How to invest in AI? A guide to navigating the future of AI investments

Artificial Intelligence (AI) is now a present-day reality rather than a futuristic concept, driving significant transformations across industries and everyday activities. From household virtual assistants to autonomous vehicles, AI is ubiquitous, prompting considerable interest from investors aiming to capitalize on its rapid growth.

However, investing in AI presents challenges. The landscape is intricate, with advancements at one company reshaping the entire industry. Just as investors in previous generations navigated the rise of smartphones and apps, today's investors must discern between emerging players and established tech giants competing for AI dominance and research funding.

In this article, we delve into prominent AI stocks and funds, equipping investors with insights to navigate this dynamic sector effectively.

How to invest in AI?

Similar to historical technological revolutions like the railroad boom in the late 1800s or the advent of personal computers in the 1980s, investing in the current AI trend offers multiple avenues. However, just as some companies in past revolutions saw immense success while others faltered, the same holds true for AI pioneers.

The analogy with the computer revolution is fitting because, while computers automated routine tasks, AI now aims to extend this capability by automating tasks that previously required human intelligence.

AI has swiftly emerged as a disruptive force. Identifying these trends and investing in new companies can yield substantial returns. Yet, given the intense competition, predicting which companies will emerge victorious is challenging.

Sometimes, the first mover gains a dominant market position, but occasionally, a competitor enhances the original technology and achieves greater success over time.

Investors can choose to invest directly in AI developers or opt for companies poised to benefit from widespread AI adoption. Drawing from the early days of the personal computer industry, successful investors backed computer manufacturers, hardware producers, software developers, or companies poised to leverage automation.

These investments ranged from direct bets on technology to more conservative approaches, such as investing in established companies set to benefit from expanding computer use. The key takeaway is that new technologies breed winners and losers.

Lastly, considering AI's potential economic impact and its potential to reshape industries and displace workers, opportunities may exist in investing in companies focusing on worker retraining or adapting to workforce shifts.

Invest in AI stocks and ETFs

Leading companies in AI

• Tesla (TSLA): Tesla employs AI to automate driving tasks, requiring continuous data processing for real-time identification of vehicles, road conditions, traffic signals, and pedestrians. Its market capitalization as of May 2024 is nearly double that of Toyota, the next largest automotive company, and 12 times that of Ford Motor Co.
• NVIDIA (NVDA): NVIDIA Corp. is a key player in the AI revolution, known for its development of graphics processing units (GPUs) and associated hardware and software products. Investors have taken notice: as of May 2024, its stock price had tripled over the past year and surged more than 2,000% over the past five. GPUs, initially designed for PC gaming, have become foundational for AI, machine learning, autonomous vehicles, robotics, augmented reality, virtual reality, and even cryptocurrency mining systems.
• Microsoft (MSFT): Microsoft has partnered with OpenAI, the company behind ChatGPT, integrating AI into its Azure cloud services. Microsoft 365 offers a subscription for generative AI called Copilot. In April 2024, Microsoft reported that 65% of Fortune 500 companies were using Azure OpenAI, mirroring the adoption rate of Copilot.
• Taiwan Semiconductor Manufacturing (TSM): As the world's largest chipmaker, Taiwan Semiconductor Manufacturing plays a crucial role in producing chips for AI applications. With AI demand rising, TSM continues to manufacture chips for both AI and traditional computing, potentially offering lower risk compared to pure AI plays. Its stock price has risen approximately 230% over the past five years, with an annualized growth rate of 17.7% from 2019 to 2024.
• Meta Platforms (META): Meta has heavily invested in AI, developing its large language models for search and content prediction across platforms like Facebook and Instagram. It integrates generative AI into advertising services and continues to innovate in AI capabilities.
• Amazon.com (AMZN): Amazon utilizes AI in its Alexa ecosystem and offers machine learning and AI services to businesses through Amazon Web Services (AWS). Amazon Q AI assistant is available for software development and data analysis, while Amazon Bedrock provides AI foundation models for building specialized AI systems.
• Apple (AAPL): Apple integrates AI into various applications including Siri for customer interactions, and has been expanding AI capabilities in photography, health, maps, and other areas. Apple users can access AI applications such as ChatGPT through its ecosystem, demonstrating its commitment to AI integration and development.

