The sell-off might make Nvidia stock attractive, but these stocks present even greater opportunities.
It’s been a rough couple of months for artificial intelligence (AI) stocks.
In January, China’s DeepSeek AI sparked a sell-off in chipmakers after sharing breakthroughs in developing a more efficient large language model that doesn’t rely as heavily on compute power.
The sell-off accelerated after Nvidia (NVDA 3.16%) reported financial results that failed to impress investors and meet high expectations.
That was exacerbated in February by the Trump administration’s trade policies toward China, Mexico, and Canada. Many expect Taiwan, where Nvidia and other chipmakers manufacture their products, is on the president’s short list for future tariffs.
The result is Nvidia stock now trades more than 20% below its high from the start of the year as of this writing. And many investors may be thinking it’s a great opportunity to snatch up shares of the AI leader. But Nvidia wasn’t the only stock that saw its price drop during the sell-off, and there are many other stocks that present even more attractive opportunities.
Here are three stocks you can’t afford to ignore right now.
Image source: Getty Images.
1. Micron Technology
Investors who are bullish on the long-term potential of Nvidia to keep selling more of its high-end GPUs to hyperscale cloud customers should take a closer look at Micron Technology (MU 2.32%). Micron supplies a key component of Nvidia’s chips: high-bandwidth memory (HBM).
Memory, not the actual compute power, is often the bottleneck in training large language models. The problem will only increase as the number of parameters in newer LLMs increases. Newer reasoning models also require more memory capacity and more efficient access to that memory.
Thus advances in memory chips can have a significant value add for the hyperscalers. Micron is one of the leading memory chipmakers in the market, supplying Nvidia as well as other chipmakers with its latest generation of HBM chips.
Memory is also an important component for inference. Greater memory capacity produces faster responses and allows AI systems to maintain larger context windows. As technology moves toward on-device AI, personal device makers will need to increase their demand for memory.
There are a few important risks to consider with Micron, though.
First, it’s hard to establish a meaningful competitive advantage in memory chips. The component is easily swapped for competing chips in data centers and consumer devices. That’s what enabled Micron to win its position with Nvidia and others in recent years from companies with much larger operations. However, it means Micron needs to continue to invest in research and development to ensure it maintains its technology lead.
The second risk stems from Micron being a vertically integrated chipmaker. Unlike many chipmakers today, Micron manufactures its memory chips itself. That means that it gets to keep a larger share of the economics when demand is high, but it also means it takes more of the downside when demand drops. That makes the stock highly cyclical.
With that in mind, Micron shares trade for an attractive price as of this writing. With a forward P/E of just 15, shares trade at very low valuation. However, Micron shares often look cheap at the peak of its cycle.
But with continued demand for memory chips thanks to growing usage of artificial intelligence, this cycle may extend quite a bit longer. Analysts currently expect earnings per share to grow 62.5% in fiscal 2026, on top of its massive 429% jump this year.
Micron’s price-to-sales ratio of about 4 is roughly in line with its average over the last five years, indicating the shares trade at fair value with strong upside from growing demand for memory chips.
2. Oracle
Oracle (ORCL 1.81%) has long been a leader in database systems and enterprise software. With the rise of big data and artificial intelligence, the company’s database software has become essential for many enterprises. And Oracle has adeptly shifted to supporting cloud computing platforms over the years as enterprises migrate from on-premise equipment to remote servers.
Oracle has moved to support all three major public cloud computing platforms with its database management software and the company is seeing strong growth across the various cloud computing companies. Management said revenue for Database MultiCloud grew 92% sequentially in the third quarter.
On top of that, Oracle has positioned its own cloud computing infrastructure as a great alternative or supplement to the big three public cloud providers. Oracle Cloud Infrastructure has emerged as the main growth driver of the business over the last three years, exhibiting accelerating growth as it scales.
There’s strong demand for AI infrastructure, which is seen in the company’s growing remaining performance obligations of $130 billion as of the end of last quarter. That’s up 63% from last year. Management plans to double its data center capacity in 2025 to meet that demand.
Oracle benefits from high switching costs for its database software and tight integration of that software with its cloud infrastructure. While the company has many competitors in the market, it’s a proven leader in security and stability. A database outage can have a huge impact on an enterprise, and few companies are going to take the risk of migrating systems from Oracle to another provider.
After the recent sell-off, Oracle stock trades for 25 times forward earnings estimates. With strong revenue growth coming down the pipeline as indicated by its growing remaining performance obligations and the potential for margin expansion as it scales its cloud computing business, that’s a great price to pay for the stock.
3. Meta Platforms
Meta Platforms (META 3.91%) might be the biggest single spender when it comes to building artificial intelligence infrastructure and developing new models. The big cloud computing companies might spend more on infrastructure, but a large portion of that goes toward servicing other customers. Meta’s spending all goes toward servicing its own needs, and it plans to spend as much as $65 billion on capital expenditures this year.
There’s a good reason Meta’s spending so much on AI. It’s at the core of practically everything it does. Artificial intelligence is responsible for curating the feeds in Instagram and Facebook and more recently its Reels product. It optimizes ad placements and determines who sees what ads and when they see them, increasing how much marketers are willing to pay per ad.
Importantly, Meta has found its results improve as it spends more on building larger more general models. It took its recommendation engine from Reels and applied a broader algorithm for its feeds and saw improved engagement. And as it generalizes the model even further, it’s seeing even better results across advertising and Stories. The result is more users seeing more ads and marketers paying more for each ad impression.
What’s more, it’s seeing excellent progress with generative AI. more than 4 million marketers use its generative AI tools for developing ad campaigns. Generative AI has the power to completely transform Meta’s advertising business. CEO Mark Zuckerberg sees a future in which an AI agent will be able to develop, run, and optimize an entire campaign for a marketer with just a couple of inputs.
Generative AI could play a crucial role in increasing the monetization of Meta’s messaging apps as well, thanks to more powerful chatbots. More businesses could use Meta’s platform to develop customer service and sales chatbots that could increase sales and customer satisfaction at minimal costs. William Blair analyst Ralph Schackart believes that’s a $100 billion opportunity in and of itself.
Meta’s stock was hit hard amid the recent sell-off. Shares were recently trading for just 23 times forward earnings. While its massive investments in data centers will weigh on its earnings growth in the near term, the long-term opportunity from AI is absolutely massive for Meta, and that might not be fully reflected in the current stock price.
