Methodology

For this list of AI ETFs, we considered funds that provide direct or substantial exposure to companies involved in artificial intelligence, including AI infrastructure, semiconductors, software, data and generative AI.

The selection emphasized several factors:

• AI exposure. The fund should have a clearly defined connection to artificial intelligence or technologies supporting AI development and deployment.
• Portfolio diversification. We considered the number of holdings and exposure across different portions of the AI value chain.
• Fund structure. Both index-based and actively managed ETFs were considered.
• Expense ratio. Lower ongoing costs can help preserve long-term returns, although fees should be evaluated alongside a fund's strategy and exposure.
• Assets and liquidity. Larger asset bases and trading activity can be useful considerations when evaluating an ETF.
• Global exposure. International holdings can provide access to companies outside the United States that are important to the AI supply chain.
• Investment approach. We considered whether a fund emphasizes AI broadly, generative AI, infrastructure, software or a combination of these areas.

This is not a ranking based on expected future returns. ETF holdings, assets, fees and investment strategies can change.

Common Questions About ETFs

What are AI ETFs?

AI ETFs are exchange-traded funds that invest in companies expected to benefit from the development, deployment or adoption of artificial intelligence.

Depending on the strategy, an AI ETF may own semiconductor manufacturers, chip designers, cloud-computing providers, data-center companies, software developers, cybersecurity businesses, robotics companies or other businesses connected to AI.

The term "AI ETF" therefore covers a broad range of investment strategies. Morningstar's 2026 analysis identified dozens of funds associated with the AI theme and noted that they can have significantly different portfolios and performance characteristics. 

Related: Best ETFs to Buy Now

Types of AI ETFs?

AI ETFs can generally be divided into several categories based on where they seek exposure in the AI ecosystem.

Hardware & Semiconductor Bedrocks

Semiconductors are fundamental to AI because training and running sophisticated AI models requires large amounts of computing power.

Companies such as NVIDIA, Advanced Micro Devices, Broadcom, Micron Technology and Taiwan Semiconductor Manufacturing can therefore appear prominently in AI ETFs. Some funds focus heavily on these businesses, while others combine them with software and application companies.

Generative AI & Large Language Model (LLM) Software

Generative AI ETFs focus more directly on companies involved in large language models, AI applications, cloud platforms and software.

These funds may hold companies such as Alphabet, Microsoft, Amazon.com and other businesses developing or deploying AI models and services.

CHAT is an example of an ETF with a particularly strong focus on generative AI and related technologies.

Data Center Utilities & The AI Power Surge

AI investment is not limited to technology companies. Data centers require substantial amounts of electricity, creating potential opportunities and challenges for utilities, power producers, grid operators and infrastructure companies.

The IEA’s 2025 Energy and AI report estimated that electricity consumption from data centers worldwide could more than double between 2024 and 2030 under its base case. 

As a result, investors may find AI exposure indirectly through ETFs focused on utilities, energy infrastructure, power equipment, data centers or related infrastructure rather than through traditional AI-themed funds.

What is the difference between a broad tech ETF and a dedicated AI ETF?

A broad technology ETF generally owns companies classified within the technology sector or a broad technology-related investment universe. A dedicated AI ETF typically uses a more specific methodology designed to identify companies connected to artificial intelligence.

That distinction can produce significant differences in portfolio composition.

For example, a broad technology ETF may have substantial exposure to established software, hardware and technology companies even when AI represents only one part of their businesses. A dedicated AI ETF may instead emphasize semiconductor manufacturers, data infrastructure, AI software or other companies considered central to the AI theme.

Investors should examine the actual holdings rather than relying solely on an ETF's name.

Related: Best AI Stocks to Buy Now

Benefits of Buying AI ETFs

Diversification. An AI ETF can spread an investment across dozens of companies instead of relying on one stock.

Targeted exposure. Investors can obtain exposure to a specific theme without researching every individual company.

Access to the AI supply chain. ETFs can hold chipmakers, cloud providers, software companies, networking businesses and other beneficiaries at the same time.

Convenience. ETFs trade throughout the day like stocks and can be purchased through most brokerage accounts.

Professional portfolio construction. Index ETFs follow predefined rules, while actively managed funds have professional portfolio managers making security-selection decisions.

Risks of Buying AI ETFs

AI ETFs carry many of the same risks as other equity investments, but thematic concentration can magnify them.

Concentration risk. Several AI ETFs hold substantial positions in the same large semiconductor and technology companies.

Valuation risk. Expectations for rapid AI growth can result in high valuations, leaving stocks vulnerable if earnings or growth fail to meet expectations.

Technology risk. Rapid technological changes can alter which companies benefit from AI.

Competition risk. Companies may spend heavily on AI while competing aggressively for customers and market share.

Regulatory risk. New laws governing AI, data privacy, copyright and semiconductor exports could affect companies in the sector.

Infrastructure risk. AI development depends on semiconductor supply, electricity, data centers and networking capacity.

Thematic volatility. Morningstar has found considerably wider performance dispersion among AI-themed ETFs than among broad large-cap funds. 

How Do AI ETF Taxes Work?

For U.S. investors in taxable brokerage accounts, AI ETFs can generate taxable dividends and capital-gain distributions, in addition to capital gains or losses when ETF shares are sold.

The IRS says regulated investment companies, including ETFs, may distribute capital gains to shareholders. Capital-gain distributions are generally reported as long-term capital gains, regardless of how long the investor owned the ETF.

Dividend income and other distributions are generally reported to investors on Form 1099-DIV. Reinvesting a distribution does not generally eliminate the tax obligation; the IRS notes that reinvested dividends are still reported as income.

