Investing money in the artificial intelligence sector is potentially an effective way to profit from this technological revolution. However, the opportunities change so frequently that it can be hard to identify where to invest. Investor gains from AI-related stocks are most likely to come from companies in four major categories: AI model developers, AI-enabled software brands, AI infrastructure providers like Nvidia, and non-tech companies leveraging AI for growth. Understanding the different ways to invest in AI, from AI-focused exchange-traded funds (ETFs) to crowdfunding AI ventures, can help you decide where to focus your investments. Here’s what you need to know about the best practices for AI investing and risks to consider.
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Artificial intelligence is the most disruptive technology since the computer. It has the potential to radically transform how businesses operate, creating a major boost to efficiency and profits. We’re already seeing AI use cases in almost every sector, from autonomous vehicles in transportation to generative AI in marketing. As AI technology develops and new AI software companies continue to enter the scene, the market should become increasingly valuable. According to Statista, the global market for AI is currently around $200 billion and expected to reach over $1.8 trillion by 2030—nearly 10 times its current size.
Since we’re likely still at the beginning of this AI revolution, investing in AI-related companies now can be a financially savvy play, especially with such high expected market growth in the coming decade. However promising this investment opportunity may be, it’s still critical to research, follow AI trends, diversify your investments, and consider factors such as high market volatility, regulatory uncertainty, and personal risk tolerance.
There are many ways to invest in artificial intelligence, from buying shares of individual AI startups to crowdfunding AI projects.
Investing in AI stocks means buying shares of companies that use AI or machine learning to provide cutting-edge solutions to customers. For example, you might invest in Netflix because its AI-driven recommendation algorithm makes the product more addicting, or you could invest in a new AI writing tool that you believe will forever change content marketing as we know it.
There are two routes you can take when investing in AI stocks:
While the potential rewards of investing in individual AI stocks can be substantial, the risks associated with this strategy are higher than those of investing in ETFs, index funds, or other stock collections. A good rule of thumb is to invest around 10 percent of your overall portfolio in individual stocks.
AI-focused ETFs are investment vehicles that contain a collection of AI-related stocks—that is, tech companies offering or benefiting from AI. A key strategic benefit of ETFs is that they provide asset diversification. ETFs typically contain dozens of AI-related stocks, so if one AI company in your ETF fund falls in value, it will only minimally lessen the value of the overall ETF. Generally, this leads to lower risk than investing in individual stocks.
However, investing in such narrowly focused ETFs still carries risk. For example, if the entire AI market plummets in value, so does the entire thematic ETF. The following three high-performing AI-focused ETFs are examples of this type of investment:
Like stocks, ETFs trade on stock exchanges, giving investors the flexibility to easily buy and sell during the trading day. Unlike stocks, they come with management fees—however, these fees are typically lower than those for traditionally managed mutual funds.
Some AI startups run crowdfunding campaigns to raise capital. This alternative funding method typically involves raising small amounts of money from a large number of individual investors. You can find AI projects to invest in using crowdfunding platforms like WeFunder, which calls itself the Kickstarter for investing.
With an initial investment minimum of $100 and a median investment of $250, this platform is geared for investors looking to get in early on promising AI startups at a low price. However, investors must be willing to endure the very high risks of early-stage tech investing.
AI-related technologies include software and hardware that support the AI infrastructure, typically by providing either computing power or the systems support necessary to train and operate AI models. As demand rises for AI, demand also rises for these AI-related technologies, causing them to rise in the stock market.
For example, Nvidia stock has been soaring due to the increased demand for its GPUs, computer chips highly useful for training complex AI models like ChatGPT due to their ability to rapidly process massive amounts of data. Another AI-related technology set to rise in value during the AI boom is cloud computing, since many AI workloads are performed in the cloud. Top solutions in this market include Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Any hardware that supports the data centers necessary to train and operate AI will also see more demand as additional data centers open up around the globe to handle the increase in AI development.
One indirect yet effective way to invest in artificial intelligence is to invest in companies that operate in industries that will benefit from advancements in AI. The following sectors are worth considering for the ways AI is likely to improve their value:
Despite their high potential for AI disruption, these are not the only industries that will leverage AI to improve performance. Consider expanding your search into education, marketing, and any other sector where you regularly invest.
When it comes to investing in AI, there are three key investment risks and challenges to consider:
Staying informed is the best way to mitigate risk in AI investing. eWeek covers advancements in artificial intelligence, spotlights new AI companies and products, and explains AI trends to help you make informed decisions about investing in AI.
