Recent Artificial Intelligence (AI) advances have brought the topic to center stage. Given the progress, the promise, and the hype, it is little wonder investors are excited to see who is focusing on the space and what they are doing. Here is a glimpse of how we at Mitchell Capital Management (MCM) approach evolving technologies such as AI.
AI is a broad idea with a million ways to manifest. Generative AI describes innovative technologies that independently create text, images, video, and computer programming using machine learning. You have interacted with many already through Apple’s Siri, Amazon’s Alexa, or a chatbot on a retailer’s website. The more they get used, the more they learn, and the better they work. And abilities are advancing rapidly.
As with most new technologies, there are few public companies for whom AI is a singular focus. Most are small, privately held, and unprofitable. OpenAI, the owner of ChatGPS, one of many generative AI technologies, was funded by various deep-pocketed investors during its development. While the enthusiasm that followed its recent introduction appears to suggest great potential, it also offers a significant downside if someone else creates a better tool. In turn, rather than try to identify which company will develop the best AI for any particular application, we adopt a much broader lens.
We seek to find companies whose products and services are in demand now and will likely be in greater demand as and when AI usage becomes more widespread. Consider software companies like Adobe or Salesforce, whose programs are used broadly. Both have recently announced additions of generative AI technologies to enhance embedded creative capabilities. Or Microsoft, whose increased investment in OpenAI includes using its models across consumer-facing products and services like its Bing search engine that competes with Google. Apple and Amazon are two other deep-pocketed tech names announcing AI projects to extend the work they have done already.
Or consider autonomous vehicles, predictions of which have outpaced actual progress. Nevertheless, engineers have made incremental improvements. The most well-known option is Tesla, whose cars already offer some degree of self-driving on their models. Traditional automotive companies are providing financial backing for and using the technology of smaller, lesser-known (and privately held) AI software developers. Some of these efforts reflect successful steps. Other investments have been written off or shut down.
AI plays a critical role in autonomous vehicles, but other technologies are required too. Radar, cameras, GPS, and LIDAR (the laser-based system that creates a 3-D image of the vehicle and everything around it) are all well-advanced, but the high levels of redundancy present a key cost challenge. AI can be perfect, but buyers will melt away if the product costs too much.
Finally, we consider the infrastructure needed to support additional AI. Machine learning that underlies AI requires massive amounts of data and energy. As AI applications expand, data and energy demands will increase in lockstep. Companies that construct, manage, and stock the associated data centers will experience similar growth as they race to add the capacity needed to meet the infrastructure requirements. Consider the hundreds of companies that operate data facilities around the globe. Many are privately held, while others are divisions of large, well-known, publicly traded companies such as Amazon Web Services, Microsoft Azure, Google Cloud, and Meta Platforms.
Each data center needs hardware from companies down the supply chain. For example, Nvidia and Intel, AMD, and IBM provide software development tools to build AI applications. Netherlands-based ASML makes powerful lithography machines for companies like Taiwan Semiconductor that produce chips faster and more accurately. Keysight provides software and consulting to help produce chips even more efficiently. Arista Networks, Cisco, Juniper Networks, and others provide hardware for the data facilities and the means of communication within. And companies like Amphenol and Schneider Electric provide simple parts such as wires and antennas to support the movement of energy.
AI is just another tool in the box. While its absence may leave certain companies less competitive, its presence doesn’t guarantee shareholder success. In our experience, first movers rarely provide the best returns. Instead, focus on the best-run companies designing incremental improvements that use these new tools most effectively.
Disclosure: This is for informational purposes only and any reference to a specific security does not constitute a recommendation to buy or sell that security. The reader should not assume that an investment in the securities identified or described, was or will, be profitable. For a complete list of disclosures, please click https://mitchcap.com/disclosure/