Artificial intelligence (AI) is disrupting industries across the globe, from education to quantum computing. Everyday interactions, like going to the store, talking to a customer service representative, filing an insurance claim, and going to the doctor are being impacted. Everywhere you look, AI is solving complex problems, automating repetitive and dangerous tasks, crunching numbers, spotting patterns.

Investors can surf the AI tech wave via a broad array of investment options, from shares of AI giants, like Alphabet and Amazon, to AI-focused mutual funds and ETFs (1). These funds can also expose investors to global and regional companies that develop, produce, and leverage AI to hone their competitive edge.

Artificial intelligence (AI), a rapidly growing offshoot of computer science, is about building smart machines capable of doing tasks that usually require human intelligence. AI involves two kinds of learning: machine learning and deep learning.

 essentially programs a machine to learn through a variety of algorithms.

feeds data into an Artificial Neural Network (ANN), a complex network of mathematic functions whose form was inspired by the neural network of the human brain.

The learning function of AI is “self-improving,” which means it can be programmed to learn. Since the earliest science fiction, we’ve fantasized about robots figuring things out themselves, but now applications can be programmed to learn too—to better identify and prevent fraud, personalize shopping, improve medical diagnosis and treatment, predict transportation issues, and much more.

In today’s uncertain markets, companies have to tighten budgets and seek creative ways to remain competitive. AI’s capabilities can reduce expenses and offer a predictive advantage, all of which are pushing the adoption of AI in a myriad of ways.

Investors can look at companies that leverage AI’s machine learning and deep learning through a few lenses:

 Alphabet is one example, from Google searches and photo albums to Google maps auto-correcting to steer us away from traffic jams. Google’s DeepMind transforms pixels data into input, learning as it goes, both to defeat gamers in video games and predict millions of protein structures. E-commerce platforms like Amazon also have similarly deep integrations, from customizing recommended products to AI robotic assistants that help human workers in fulfillment centers, not to mention Alexa.

Companies like Tesla collect data from on-road autopilot vehicles to advance deep learning and hone outcomes. In addition, Tesla is designing its own AI chips (and even developing a robot taxi service).

 Makers of graphic processors (GPUs), or chip makers like Nvidia power AI applications in numerous industries, from higher education to video games to health care and logistics, speech recognition, medical imaging, and more.

 From automating tasks to smart diagnostic tools, AI promises to deliver better outcomes for patients, caregivers, and medical professionals.

Smart homes and appliances, self-driving cars, algorithms that personalize content from social media to product recommendations on Amazon, digital assistants that help you invest. Each generation of AI has become more powerful, spawning new capabilities and new applications.

Here’s one cutting-edge example: generative AI. With generative AI, the technology uses neural networks and prompts to generate new text, images, and other media or analyze complex information. Do you believe AI can create art and write novels? The debates are endless—and so are the possibilities.

Today, if a company isn’t investing in AI, it could become obsolete. For investors, this imperative is a potential boon to their portfolios. The global AI industry is predicted to soar to $422.37 billion by 2028—from a “mere” $59.67 billion in 2021 (2). In 2021, a record number of AI companies reached a value of more than $1 billion, up 442 percent from the previous year (3). AI innovations are already impacting healthcare, customer service and experience, banking, financial services, insurance, logistics, retail, cybersecurity, transportation, marketing, defense, and lifestyle.

Most businesses (65 percent) plan to use AI. Repetitive and low-level tasks look to be the majority of the applications, but identifying risks and improving security are priorities too (4). All in all, AI 

has the highest share of the AI market. (For example, think IBM Watson and Google Cloud Machine Language, which reflect AI’s capacity to facilitate decision-making and extract data.) AI services are the second-highest share, with smart solutions that fuel competitive business operations. AI 

makes up the rest of the market share but promises steady growth—and this makes sense as more and more companies will need robust AI storage and servers (5).

Globally, the AI market also holds a broad set of opportunities. The US is reaping the benefits of government initiatives and rapid adoption, while increased 5G adoption in countries like China and India means AI growth is ramping up in the Asia Pacific region as well (6). Big players have been acquiring key startups, but as long as there are engineers, entrepreneurs, and others who see yet another application, the race is still on to find the next big thing in AI, from more powerful GPUs to AI-generated art.

 There are ethical, legal, and social issues that arise from AI, such as bias, misinformation, and hate speech. To address these, governments are defining new regulations about when and how AI can be used, with leaders in the industry also setting governance structures in place to address. How these regulations—and the issues themselves—will impact growth potential is worth considering.

 There seem to be no limits to what AI can change and produce, but as we saw during the pandemic and during geopolitical conflicts, a drop in demand and supply chain issues can check growth.

 With any emerging industry, it’s challenging to predict which company will succeed. Nvidia is now dominating the market, but it wasn’t a sure thing when it launched in 1993. Spotting the pioneer who will break through to the big time—as well as weather global crises—isn’t an exact science. This is another reason why long-term investors who want to leverage AI growth look to ETFs instead of risking all their investment eggs by putting money in single stocks.

People can fear AI or see AI technology as a boon to progress, but its impact is undeniable. Perhaps Gary Kasparov sets the debate about AI in perspective the best. The chess master who famously lost a match against IBM’s Deep Blue computer had accused the machine and IBM scientists of “cheating,” but changed his mind by the time he wrote his 2017 book 

. “If we feel like we are being surpassed by our own technology,” he offers, “it’s because we aren’t pushing ourselves hard enough, aren’t being ambitious enough in our goals and dreams" (7).

There are a number of ways to add exposure to artificial intelligence to your investing portfolio. Investing in AI-focused mutual funds and ETFs allow investors to keep diversified with a range of AI investments, from GPUs to industries like gaming that are capitalizing on this sector’s explosive potential (8). Try one of these searches to get started:

Mutual Funds and Exchange Traded Funds (ETF’s) are sold by prospectus. Please consider the investment objectives, risks, charges, and expenses carefully before investing. The prospectus, which contains this and other information about the investment company, can be obtained from the Fund Company or your financial professional. Be sure to read the prospectus carefully before deciding whether to invest.

“How to Invest in Artificial Intelligence,” October 5, 2022, Forbes.com, https://www.forbes.com/sites/qai/2022/10/05/how-to-invest-in-artificial-intelligence/?sh=d34db2914384.

Global Artificial Intelligence Market Report, accessed January 9, 2023, International Trade Administration, US Department of Commerce, https://www.trade.gov/global-artificial-intelligence-market-report.

Global Artifical Intelligence Market Report.

“Artificial Intelligence (AI) Market Size, Share & COVID-19 Impact Analysis . . . 2022–2029,” accessed January 9, 2023, https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114.

“Artificial Intelligence (AI) Market Size, Share & COVID-19 Impact Analysis . . . 2022–2029,” https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114.

Kasparov, Garry, “Deep Thinking,” https://www.kasparov.com/deep-thinking-ai/.

Diversification does not guarantee a profit or protect against a loss in a declining market. It is a method used to help manage investment risk.

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