5 ways to invest in AI

Artificial Intelligence (AI) has exploded in popularity since the launch of ChatGPT in November 2022. Consumers and businesses alike have adopted the technology faster than any previous innovation, including the personal computer, internet or mobile phone. Analysts now even talk about other technologies having their “ChatGPT moment,” where a technology suddenly goes viral and achieves mass adoption.

In this article, we highlight 5 ETF and stock strategies for investing in different types of AI companies.

Broad market ETFs

If investors believe that companies will widely adopt AI as a long-term trend, then the simplest way to invest in AI is to hold a broad market fund. If AI ends up being a key driver of corporate profits, its value will be reflected in the equity market. Popular stock benchmarks like the S&P 500, based on market-cap weighting, already bring huge inflows of capital to the leading stocks. For example, if the top 10 stocks in the S&P 500 were equally weighted, they would make up 2% of the index; in contrast, they currently make up 38.5% of the index.¹ 

Although investing in a broad market fund is a straightforward approach, it still involves some careful thinking about which markets to emphasize. Investors may wish to consider equity exposure not only to the United States but also to China. However, Chinese equity returns have been almost flat over the last decade, even though China has boosted its capacity in AI and related areas such as automation and robotics. Investors should not assume that massive spending on AI will result in strong performance for broad equity markets.

AI-focused ETFs

Investors who want enhanced AI exposure but do not want to select individual stocks may consider AI-focused funds. As a starting point, visit the Investor’s Edge platform. When searching ETFs by symbol, type “Artificial” and explore some of the ETFs in the search results. While some funds are pure-play AI, other funds include AI as part of trends like automation or robotics.

High-growth tech companies often move fast but can also take a long time to become profitable. For example, investors may have correctly identified in the 1990s that the internet would become a profit-generating technology. To be proven right, technology investors had to endure a lost decade in the 2000s, before internet companies finally became highly profitable in the 2010s. If AI follows a similar path, do you have the patience to wait?

Expect AI-focused funds to be more volatile than broad market funds, with greater sensitivity to interest rates. AI companies often invest a lot of capital upfront — for example, building data centres or acquiring patents — expecting that it will take many years for their investments to pay off. A large part of the equity value of high-growth tech companies is in the distant future. When interest rates rise, those distant cash flows are worth much less than near-term cash flows, which can lead to sharp selloffs. Investors had a taste of this in the tech crash of 2022, even before AI became a major investment theme. On the flip side, when interest rates fall steadily over time, high-growth tech companies may benefit more than the broad market.

Tech leaders

Investors may want additional AI exposure but may feel that AI-focused funds are too niche for their taste, given their inclusion of pure-play AI companies and early-stage technologies. One way for investors to accentuate AI in a portfolio is to consider large companies that are already technology leaders, expecting that they will build AI strategies into their business. To explore these companies, sign on to the Investor’s Edge platform, go to the Quotes and Research menu and select Trade Ideas. From the available themes under Trade Ideas, select AI. This curates a selection of mostly U.S.-based companies with large, diversified businesses, where AI may play an important role.

The AI landscape is diverse, including not just tech leaders that are inventing AI software and hardware but also AI adopters and suppliers. Let’s explore some of these other companies.

AI adopters

Businesses in some sectors, such as health care, finance and utilities, are major adopters of AI. Applications of AI in these sectors include:

• Health care: Clinical decision support, medical imaging analysis, drug development, personalized medicine and remote patient monitoring.
• Finance: Fraud detection and prevention, algorithmic trading, credit risk assessment, anti-money laundering and insurance underwriting.
• Utilities: Automation of meter reading and outage detection, analytics for smart grid management and personalized consumer insights to save energy costs.

Typically, the larger companies in these sectors are at the forefront of implementing AI. To find likely AI adopters in these sectors, start by looking at the largest 10 to 20 holdings of U.S. sector funds. Also see what AI can find for you. Here’s an example of an AI prompt: “Identify the top 10 companies in the U.S. health care sector that are implementing AI.” This is a task well suited to AI, since it involves scanning a wide variety of data sources, such as analyst reports, earnings calls and social media.

AI suppliers

Businesses in other sectors, such as energy and mining, are important suppliers to the AI industry. Here are some of the effects of AI on these sectors and possible implications for individual stocks.

• Energy: Increased demand from data centres and greater need for clean or renewable energy, rewarding companies that can deliver on long-term contracts.
• Mining: Increased demand for copper, lithium, cobalt and rare earth metals. Miners may also incorporate AI to improve geological surveys.

Here AI will likely find some examples close to home. As an example of an AI prompt: “Identify the top 10 companies in the Canadian energy sector that will likely benefit as suppliers to the AI industry.” 

The examples of adopters and suppliers highlight that AI can have ripple effects that go beyond the technology sector. These effects may be of interest to those who would not normally think of themselves as technology investors.

In this article, we discussed 5 strategies to invest in Artificial Intelligence (AI).

• ETF strategies include broad market funds for long-term exposure, or AI-focused funds for higher-conviction plays. These strategies let you get exposure to AI without trying to pick the winners.
• Stock strategies include AI leaders in the tech sector; AI adopters in sectors such as health care, finance and utilities; and AI suppliers in sectors such as energy and mining. These strategies let you assess which companies may stand to benefit from AI, including a wide range of companies beyond the technology sector.

AI can help you identify and research investments. Maybe at some point, it will even invest for you. But for now, that’s over to you; as with any investment, check that it meets your goals and risk tolerance.

¹ Data from iShares S&P 500 ETF, ticker symbol IVV, as of August 12, 2025.