Strategies for investing in AI include diversification, long-term investing, and company analysis.
Diversification, or investing in various AI assets, is a great way to reduce risk. It protects against the high volatility of any single AI investment, minimizing the impact of losses. If, for example, a single AI software company falters for whatever reason, you’ll still have money in other AI stocks that continue to grow. A diversified AI portfolio might include stocks in the following categories:
Thematic funds such as AI-focused ETFs are also a form of diversification, as they compile many AI-related stocks into one fund.
Short-term investment strategies for AI focus on generating quick returns, often within a few months or less. The goal is to capitalize on short-term market fluctuations for rapid gains. An example would be investing in a new AI startup disrupting an established industry to capitalize on the hype and sell before it hits the top of its hype cycle. Despite their quick and potentially lucrative payouts, short-term strategies are more speculative in nature and carry a higher risk than long-term investment strategies.
Long-term investment strategies, often called buy-and-hold, focus on steady growth over multiple years or decades. The goal is to find stable AI-related assets that will increase in value over the long run. Often, stock investors leverage diversification in their long-term strategy to overcome market volatility, investing in assets like AI-focused ETFs, index funds, and established tech companies. On the other hand, value investors—who focus on stocks with lower valuations, which tend to be safer—often introduce a bit of risk to maximize their gains by investing in AI companies they believe to be undervalued.
Long-term strategies in the AI market are ideal for individuals looking to build wealth on autopilot and avoid frequently investing in stocks.
An investment analysis helps you understand an AI company’s intrinsic value, growth potential, and competitive advantage within its respective market. The following steps can help you analyze an AI-related company:
There are numerous factors to consider when picking AI stocks, from earnings forecasts to a company’s growth analysis. If you’re not a professional or skilled stock investor, conducting a full analysis of an AI-related company might be too time-consuming, not to mention risky. Fortunately, you can find analyst projections online. In these reports, professional researchers who understand the AI space share their thoughts on AI markets and stocks, helping you pick the right ones for your needs, risk tolerance, and investing goals.
Following AI news helps you make more accurate predictions about the growth of AI companies, industries, and technologies. Generally, the more in-depth your understanding and knowledge, the more successful your investments. The following are popular sources for staying up-to-date with AI trends:
When you regularly consume reports, articles, and other content from authoritative AI and finance publications, you set yourself up to spot AI investment opportunities, avoid pitfalls, and create an intelligent AI investment strategy.
While the AI landscape is packed with interesting and valuable companies, three are at the forefront and stable: NVIDIA, Microsoft, and Amazon.
This technology company—whose stock has soared in recent years—specializes in hardware, software, and artificial intelligence. Notably, it’s a leader in accelerated computing and graphic processing units (GPUs), which are used by data centers to run complex AI models.
A top driver in the AI landscape, Microsoft also offers the cloud computing platform Azure, which is a powerful solution for running AI workloads. The company is making breakthroughs in AI-powered software solutions with tools like AI agents and AI Copilot.
The e-commerce giant uses AI in various ways, from autonomous robots in its warehouses to personalized shopping experiences. It also offers the cloud computing platform Amazon Web Services, which helps businesses build AI-based software.
While no company is definitively leading in AI, top innovators include Amazon, Microsoft, and Nvidia. These companies offer AI solutions, cloud computing, and hardware that supports AI infrastructure. They also invest heavily in research and development, so they’re always launching new AI applications and tools.
It is not too late to invest in artificial intelligence. The initial revelation of generative AI occurred only two years ago, and that event marked the beginning of a long, gradual process of AI development and growth in the years to come.
Depending on the price of the stock or ETF, investing in AI can be just a few dollars. Crowdfunding AI websites even allow you to invest in startups for as low as $5. With so many AI investing options, you’ll likely find one that fits your budget.
Investing in AI-related stocks and ETFs requires careful consideration, which can be difficult amid all the hype and noise surrounding artificial intelligence. Instead of quickly jumping on the next hot tech company, investors should research fundamental metrics like revenue growth, earnings potential, and competitive advantages while understanding each company’s AI capabilities and applications.
They should also consider their own risk tolerance, financial needs, and whether they want to pursue a long-term or short-term strategy. Diversification across AI subsectors—from semiconductor manufacturers to AI software startups—can help reduce risk in this rapidly evolving, highly volatile space. Of course, staying informed on AI is vital to investor success. Read eWeek to stay abreast of the latest developments in artificial intelligence and related emerging technologies.
Read eWeek’s guide to the top generative AI companies for a detailed look at today’s leaders in the AI sector.
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