Best AI stocks for 2026

Not so long ago, the term “artificial intelligence” or AI would probably conjure images of life-like, sentient robots that were secretly plotting to replace or overthrow humankind — a notion popularised by science fiction films like The Terminator and The Matrix.

Fast forward to today, and the reality of AI is less about robots gone rogue (not yet, anyway) and more about groundbreaking technologies that are revolutionising industries. If you’re keen on investing in this rapidly growing industry, here are some of the best AI stocks that might be worth considering.

What are the best AI stocks?

This is an ever-changing space that moves at a rapid pace, and the best AI stocks of today may not be the best AI stocks of tomorrow. But to give you some starting inspiration, here are the top holdings in one of the largest AI-related investment funds around, the WisdomTree Artificial Intelligence UCITS ETF (WTAI):

The better-known AI Goliaths…

AI stock	Icon	1-year performance (to Nov. '26)	5-year performance (to Nov. '26)	Link
Broadcom (AVGO)		38.50%	731.31%	Invest Capital at risk
Micron Technology (MU)		718.52%	1,210.65%	Invest Capital at risk
NVIDIA Corporation (NVDA)		24.08%	191.56%	Invest Capital at risk
Oracle Corporation (ORCL)		-45.55%	46.23%	Invest Capital at risk
Advanced Micro Devices (AMD)		252.25%	538.18%	Invest Capital at risk
Taiwan Semiconductor Manufacturing (TSM)		77.42%	263.22%	Invest Capital at risk
ASML Holding N.V. New York Registry Shares (ASML)		115.75%	158.30%	Invest Capital at risk
Microsoft Corporation (MSFT)		-23.90%	37.11%	Invest Capital at risk
Amazon.com (AMZN)		9.34%	38.51%	Invest Capital at risk
Qualcomm (QCOM)		15.42%	27.48%	Invest Capital at risk
CoreWeave Class A (CRWV)		-43.14%	N/A	Invest Capital at risk

…and some lesser-known AI stocks

AI stock	Icon	1-year performance (to Nov. '26)	5-year performance (to Nov. '26)	Link
SoundHound AI (SOUN)		-40.80%	92.80% (3 years – 2022 IPO)	Invest Capital at risk
SK Hynix (000660)		540.87%	1,474.49%	Invest Capital at risk
Analog Devices (ADI)		63.36%	144.80%	Invest Capital at risk
Teradyne (TER)		279.69%	194.63%	Invest Capital at risk
Trimble (TRMB)		-35.10%	-40.29%	Invest Capital at risk
Microchip Technology (MCHP)		19.15%	-34.88%	Invest Capital at risk
Iveda Solutions (IVDA)		-87.80%	-99.50%	Invest Capital at risk
Skyworks Solutions (SWKS)		-22.46%	-69.92%	Invest Capital at risk
Pri0r1ty Intelligence Group PLC (PR1)		-72.73%	-91.60% (3 years)	Invest Capital at risk

What are AI stocks?

Artificial intelligence means the ability of machines, such as computers, to perform tasks and activities that would normally require human intelligence. AI stocks, then, represent companies at the forefront of this transformation.

These firms are involved either in the research, development, or application of AI. This could be companies whose entire business model revolves around AI, or those where AI constitutes only a small segment of their operations.

Types of AI stocks

Though the concept of AI is not new, the industry is still in its early stages of development. As time progresses, we’re likely to witness the emergence of more specific segments of this industry. For now, we can break down AI stocks into the following categories:

• Pure AI plays. These are companies whose main focus includes developing and providing cutting-edge AI solutions, platforms, and related services. These might be the best stocks if you want complete exposure to the AI industry. Unfortunately, at the moment, there are very few major public companies that fit this bill. One example that didn’t make it onto our best AI stocks list is C3.ai (AI).
• Partial AI businesses. These are companies that are looking to profit from AI, but it’s not their sole source of revenue. Notable examples of some of the best AI stocks that fit this include Nvidia (NVDA), Arm (ARM), Oracle (ORCL), Micron Technology (MU) and Salesforce (CRM).
• Stocks heavily investing in AI. This category includes firms that are integrating AI into their business model to fuel growth or improve efficiency. Essentially, they leverage AI as a strategic tool for gaining a competitive edge or achieving success. The segment also includes companies that are betting big on the future of AI by making speculative investments in early-stage AI companies. Examples of top stocks include the likes of Microsoft (part-owners of OpenAI), Alphabet (GOOG), Baidu, Tesla (TSLA), and Amazon (AMZN).

How to invest in AI stocks

1. Open a share dealing platform. The first step in investing in AI stocks is to open a share trading account. Choose a platform that suits your needs, whether it’s one with robust research tools, low fees, or a user-friendly interface.
2. Fund your account. Once your account is set up, deposit funds. You can do that via a bank transfer, debit card, or any other means allowed by your platform.
3. Research and choose AI stocks. Research the best AI stocks (or funds) for your portfolio, and then search for them on your chosen platform by company name or ticker symbol.
4. Buy shares. Once you’ve found the stock(s), select the amount you want to invest and create an order to buy shares. And just like that, you’re now officially an investor in the AI sector.