Best AI ETFs

Investing in professionally managed ETFs or mutual funds that hold shares in AI companies allows investors to rely on fund managers' expertise in researching and selecting suitable AI firms. Through an ETF, investors gain exposure to a diversified portfolio of multiple AI stocks within a single investment.

iShares Exponential Technologies ETF (XT): XT is a large-cap fund that targets global stocks aiming to disrupt their respective industries, including significant holdings in AI technology stocks. These stocks constitute nearly half of the fund, with the remainder allocated to healthcare and industrial sectors actively exploring AI applications. The fund has an expense ratio of 0.46% and an annual yield of 0.44%.

Defiance Machine Learning & Quantum Computing ETF (QTUM): With approximately $246 million in net assets, QTUM invests in companies advancing research and development in quantum computing systems. It tracks the BlueStar Quantum Computing and Machine Learning Index and has an expense ratio of 0.40% and an annual yield of 0.80%.

ROBO Global Robotics & Automation Index ETF (ROBO): ROBO focuses on companies involved in robotics, automation, and AI, encompassing both growth and value stocks. The fund has an expense ratio of 0.95% and an annual yield of 0.05%.

How can one identify AI investment opportunities?

Investing in individual AI stocks requires more effort from the investor. Begin by familiarizing yourself with the AI industry to understand its different facets. Within AI, there are pure-play companies and more conservative options, so decide on the type of exposure you seek. Conduct traditional investment analyses, both fundamental and technical, once you've identified your investment targets.

• Evaluate Earnings Forecasts: Consistent and growing earnings are crucial for AI companies, especially as many are viewed as growth stocks. Earnings releases often have a significant impact on AI stock prices.
• Review Annual Reports: These provide narrative insights into company activities, while financial statements offer key metrics like debt-to-equity ratios to inform financial decisions.
• Assess Relative Performance: Compare how AI stocks perform against market indices or similar companies to gauge their competitive position.
• Conduct Growth Analysis: Evaluate metrics such as earnings growth and market share to gauge a company's growth trajectory.
• Consider Analyst Projections: Analyst reports provide valuable insights, particularly in a fast-changing and volatile sector like AI, where technological advancements and company prospects evolve rapidly.

These steps help investors navigate the complexities of investing in AI stocks and make informed decisions based on thorough analysis and industry knowledge.

Is it profitable for investors to invest in AI?

AI adoption is on the rise, poised for significant expansion across various industries and practical applications. Like other capital-intensive technologies, AI presents numerous opportunities for investors to capitalize on potential gains, but it also carries inherent risks. Therefore, it's essential to carefully assess how to gain exposure to AI without exceeding your risk tolerance. Options range from more speculative investments directly in individual AI firms to diversified approaches via ETFs and mutual funds. Additionally, established companies poised to benefit from widespread AI adoption offer another avenue for investment growth.

How to invest in AI art?

Generative AI's application in creating images has been widely embraced, allowing users to describe an image they envision, and AI generates it based on available images worldwide, albeit not always perfectly. This technology has attracted users of diverse backgrounds and ages.

Copyright concerns are prevalent with AI-generated art, similar to other generative AI applications. Many artists argue that these AI programs infringe on their copyrights by using existing examples to create new art, potentially jeopardizing their income. Publicly traded companies like Pinterest, Getty Images, Snap Inc., and Shutterstock possess extensive art collections used by AI art generators.

How can you invest in AI startups?

Startup companies frequently emerge in burgeoning sectors like AI and machine learning. These ventures typically start with funding from venture capitalists, aiming to later go public to scale their initial investments and attract further capital as they expand and introduce their products to a broader market. Investing in startups carries inherent risks, yet successful ventures can yield substantial returns. Notable examples of prosperous startup companies include Apple, Amazon, and Microsoft.

Is it possible to make direct investments in AI?

In conclusion, investing in AI in 2024 presents promising opportunities for portfolio diversification. AI technology is increasingly integrated into various industries such as media, healthcare, automotive, and finance. However, investors should be prepared to address challenges including regulatory changes, supply constraints, and broader ethical and environmental concerns related to AI deployment. Keeping abreast of developments and focusing on companies with strong business models will be essential for maximizing opportunities while managing risks in this burgeoning sector.