and never ended, Big Blue refocused its vast assets on the high-growth “strategic imperatives” of cloud computing, data security, analytics and AI.

The watsonx.ai platform is a development platform tailor-made for enterprise-scale businesses looking for machine learning and generative AI tools. It includes support for generative AI in the app creation environment and the option to create apps in a drag-and-drop graphical interface rather than manual coding, and draws on IBM’s decades of AI research.

And the company isn’t resting on its digital laurels. The company has $11 billion in cash equivalents and generated $10.3 billion in free cash flow over the last four quarters. And that money is targeting AI opportunities right now.

For example, IBM recently committed to collaborating with universities around the world to train 2 million AI experts over the next three years. It also launched a $500 million investment fund focused on innovative AI startups.

As a result, IBM is poised to make up for the difficulties of its strategy shift with strong profits over the next few years. Trading at 2.4 times trailing sales and 12.3 times free cash flow, IBM’s stock seems like a no-brainer buy today.

But market makers seem to have forgotten the huge shadow IBM casts over the AI ​​opportunity. The stock price will rise only 16% in 2023. S&P 500 Index increased by 25%.

I’m not trying to throw a market leader like Nvidia under the bus, and I own its stock. However, the chip designer’s stock price is trading at 27 times sales and 70 times free cash flow. If you’re looking for a strong AI investment on the doorstep of 2024, IBM combines fantastic growth prospects and an outstanding AI history with a cheap stock price.

This essential AI stock has lagged its peers this year, but could soar in 2024.

Billy Duberstein (ASML Holdings): Artificial intelligence stocks have risen a lot this year, so there isn’t much discount left. But at least by comparison, ASML Holdings has underperformed compared to many AI stocks, up “only” 38%, despite its machines being essential to the AI ​​chip manufacturing process. The stock also remains about 15% below the all-time high it set in late 2021, while many other semiconductor and AI stocks are now above their previous highs.

ASML data from YCharts.

There are several reasons for this year’s poor performance. First, ASML is a European stock, so the relative performance of each market may have some influence. Second, ASML was traded at a relatively high valuation compared to other semiconductor equipment companies this year. So there wasn’t much ground to “make up” after the sector’s plunge in 2022. Even now, ASML trades at 35 times earnings.

Moreover, ASML management has already stated that the company will not see significant growth in 2024. This may be surprising, as most other semiconductor companies reported poor performance in 2023 and are now expecting a recovery year in 2024. But ASML’s growth was a little different. . During the pandemic, ASML’s extreme ultraviolet (EUV) and deep ultraviolet (DUV) lithography machines were in such high demand and so complex and expensive to manufacture that they caused a production bottleneck until this year. So while many other semiconductor equipment companies have seen a decline in revenue in 2023, ASML is actually expected to see its 2023 revenue increase by about 30%. We will have to endure the effects of the post-pandemic recession only next year, in 2024.

However, since chip inventory tends to be about a year ahead, ASML may outperform some of its peers in 2025. Management predicted that this would be a big year of growth, with several new cutting-edge fabs coming online using ASML’s latest EUV. machine. In fact, ASML has just shipped the first parts of its first high numerical aperture (NA) EUV equipment, the latest and most advanced model of EUV. intel. High NA machines are so huge that they have to be shipped in 250 separate boxes! The first batches are currently being shipped, but production using them probably won’t occur until late 2025.

ASML stock isn’t cheap, but it has a monopoly on the EUV technology needed to make sub-7nm chips, which the industry surpassed years ago. Last year, cutting-edge chips like the Nvidia H100 were manufactured on the 5nm node, and the first 3nm chips will be produced in 2023.

However, the first 2nm chips are not scheduled to be produced until 2025, the node at which Samsung and Intel hope to catch up with foundry leaders. Taiwan Semiconductor Manufacturing On state-of-the-art logic chips. Intense competition for the 2nm node means all of these companies will be purchasing a lot of ASML’s machines to make that dream a reality.

The story does not end here, as all major dynamic random access memory (DRAM) manufacturers will also start making DRAM chips using EUV in the future. Samsung started using EUV two years ago, but will still use it in 2025. micron It is the last memory holdout to use complex processes and begins using EUV for memory production for the first time.

Generative AI will rely heavily on advanced processors and high-bandwidth memory, so ASML is expected to outperform its peers in 2024 after falling behind in 2023.