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Why do people want to invest in AI stocks?

Here’s a glimpse into why many investors are turning their attention toward artificial intelligence.

• Huge growth potential. The AI industry is on an explosive trajectory, fundamentally changing how we live, work, and interact. In fact, the global AI market has tripled in size in the last 4 years, surging from $108 billion in 2020 to $370 billion in 2024.
• Investment returns. Some projections are that this futuristic market could hit almost $7.4 billion by 2030. For investors, this translates to a sector ripe with opportunities for significant returns as the application of AI spreads across industries.
• Innovation’s front row. Investing in AI stocks is akin to having a backstage pass to the future. It’s a chance to be part of groundbreaking developments that could redefine or completely reshape societal norms and structures.
• Diversification. AI’s versatility means it spans numerous sectors, from finance to healthcare to automotive and many others. Investing in the best AI stocks allows for a strategic spread of investments, mitigating risks associated with market volatility in individual sectors.

Risks of AI stocks

While the visions of human-like robots taking over the world remain the object of science fiction movies and stories rather than reality for now, there are still some very real risks to investing in this industry you should be aware of:

• No guarantee of profitability. As mentioned, AI is still a relatively new industry. While it holds immense potential, there’s still no guarantee that all segments of the industry will be profitable. However, it’s also true that investing never comes with any guarantees of positive returns, regardless of the industry.
• Technological obsolescence. AI is advancing at a blistering pace. Unfortunately, that means today’s leading AI tech can quickly become outdated tomorrow. Companies that fail to continuously innovate or keep up with rapid advancements risk losing their competitive edge or becoming obsolete, which is bad news for investors.
• Regulatory risks. As AI technologies become increasingly woven into the fabric of society, they are attracting more regulatory scrutiny. Changes in regulations or concerns over privacy, data security, and the ethical use of AI can have unforeseen impacts on companies and their stock prices.

Our expert says: Will the AI industry continue to be profitable?

"It’s looking that way, but there’s no guarantees. If AI becomes commonplace, and the technology is open-source, this could make it much cheaper, devaluing companies. At the moment, AI stocks can generate high profit margins because the technology is advanced and hard to compete with.

If AI becomes a normal part of everyday life, this might actually be a negative for the profitability of AI stocks. This happened with the airline industry. Airline travel was a new technology that many were betting on. It did become a hugely important industry, but not necessarily a profitable one, running on extremely slim margins."

George Sweeney, DipFA

Deputy editor

Alternative ways to invest in AI stocks

Beyond directly buying individual stock in AI companies, there are several other ways to gain exposure to this dynamic industry.

• Exchange-traded funds (ETFs). These funds invest in a basket of different AI stocks, spreading out the risk associated with individual stocks. They offer flexibility and accessibility, as you can easily trade them on a regular stock exchange. Popular examples include the WisdomTree Artificial Intelligence UCITS ETF (WTAI) and the Legal & General Artificial Intelligence UCITS ETF (AIAG).
• Investment funds and trusts. Funds and investment trusts pool money from investors and then invest it in a diversified portfolio of assets. Some funds and assets may focus exclusively on AI assets but others include other types of investments like tech stocks. Examples of popular investment trusts holding AI stocks include Scottish Mortgage (SMT) and Polar Capital Technology (PCT).
• Index funds. Investors can also engage with the AI sector through index funds that track AI-specific indices or broader market benchmarks like the S&P 500 (with AI exposure). Index funds offer instant diversification. They also tend to have lower expenses and fees compared to actively managed funds.

Pros and cons of investing in AI stocks

Bottom line

The robots haven’t taken over, but it appears artificial intelligence is here to stay. Finding the best AI stocks to invest in presents a challenge because no one knows just yet how much of a role AI will play in the future of human civilization. Sorry for sounding philosophical.

There’s no need to worry about AI being a threat to human existence, not just yet anyway. If you want to make money with AI stocks, make sure you understand the risks and aim for companies you think will still be around in 10 or more years. This is challenging with AI technology that’s still in its infancy, but try your best.

Frequently asked questions

• Who is the leader in AI technology?

  There's no definitive leader because there are different branches and segments within the AI industry. There are leading companies across various AI sectors, but there isn't a single AI stock that dominates across the board. The AI stock best-known at the moment is probably Nvidia, but it may not remain on top.

• What is the best AI penny stock to buy?

  These are some of the most commonly referenced AI penny stocks:

  1. BigBear.ai (BBAI)
  2. Remark Holdings (MARK)
  3. Inuvo (INUV)
  4. Veritone (VERI)
  5. IZEA Worldwide (INDEX)
  6. Iveda Solutions (IVDA)

• Is AI a good investment?