The tax treatment can vary based on the type of distribution, the investor's tax situation and whether the ETF is held in a taxable account or a tax-advantaged account. Investors should consult a qualified tax professional for advice about their circumstances.

How to Choose AI ETFs

Investors evaluating AI ETFs should look beyond recent performance. The fund's strategy, holdings, expenses, concentration, liquidity and risk profile can all affect its suitability.

What is the Risk Rating of Thematic AI Funds Compared to the S&P 500?

Thematic AI ETFs generally carry more concentration risk than a broad S&P 500 ETF because they deliberately focus on a narrower group of companies and industries.

ARTY, for example, had a three-year standard deviation of 31.94% and a three-year equity beta of 1.95 as of July 31, 2026. These three-year figures span the August 2024 index change and therefore do not reflect the current strategy alone. 

These figures should not be treated as permanent risk ratings. Volatility can change as holdings, valuations and market conditions change.

A broad S&P 500 ETF can also have significant AI exposure because major technology companies and semiconductor stocks are already members of the index. Morningstar notes that investors may already have considerable AI exposure through broad-market holdings. 

Are AI Funds Market-Cap Weighted or Equal-Weighted?

There is no single weighting methodology for AI ETFs.

Some funds use market capitalization, while others use modified market-cap weighting, equal weighting, factor-based systems or active management.

AIQ, for example, tracks an index, while BAI is actively managed. ARTY tracks the Morningstar Global Artificial Intelligence Select Index, and WTAI tracks the WisdomTree Artificial Intelligence & Innovation Index. 

Investors should review an ETF's methodology to understand how positions are selected and weighted.

How Much of My Portfolio Should I Allocate to an AI ETF?

There is no universal allocation that applies to every investor.

The appropriate allocation depends on factors such as investment objectives, time horizon, risk tolerance, existing technology exposure and overall diversification.

Investors should also consider overlap. A portfolio containing an S&P 500 ETF, a Nasdaq-100 ETF and an AI ETF may have substantially more exposure to the same large technology companies than the number of funds suggests.

Because AI ETFs are thematic funds, investors may want to treat them as a satellite allocation around a diversified core portfolio rather than assuming that an AI ETF alone provides broad-market diversification.

How to Buy AI ETFs

Buying an AI ETF is generally similar to buying a stock.

1. Open a brokerage account.
2. Research the ETF's strategy, holdings and expenses.
3. Review the fund's liquidity and bid-ask spread.
4. Decide how much to invest.
5. Enter the ETF's ticker symbol.
6. Choose a market or limit order based on your trading preferences.
7. Review the order before submitting it.
8. Monitor the investment and rebalance your portfolio when appropriate.

Investors should confirm that the ETF is available through their brokerage and review the fund's prospectus before investing.

Alternatives to AI ETFs

Investors seeking exposure to the AI theme have several alternatives.

Broad-market ETFs. S&P 500 ETFs provide exposure to many of the largest companies investing heavily in AI without concentrating exclusively on the theme.

Technology ETFs. Broad technology ETFs can provide exposure to semiconductors, software and hardware while offering a different diversification profile than dedicated AI funds.

Semiconductor ETFs. Semiconductor-focused ETFs provide more concentrated exposure to the chips and manufacturing equipment underlying AI computing.

Individual AI stocks. Investors can select individual companies involved in AI, although this introduces greater company-specific risk.

Data-center and infrastructure ETFs. These funds can provide exposure to businesses supporting the physical infrastructure required for AI.

Frequently Asked Questions About AI ETFs

What is the largest AI ETF by AUM?

As of Sept. 24-25, 2026, the iShares A.I. Innovation and Tech Active ETF (BAI) was the largest U.S.-listed AI ETF by assets, with approximately $14.6 billion in net assets, according to ETFIQ. iShares reported $14.44 billion in net assets as of Sept. 9. 

The Global X Artificial Intelligence & Technology ETF (AIQ) was the next-largest fund in this group, with approximately $10.45 billion in net assets as of Sept. 25. 

AUM changes daily with market movements and investor flows.

Do AI ETFs Pay Dividends?

Some AI ETFs make distributions, but they generally are not designed primarily as income investments.

For example, WTAI reported a 1.26% distribution yield as of Sept. 10, 2026, while ARTY's 12-month trailing yield was 0.06% as of July 31, 2026. BAI reported a 1.34% 12-month trailing yield as of Aug. 31, 2026. 

Distribution amounts can change from year to year based on portfolio income and realized gains.

Is It Better to Buy an AI ETF or Individual Tech Stocks?

The choice depends on an investor's objectives and willingness to accept company-specific risk.

An AI ETF spreads exposure across multiple companies, reducing the effect that one company's poor performance can have on the portfolio. An individual stock can provide more concentrated exposure to a particular company's AI business, but the investment's results will depend much more heavily on that company.

Investors can also combine the two approaches by using a diversified ETF for core thematic exposure while maintaining smaller individual-stock positions.

What is the Difference Between AIQ and BOTZ?

AIQ and the Global X Robotics & Artificial Intelligence ETF (BOTZ) are both Global X thematic ETFs, but they target different parts of the technology landscape.

AIQ tracks an artificial intelligence and big-data index and holds companies involved in AI technology and the hardware used for big-data analysis. It had 88 holdings and approximately $10.45 billion in net assets as of Sept. 25, 2026. 

BOTZ focuses on robotics and artificial intelligence, including industrial robotics, automation, non-industrial robots and autonomous vehicles. It had 81 holdings and approximately $3.34 billion in net assets as of Sept. 24, 2026. Its top holdings included FANUC, ABB, Keyence, Intuitive Surgical and NVIDIA.

In other words, AIQ has a broader AI-and-big-data orientation, while BOTZ places greater emphasis on robotics, automation and autonomous technologies.