3 AI ETFs to Harness the Power of Artificial Intelligence

If you want to get into artificial intelligence without making potentially risky bets on just one or two stocks, AI ETFs are the way to go.

Why not mutual funds? AI mutual funds simply don't exist. Thanks to less stringent requirements and regulations for ETFs, ETF providers can quickly pump out products to serve just about any emerging trend—mutual funds, not so much. The "funkiest" mutual funds you're likely to see are sector-level funds, such as technology or healthcare funds. But you can find an ETF or two for the smallest of niches. And the number of artificial intelligence ETFs already numbers in the double digits.

With all of that said, let's home in on some of the best products on the market right now. Read on as I share three picks from my broader list of the best AI ETFs.

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The AI Opportunity

I can't predict the future, but I can point out what others seem to think—and broadly speaking, other businesses seem to think AI is only going to get bigger and more entwined with numerous facets of the human experience.

I won't flood the zone with opinions. Instead, I'll provide three numbers I believe sum up the most prevailing thoughts on where AI is going:

• $15.7 trillion: "AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption-side effects." (PWC analysis)
• $2.5 trillion: "Worldwide spending on AI is forecast to total $2.52 trillion in 2026, a 44% increase year-over-year. ... Building AI foundations alone will drive a 49% increase in spending on AI-optimized servers for 2026, representing 17% of total AI spending. AI infrastructure will also add $401 billion in spending in 2026 as a result of technology providers building out AI foundations." (Gartner analysis)
• 337: "FactSet searched for the term 'AI' in the conference call transcripts of all the S&P 500 companies that conducted earnings conference calls from March 15 through June 11. Overall, the term 'AI' was cited on 337 earnings calls conducted by S&P 500 companies during this period. This number is well above the five-year average of 164 and the 10-year average of 103. In fact, this is the highest number of S&P 500 earnings calls on which 'AI' has been cited over the past 10 years (using current index constituents going back in time). The previous record over the past 10 years was 334, which occurred in the previous quarter (Q4 2025). This number also reflects 68% (337 out of 498) of the earnings calls conducted by S&P 500 companies during this period." (FactSet analysis)

And this is just a small sampling of the pro-AI estimates, forecasts, and analyses that have been sent my way in just the past few months.

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Global X Artificial Intelligence & Technology ETF

• Inception: May 11, 2018
• Assets under management: $8.9 billion
• Expense ratio: 0.68%, or $6.80 per year on every $1,000 invested

The Global X Artificial Intelligence & Technology ETF (AIQ) is the 500-pound gorilla of the artificial intelligence ETF space. It was the first to reach more than $10 billion in assets under management (AUM), and while it has less than that now, it's still roughly five times as large as the next closest broad AI ETF.

Here's how AIQ explains its "unconstrained" approach: "AI spans multiple segments, and its most innovative companies include both household names and newcomers from around the world. AIQ invests accordingly, without regard for sector or geography."

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Put differently: Global X's ETF believes AI profits will be made not just by companies that produce the technology, but also companies that adopt it. That's reflected in AIQ's tracking index, which breaks companies down into two categories, which themselves are broken down into a total of four easier-to-understand subcategories:

1. AI applied to products and services: Companies with developed internal AI capabilities and that are directly applying AI tech into their products and services. This can include image and/or language processing, threat detection, recommendation generation, and more.
2. AI-as-a-service for Big Data applications: Companies that provide AI capabilities to their customers as a service. They usually offer cloud-based platforms that let their customers apply AI techniques to big data without having to build their own capabilities.
3. AI hardware providers: Companies that produce semiconductors, memory storage and other hardware needed for AI applications.
4. Quantum computing: Companies developing quantum computing technology. This isn't highly commercialized yet, but it's expected to be a hotbed of potential in the AI space.

AIQ's index takes 60 companies from Nos. 1-2, and 25 companies from Nos. 3-4. Stocks are given an "exposure score" (effectively, the more business exposure to AI, the greater the score). All stocks with a score greater than 20% are capped at 3% of assets at each rebalancing, while all stocks with a score less than 20% are capped at 1%. (Stocks can exceed these levels if they rise in value between rebalancings.)

The resulting 84-stock portfolio is unsurprisingly thick in tech stocks, but it's not technology-exclusive. Right now, the tech sector accounts for 76% of assets, followed by communication services (12%), consumer discretionary (7%), and industrials (4%). The slim remainder is sprinkled across a few other sectors.