  It can be, but it depends on the specific AI investment or stock you're looking at. Also, it's important to remember that past performance doesn't dictate future results. It's impossible to predict exactly what will work out to be a good investment in the future. Otherwise, we'd all be rich already.

• What impact could government regulation have on AI stocks?

  Heavy-handed regulations by national governments could put a damper on the AI boom, dragging down stock prices with it.

  The Italian government caused a stir in April 2023 by banning Microsoft’s AI-powered chatbot ChatGPT. The Italian Data Protection Authority (IDPA) said ChatGPT was not complying with the EU’s user privacy laws. The IDPA questioned the legality of using Italians’ personal data to train the AI chatbot, citing concerns about potential breaches that could expose conversations and even payment details.

  But is ChatGPT’s skirmish with the Italian government a canary in the coal mine or an isolated incident for AI as a whole? It is still early days, but the UK government is out in front, having released what it called a “world-leading” white paper in March 2023 outlining its 5 regulatory principles for AI. Those principles include words like “fairness”, “explainability” and “transparency”. The report starts out positively enough, with the title “a pro-innovation approach” and a nod to the £3.7 billion AI already contributes to the UK economy each year in Gross Value Added terms.

  Still, the report is over 40 pages in length, and it concludes with the promise of more volumes to come. Now, multiply that by the hundreds of other jurisdictions that will also pen their own AI regulations in the following years.

  Could the AI frenzy die from one million paper cuts dished out by regulators the world over? While regulators are unlikely to put a total stop to AI, they could cause headaches for tech companies. Investors should think long and hard about regulatory risks before diving into any particular AI stocks.

• Are AI stocks more volatile compared to traditional stocks?

  The price volatility of a stock can be measured using the “beta”. A stock with a beta of 1 generally moves in line with the market. If the market goes up 1%, the stock tends to go up around 1%, and if the market goes down 1%, the stock tends to go down around 1%. Any stock with a beta above 1 experiences bigger price swings than the market. Meanwhile, a beta below 1 signifies a steady Eddie stock that is less volatile than the market.

  So, where do AI stocks rank in these terms? According to a spreadsheet maintained by academics at New York University, semiconductor equipment (1.76), software/internet (1.55) and computer services (1.17) all have a beta above 1. Unfortunately, the spreadsheet doesn’t have a category that considers only AI stocks.

  Still, we can conclude that stocks in the tech sphere are riskier than the market average. Less volatile than the market are snooze-fest sectors like regional banks (0.5), grocery retailers (0.67) and telecom services (0.88).

• How do I find promising AI stocks?

  The first step would be to swat up on the hot terms that any AI investor worth their salt knows. Below, we’ve compiled a list of concepts you might see bandied about in companies’ presentations:

  • Machine Learning (ML). ML is a core technology within AI that focuses on the development of algorithms and models that can learn from data and make predictions or decisions without explicit programming. ML enables AI systems to recognise patterns, make inferences and improve performance over time.
  • Neural Networks. Neural networks, inspired by the structure of the human brain, are a fundamental component of deep learning, a subfield of ML. They consist of interconnected layers of artificial neurons that process and analyse data, enabling complex learning tasks such as image and speech recognition.
  • Natural Language Processing (NLP). NLP allows machines to understand and interpret human language. It involves techniques for processing, analysing and generating text or speech, enabling applications like language translation, sentiment analysis, chatbots and voice assistants.
  • Computer Vision. Computer vision involves teaching machines to interpret and understand visual information from images or videos. It enables AI systems to analyse and extract meaningful insights from visual data, such as object recognition, facial recognition and image classification.
  • Data Analytics. Data analytics involves the collection, processing and analysis of large volumes of data to derive valuable insights. AI systems heavily rely on data analytics to train models, make predictions and drive decision-making processes.
  • Cloud Computing. Cloud computing provides the necessary infrastructure and resources for AI development and deployment. It offers scalable computing power, storage and data processing capabilities, enabling AI systems to handle complex tasks efficiently.
  • Edge Computing. Edge computing brings AI processing closer to the data source or device, reducing latency and enabling real-time AI applications. It is particularly important for AI systems deployed in resource-constrained environments or those requiring quick response times.
  • Robotics. Robotics combines AI with physical systems, enabling machines to interact with the physical world. Robotic technologies, such as autonomous robots and robotic process automation, have significant applications across industries like manufacturing, logistics, healthcare and more.

To make sure you get accurate and helpful information, this guide has been edited by Sean LaPointe as part of our fact-checking process.

Written by

George Sweeney, DipFA

Deputy editor

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George is a deputy editor at Finder. He has previously written for The Motley Fool UK, Nasdaq, Freetrade, Investing in the Web, MoneyMagpie, Online Mortgage Advisor, Wealth, and Compare Forex Brokers. He's focused on making personal finance and investing engaging for everyone. To do this he draws from previous work and his Level 4 Diploma for Financial Advisers (DipFA), sharing what he’s learnt. When he’s not geeking out about money, you’ll find him playing sports and staying active. See full bio

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