Computers excel at crunching numbers but struggle with tasks that many people do with ease, like language processing, visual perception, object manipulation, reasoning, planning, and learning. Artificial intelligence (AI), including its offshoots of deep learning and machine learning, uses computers to perform tasks that typically require human intelligence, such as language generation and facial recognition.
AI stocks are publicly traded companies that develop or employ AI technology as part of their business. AI stocks span sectors such as semiconductors, software, and robotics, going beyond conventional technology and representing companies that are using AI in ways that set them apart from their peers.
How do companies use artificial intelligence?
Companies use AI in a number of ways. Those include:
- Machine learning: Training a machine using vast amounts of data so it can make inferences from data it hasn't seen.
- Robotics: Machines that can move and act without human intervention.
- Generative AI: Creating text, images, and video, typically in response to a prompt from a human.
- Autonomous vehicles: Cars that can drive without human assistance.
- Neural networks: A kind of AI that attempts to mimic the human brain. It's a fundamental technology for AI skills like natural language processing, image recognition, and predictive analytics, and it also forms the basis of deep learning.
- Agentic AI: Agents based on artificial intelligence that can carry out work tasks such as customer service without being prompted.
AI is a growth business
According to International Data Corporation, the global artificial intelligence market is expected to grow from $235 billion in 2024 to more than $631 billion in 2028. While the AI market is already large and continues to grow rapidly, plenty of companies can still profit from AI. As shown in The Motley Fool's 2026 AI Investor Outlook Report, investors remain bullish on AI stocks. Although picking stocks in a growth industry comes with a lot of uncertainty, these top AI stocks are all worth considering.
Seven AI stocks to buy in 2025
| Name and ticker | Market cap | Dividend yield | Industry |
|---|---|---|---|
| Nvidia (NASDAQ:NVDA) | $4.3 trillion | 0.02% | Semiconductors and Semiconductor Equipment |
| Alphabet (NASDAQ:GOOG) | $3.7 trillion | 0.27% | Interactive Media and Services |
| Alphabet (NASDAQ:GOOGL) | $3.7 trillion | 0.27% | Interactive Media and Services |
| Microsoft (NASDAQ:MSFT) | $3.6 trillion | 0.71% | Software |
| CoreWeave (NASDAQ:CRWV) | $39.2 billion | 0.00% | IT Services |
| Meta Platforms (NASDAQ:META) | $1.6 trillion | 0.32% | Interactive Media and Services |
| Adobe (NASDAQ:ADBE) | $149.2 billion | 0.00% | Software |
| Alibaba Group (NYSE:BABA) | $349.6 billion | 0.67% | Multiline Retail |
1. Nvidia
NASDAQ: NVDA
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Leading graphics processing unit (GPU) company Nvidia (NVDA -3.30%) has taken advantage of the AI boom, with its GPUs becoming the de facto standard in data centers worldwide. Generative AI's training phase demands a lot of computing power. The phase that follows, the inference phase, typically requires less.
GPU chips, which were once used primarily for rendering video games, support both phases well. Nvidia's ambitions have gone beyond GPUs; the company now aims to build AI factories or data centers full of Nvidia components to run AI applications and programming, and its business has grown by multiples since the launch of ChatGPT.
Nvidia's data center business makes up the vast majority of the company's revenue, thanks to the emergence of generative AI. Because it sells the building blocks for AI infrastructure, Nvidia became the first major company to see a significant revenue boost from AI.
Revenue has surged since 2023, and the stock has soared as well. It's been the most valuable company in the world on several occasions and was No. 1 in December 2025. It also became the first company to reach a market cap of $5 trillion. In 2024, full-year revenue jumped 114% to $130.5 billion, driven by the surge in data center demand. Growth has been strong in 2025, as well.
Nvidia's chips are popular for running demanding workloads that applications like large language models (LLMs) require. The pure-play chip stock is now selling its new Blackwell platform, which major cloud infrastructure services have deployed in 2025, and demand is outstripping supply. Its next iteration, the Rubin platform, is expected to become available in the second half of 2026.
Self-driving cars and "physical AI" are other areas of focus. Nvidia develops hardware and software platforms that can power driver-assistance features and fully autonomous driving, which could be a significant source of revenue if that industry takes off. Automotive revenue accounts for only a small fraction of the company's revenue, but that could change.
With Tesla (TSLA +2.57%) having launched its robotaxi network in Austin and the Bay Area, the autonomous vehicle race appears to be heating up, which should be good news for the semiconductor sector.
A self-driving car must process massive amounts of data from multiple sensors and cameras in real time, detect objects such as pedestrians and other vehicles, and make complex decisions. They require tremendous computing power, exactly what Nvidia's platform delivers.
Its professional visualization segment, which includes its Omniverse, also has potential in AI. Nvidia's chipsets could someday be supplanted by more specialized processors designed for AI, but the company is in an enviable position for now.
2. Alphabet
NASDAQ: GOOGL
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NASDAQ: MSFT
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NASDAQ: CRWV
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NASDAQ: META
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6. Adobe
NASDAQ: ADBE
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NYSE: BABA
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Tesla is best known for its electric vehicles (EVs). CEO Elon Musk sees AI as the future of the company. Machine learning and neural networks are very much at the center of the company's autonomous vehicle and Optimus autonomous robot projects.
Tesla introduced its driverless Cybercab in October 2024, and the company hopes to begin producing the vehicles by 2026. It launched its robotaxi network in June, though with just a handful of vehicles, and Musk envisions an expansion to more cities in the near future. Musk has said Tesla's automation technology could make it the most valuable company in the world.
Deep learning stocks
Deep learning is a subset of machine learning that uses artificial neural networks inspired by the human brain. It's the most advanced kind of AI and is crucial in technologies such as self-driving cars. Deep learning is advancing in areas such as preventive healthcare, where predictive algorithms are necessary. It differs from machine learning in that it doesn't require human input.
Nvidia is among the companies closely associated with deep learning. Its GPU chips use deep learning to power data centers and enable autonomous driving and cloud computing, among other functions.
Alphabet has exposure to deep learning through a number of its businesses, including its autonomous vehicle start-up, Waymo. It also owns DeepMind, a deep learning platform that can diagnose eye diseases, predict the shapes of proteins, and accelerate the scientific discovery process.
How to invest in AI stocks
- Open your brokerage app: Log in to your brokerage account where you handle your investments.
- Search for the stock: Enter the ticker or company name into the search bar to bring up the stock's trading page.
- Decide how many shares to buy: Consider your investment goals and how much of your portfolio you want to allocate to this stock.
- Select order type: Choose between a market order to buy at the current price or a limit order to specify the maximum price you're willing to pay.
- Submit your order: Confirm the details and submit your buy order.
- Review your purchase: Check your portfolio to ensure your order was filled as expected and adjust your investment strategy accordingly.
Pros and cons of investing in AI stocks
Investing in AI stocks has gotten popular given the growth in the sector. Let's take a look at the pros and cons related to these stocks.
Pros:
- There's a lot of growth potential.
- Momentum is building.
- Valuations still look reasonable.
- The technology could be as disruptive as the internet.
Cons:
- A bubble could be forming in AI.
- It's unclear whether the capex spending is justified.
- AI stocks are getting riskier as they grow more expensive.
- Most new technologies experience a crash at some point.
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