Names such as Micron (MU), SK Hynix (SKHY), and Samsung are the hardware providers you're used to seeing in AI conversations. Microsoft (MSFT) and Google parent Alphabet (GOOGL) enable organizations to utilize AI through their software. Components like Netflix (NFLX) and Uber Technologies (UBER) are examples of companies on the AI-application side of the equation.

And as the inclusion of SK Hynix and Samsung might suggest, AIQ isn't a strictly U.S.-based fund. It's global (read: U.S. plus international), with a roughly 75/25 split of American and foreign stocks. That international exposure includes South Korea, Taiwan, Germany, and China, among other nations.

This broad coverage of the industry has made AIQ an immensely popular fund, and deserving of a spot on any list of the best AI ETFs.

Related: Pros Cut Meta Platforms (META) Stock Targets After Q2 Miss

ARK Autonomous Technology & Robotics ETF

• Inception: Sept. 30, 2014
• Assets under management: $1.8 billion
• Expense ratio: 0.75%, or $7.50 per year on every $1,000 invested

The ARK Autonomous Technology & Robotics ETF (ARKQ) is different from many of the other AI ETFs in that it's actively managed. It was one of the first two funds to launch under Cathie Wood's innovation-minded ARK Invest firm.

ARK Autonomous Technology & Robotics holds a tight portfolio of fewer than 40 autonomous technology and robotics companies "relevant to the Fund's investment theme of disruptive innovation." These are companies that develop, produce, or enable autonomous mobility, intelligent devices, advanced battery technologies, adaptive robotics, neural networks, reusable rockets, next-gen cloud technology, and 3D printing. In selecting companies, Wood is looking for three types of companies: "automation transformation," "energy transformation," and "artificial intelligence."

Put differently: ARKQ absolutely provides AI exposure, but AI isn't explicitly the point.

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While technology accounts for a third of assets, it's not even the biggest sector by weight—the industrial sector is, at more than 40%. There's also a healthy helping of consumer discretionary (17%) and a decent amount of communication services (6%), with sprinklings across energy and healthcare. ARKQ also leans a little smaller in company size than other funds on this list. Roughly 55% of assets are invested in large caps, with another 20% in mid-caps and 25% dedicated to smalls.

The most important aspect of ARKQ is that it's actively managed. While Wood is bound by a theme, there's not much else constraining her. And she's more than happy to concentrate weights in her favorite bets. That aggression can cut both ways, performance-wise.

Right now, for instance, the two largest holdings are Elon Musk's Tesla (TSLA) and Space Exploration Technologies (SPCX) ... and that has been a serious detriment of late. All of the funds on this list have struggled since our last update a couple months ago, but ARKQ has been the worst, declining by more than 20%.

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Invesco AI and Next Gen Software ETF

• Inception: June 23, 2005
• Assets under management: $1.1 billion
• Expense ratio: 0.56%, or $5.60 per year on every $1,000 invested

The Invesco AI and Next Gen Software ETF (IGPT) boasts an inception of 2005, which makes it more than two decades old ... but don't congratulate Invesco for unparalleled prescience. This AI ETF has only existed in its current form since Aug. 28, 2023, when the fund provider changed its name and ticker from "Invesco Dynamic Software ETF (PSJ)."

Do, however, congratulate the marketing department for a smart pivot.

Anyways, IGPT is another broad-AI-industry fund that works similarly to the aforementioned AIQ, but without any requirements that are explicitly tied to artificial intelligence. Instead, IGPT's tracking index, the STOXX World AC NexGen Software Development Index, requires a baseline amount of exposure to (specifically, at least 50% of revenues from one or more) subsectors "associated with future software development." So while it includes areas like AI and robotics, it's not limited to them.

Related: 5 Best Energy ETFs for the Rise of Oil, Natural Gas + More

Invesco AI and Next Gen Software ETF is another global fund, though it has a pretty low international exposure at just 15% of assets right now. It's also thick in large caps, which account for 80% of the portfolio. And it frequently boasts higher single-stock concentrations than many of the funds on this list; five holdings, including Meta Platforms (META) and Alphabet, account for 7% to 10% of assets each. AIQ's two largest holdings (SK Hynix and Micron) top out just above 5%.

This is because IGPT factors both revenue exposure and market capitalization when weighing stocks. It caps constituents at 8% between rebalancings, but that's still an enormous difference—one that means IGPT's returns are far more beholden to the AI industry's mega-caps than similar funds. Good news: That could provide more stability in flat and down markets. Bad news: That could mean a little less upside in up markets.

Invesco's AI ETF is also economically priced. At 56 basis points in fees, it's not the absolute cheapest broad-spectrum AI play on this list, but it's one of the least expensive. (A basis point is one one-hundredth of a percentage point.)

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