“The heart and lungs of the AI revolution will be in software,” said Daniel Ives, Global Head of Technology Research at Wedbush, in a February 10 interview with CNBC.

While artificial intelligence (AI) has become a broad investment theme across semiconductors, cloud infrastructure, and enterprise software, machine learning remains the core technology enabling many of these advancements. In this article, we focus on companies with meaningful exposure to machine learning applications and AI-driven revenue opportunities.

In the interview, Ives noted that while much of the current focus is on data centers and GPUs, the real long-term opportunity lies in software applications. He pushed back against investors who think companies like Salesforce and ServiceNow are structurally broken, calling skepticism about software’s central role in AI “one of the most disconnected market calls” he has seen in his career.

According to Ives, although these stocks have struggled recently, their deep integration within large enterprises gives them a strong position to benefit from AI over the next 6 to 18 months. He believes the market is not fully pricing in the potential for significant new revenue streams driven by AI use cases. On the long-term opportunity for these stocks, Ives said:

”When I look at the revenue for a ServiceNow or Salesforce, I could argue there’s 20%, 30% incremental revenue from where they are today. We’re talking ultimately tens of billions of dollars when it comes to Salesforce that are not factored into the valuation. Because I get in the near term, it’s a headwind. But to say that Salesforce and ServiceNow, given how integrated they are in enterprises, in the stack, you look at the hundreds of thousands of customers as these use cases play. You haven’t seen it today, but in the next 6, 9, 12, 18 months, I think what Jensen (Huang) talked about is exactly right. You cannot paint all of them with the same brush.”

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Meanwhile, the AI juggernaut has continued unabated. On February 9, NVIDIA CEO Jensen Huang joined CNBC to discuss AI and said demand for AI infrastructure remains “sky high,” describing the current era as a once-in-a-generation infrastructure buildout. He reiterated the long-term case for AI and the scale of spending required:

”Artificial intelligence is going to fundamentally change how we compute everything — everything from database processing, the way we do search, the way we do recommender systems when you shop, the way you watch movies, and of course these new systems that are being developed and evolved.”

With that backdrop, let’s explore our selection of the best machine learning stocks to buy according to analysts.

Our Methodology

To identify the best machine learning (ML) stocks to buy according to analysts, we first compiled a list of U.S. stocks with a market capitalization of at least $2 billion. From this universe, we focused on companies where ML is a core driver of product differentiation and monetization, or platform and infrastructure leaders that enable ML deployment at scale. From this refined list, we identified the top 11 stocks with at least 20% upside and ranked them in ascending order. Additionally, we have included data on the number of hedge funds holding stakes in these companies as of Q3 2025 to provide further insight into investor interest.

Why are we interested in the 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 427.7% since May 2014, beating its benchmark by 264 percentage points (see more details here).

Note: All pricing data is as of market close on February 10, 2026.

11. NVIDIA Corporation (NASDAQ:NVDA)

Potential Upside: 32.6%

Number of Hedge Fund Holders: 234

NVIDIA Corporation (NASDAQ:NVDA) is among the best machine learning stocks to buy according to analysts. As NVIDIA and OpenAI sit at the core of the AI ecosystem, any deal between the two is likely to have a broad industry impact. That is why the recent news flow about NVIDIA’s investments in OpenAI has been discussed keenly, given its second-order effects.

On Wednesday, February 4, Bloomberg reported that talks between NVIDIA Corporation (NASDAQ:NVDA) and OpenAI are nearing completion of a $20 billion investment from NVIDIA. The report cites people close to the matter, although both companies have declined to comment to Bloomberg. This development was previously reported by The Financial Times.

Bloomberg had earlier reported that OpenAI is targeting $100 billion in new funding, and Amazon.com and SoftBank have already discussed investing up to $50 billion and $30 billion, respectively. It should be noted that NVIDIA discussed an up to $100 billion investment in the company in September 2025, which hasn’t yet materialized and has again taken the center stage, as The Wall Street Journal recently reported that the investments have been paused. But on February 3, during a discussion in Taipei, CEO Jensen Huang said that the investment was “never a commitment”:

”We never said we would invest $100B in one round. They invited us to invest up to $100 billion, and of course, we were very happy and honored that they invited us, but we will invest one step at a time.”

NVIDIA Corporation (NASDAQ:NVDA) is a fabless semiconductor and AI computing company that designs GPUs, AI accelerators, Application Programming Interfaces (APIs), and system-on-a-chip units. Through its CUDA ecosystem, the company enables industries ranging from autonomous vehicles to scientific research by advancing AI, accelerated computing, and data center infrastructure.

Through innovation over the years, NVIDIA has become central to machine learning, as its GPUs are the standard hardware for training and running AI models.

10. Dynatrace Inc. (NYSE:DT)

Potential Upside: 35.9%

Number of Hedge Fund Holders: 40

Dynatrace Inc. (NYSE:DT) is among the best machine learning stocks to buy according to analysts. Following the company’s Q3 2026 results (FY ends in March), DA Davidson analyst Gil Luria cut DT’s price target from $65 to $50 but reaffirmed his Buy rating, according to a February 10 report by The Fly. The analyst said the company’s quarterly results were strong and that, due to end-to-end observability deals, it reported better-than-expected net new annual recurring revenue (ARR).

Luria also appeared impressed by Dynatrace Inc.’s (NYSE:DT) log management product and go-to-market changes, which, in his view, are not only helping the company gain market share but also driving strong pipeline growth.

On February 9, Dynatrace Inc. (NYSE:DT) reported an 18% growth in its Q3 revenue of $515 million, driven by $493 million (+18% year over year) in Subscription revenue. While total ARR grew 20% to $1.97 billion, the adjusted EPS came in at $0.44, ahead of the consensus at $0.41. Encouragingly, the company’s execution remains strong: it closed 12 deals exceeding $1 million in ARR in the quarter and announced a new $1 billion share repurchase program after nearly completing its earlier $500 million program.

On the results, Rick McConnell, CEO of Dynatrace, highlighted the company’s increasing traction with enterprises and stated:

”Our third quarter results surpassed the high end of our guidance across all top-line growth and profitability metrics. Notably, we’ve generated double-digit net new ARR growth for three consecutive quarters, which reflects the growing number of enterprises adopting Dynatrace as their end-to-end observability platform.”

Dynatrace Inc. (NYSE:DT) is a U.S.-based software company that provides AI-powered observability, application performance monitoring, and security solutions. The company employs machine learning to automatically monitor applications, networks, and cloud systems.