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AI ETFs to Watch & How to Pick Them

Defining AI ETFs

What are AI ETFs?

Artificial intelligence (AI) ETFs are exchange-traded funds that track a diversified basket of stocks from companies involved in artificial intelligence. These might be businesses that develop AI software, design AI-powered products, or manufacture the hardware used in AI technologies.

One of the key benefits of AI ETFs is that they hold multiple AI-related stocks, from software developers like Microsoft (MSFT) to hardware suppliers like NVIDIA (NVDA). This provides exposure to a broad range of AI companies and reduces the risk of relying on a single company’s performance.

Types of AI ETFs

AI ETFs can be broken down into a few different categories:

Technology ETFs

These ETFs invest in large tech firms that are leaders in AI innovation, such as Microsoft (MSFT), Nvidia (NVDA), and Alphabet (GOOGL). They may not be exclusively AI-focused, instead holding several stocks that drive AI development.

Examples of technology ETFs include:

  • iShares Future AI & Tech ETF (ARTY): Invests in AI and tech stocks, including chipmakers and cloud computing companies.
  • Invesco AI and Next Gen Software ETF (IGPT): Invests in companies that benefit from various forms of software and AI.

Technology ETFs are suitable for investors wanting broad exposure to tech companies benefiting from AI advancements.

Thematic AI ETFs

These ETFs focus specifically on businesses that are developing, applying, or benefit from AI technology. Their holdings might overlap with general tech ETFs, but they’re generally more concentrated in AI innovation.

Examples of thematic AI ETFs include:

  • Global X Robotics & Artificial Intelligence ETF (BOTZ): Invests in AI and robotics companies across various industries.
  • First Trust Nasdaq Artificial Intelligence & Robotics ETF (ROBT): Invests in AI and automation across healthcare, industrial, and software sectors.

These ETFs are ideal for investors wanting direct exposure to AI-focused companies rather than general tech firms.

AI-Powered ETFs

These ETFs don’t necessarily invest in AI companies but use AI-powered algorithms to analyze market data, sentiment, and trends to optimize stock selection. AI is used to decide which stocks to buy, hold, or sell.

Examples of AI-Powered ETFs include:

  • AI Powered Equity ETF (AIEQ): Uses IBM Watson to analyze financial reports and media to choose stocks expected to outperform.
  • Qraft AI-Enhanced U.S. Large Cap Momentum ETF (AMOM): Uses AI to identify and invest in large-cap stocks with strong recent performance.

These types of ETFs are for investors interested in using AI for portfolio management rather than AI as an industry.

Criteria for selecting AI ETFs

Choosing the right AI ETF requires carefully evaluating your investment goals and risk tolerance, as well as assessing the ETF’s fees, diversification, and past performance.

Investment goals and risk tolerance

First, it’s important to determine your investment goals and risk tolerance. Are you more interested in long-term growth or earning passive income?

  • If your goal is long-term growth, consider AI ETFs with exposure to innovative, high-growth companies. These funds might have higher volatility but may also offer greater return potential.
  • If passive income is what you're after, search for AI ETFs that include dividend-paying stocks, such as the ROBO Global Robotics & Automation Index (ROBO).

At the same time, it’s important to consider your risk tolerance. If you can take on higher risk, you might want to consider investing in thematic AI ETFs focused on emerging AI companies. If you have a lower risk tolerance, it may be more suitable to invest in broad tech ETFs that offer more diversification.

Expense ratios and fees

ETFs charge an expense ratio, which is the annual fee taken as a percentage of assets under management. Lower expense ratios mean lower costs, which can help maximize your returns. When comparing ETFs, pay careful attention to expense ratios as even small differences can affect long-term returns.

For example, iShares Future AI & Tech ETF (ARTY) charges an 0.47% expense ratio, while ROBO Global Robotics & Automation ETF (ROBO) has an 0.95% expense ratio. If you were to invest $10,000 in ARTY, you would be paying $47 per year in fees compared to $95 if you invested in ROBO. These costs compound over time and reduce overall returns.

Portfolio holdings and diversification

Next, you’ll want to look at the ETF’s stock selection and diversification. Some AI ETFs are broad, holding a large mix of companies across AI software, hardware, and cloud computing. Others are more niche, focusing on specific AI sectors like robotics, automation, or machine learning.

More diversified ETFs can help reduce risk by preventing one failing stock from impacting the entire portfolio. Look for AI ETFs that hold a diverse mix of AI companies across industries, or those that balance established tech leaders with emerging companies.

Historical performance

Past performance doesn’t always guarantee future results, but reviewing an ETF’s track record can help you spot those that have made steady growth over the years. This can suggest strong stock selection.

One way to do this is by comparing an ETF’s returns to the S&P 500 or Nasdaq-100. Look at 5-year annualized returns to identify long-term trends. If the ETF consistently underperforms, it may not be a good investment. If an ETF appears highly volatile, it’s a good idea to exercise caution unless you have a high risk tolerance.

Benefits and risks of AI ETFs

Benefits of AI ETFs

Some potential benefits of investing in AI ETFs include:

  • Diversification: AI ETFs provide exposure to a range of companies involved in AI, from software developers to hardware suppliers. This allows investors to hold a basket of AI-related companies instead of relying on a single stock.
  • Lower risk: Since ETFs contain multiple stocks, they’re generally less volatile than investing in a single company.
  • High-growth industry: AI is one of the fastest-growing sectors in technology. Investing in AI ETFs allows investors to participate in this growth while spreading risk across multiple companies.
  • Potentially lower costs: Some AI ETFs, like AI Powered Equity (AIEQ), use advanced algorithms to manage portfolios. Over time, this might lead to lower expense ratios by reducing the need for stock analysts and fund managers. This can maximize returns for investors.
  • Flexibility: ETFs that are managed by AIs might also be more adaptable when it comes to changing market conditions. For example, an AI may be able to analyze the market and adjust holdings in real-time, minimizing losses and capitalizing on trends before they become widely recognized.

Risks of AI ETFs

Some potential risks of investing in AI ETFs include:

  • Limited track record: Many AI ETFs are relatively new, meaning they don’t have a long history of performance data. This can make it difficult to assess whether these funds can consistently beat the market.
  • Low assets under management: Some AI ETFs have low assets under management, which signals relatively low investor interest. As a result, it might be harder to buy and sell shares efficiently, and volatility may be higher compared to established funds with more assets under management.
  • High expense ratio: Because many AI ETFs are small, they tend to have higher-than-average expense ratios compared to larger index funds. On top of that, many funds have a limited performance history, which could lead to investors essentially paying more for underperformance.

How to invest in AI ETFs?

Factors to consider when investing in AI ETFs

To recap, before you invest in an AI ETF it’s important to consider:

  • Portfolio holdings: What stocks does the ETF include? Some funds focus exclusively on AI-related companies while others hold a mix of general tech stocks that include AI firms.
  • Expense ratios: An ETF’s expense ratio will determine how much you pay in annual fees. Lower fees help maximize returns over time.
  • Historical performance: Reviewing an ETF’s history can provide insight into how it performs under different market conditions.

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