Umesh S. Nathani
During the first half of 2023, the S&P 500 Index returned 16.8% with nearly three-fourths of that performance coming from just ten companies.1 The dominating theme driving these lopsided returns is the advance of Artificial Intelligence (AI). While AI technologies have progressed steadily over the years, numerous advocates believe that AI has reached a tipping point where mass adoption by both businesses and consumers is imminent. Should this be true, it will affect investor returns in the years ahead.
However, it is important to recognize that market responses to technological innovation are often both rational and irrational—with the latter response driven by the “fear of missing out” (FOMO) following a surge in popularity and interest as evidenced with AI in Chart 1.2
To make better sense of these developments and their implications for investors, this article will delve into following areas:
In simple terms, the recent advances in AI showcase a significant leap in the way humans and machines interact. The latter are tireless artificial brains with access to copious textual data stored on the Internet, with masterful abilities to provide concise and seemingly logical answers to almost any reasonable question or request. With the addition of other qualities—such as no receding memory, 24×7 multi-tasking, no procrastination, no mood swings, and no excuses—the possibilities seem limitless.
The focal point of AI bustling to the scene is Generative AI—a broad term that can be used for any AI system that generates content of various types including text, images and audio. Generative AI is the underlying technology for a tool named ChatGPT, which is being used by more than 100 million users and has garnered attention as the fastest growing app ever.3 Developed by OpenAI, ChatGPT enables interactive and human-like conversations, offering insights and information on a wide range of topics. It should be noted that ChatGPT doesn’t possess true comprehension of text. Instead, it uses historical patterns to generate coherent responses to queries.4
The enthusiasm with ChatGPT has manifested in the markets through strong returns year-to-date for companies linked to AI, most noticeably Nvidia (+189%), Meta Platforms (+138%), Salesforce (+59%), Amazon (+55%), Microsoft (+43%), and Alphabet (+36%).5 The level of excitement with AI in equity markets today rhymes with some pivotal moments witnessed in Goelzer Investment Management’s 54 years of existence, including technological innovation waves such as the early adoption of PCs, the dot-com boom, and the advent of robotics.
Far beyond the recreational value of interacting with AI, Generative AI and Large Language Models (the technology underlying ChatGPT) are being explored for their potential to amplify productivity across major corporate functions, including marketing and sales, operations, IT, engineering, legal, and R&D.6 The potential of AI has grown to such an extent that roughly one-third of companies in the S&P 500 Index touted the potential benefits of AI during earnings calls from April through June 2023, as reflected in Chart 2.7 This represents a 65% increase in the number of companies expressing interest.
While the developments around AI are in early innings, two broad investment opportunity sets have emerged. The first includes those companies that develop AI technologies. The second opportunity set is in those companies that improve through the use of AI technologies.
Companies that are directly poised to benefit include, but are not limited to, cloud-computing services, companies offering AI-enhanced software products, and companies selling advertisements on social media platforms. Some examples of participating companies held in Goelzer equity strategies are listed in Table 1 below.
Many more companies may benefit through the use of AI technologies. Margin expansion is anticipated with the emergence of AI as a general-purpose and versatile technology. Although quantifying the precise impact on companies’ bottom lines may be challenging, initial studies suggest significant productivity gains when AI tools are implemented in the workplace.
For instance, according to research by the National Bureau of Economic Research, customer support agents experienced a 14% increase in productivity in resolving customer issues.8 Additional studies indicate that software engineers can code at a doubled pace, while economists can be 10 to 20% more productive by completing their writing tasks in half the time using AI.9 Healthcare providers are looking to AI to reduce administrative burden by automating clinical documentation during both virtual and in-patient care. A Biotech company, Insilica, has developed a Phase 2 drug candidate using their end-to-end Generative AI platform for one-tenth of the cost and one-third of the time needed with traditional methods.
While optimism surrounding AI is justified, it is important to address the potential risks associated with investing in AI-related stocks. The risks span two categories: expensive valuations and uncertainty of how this technology and its adoption will evolve.
One crucial aspect is the current valuations of these companies, which exhibit signs of market exuberance. Ignoring high valuations can lead to suboptimal long-term investment outcomes. For example, one metric commonly used for valuation analysis is the price-to-sales (P/S) ratio, which reflects the market’s expectations of growth prospects. Notably, Nvidia, a renowned AI darling, has traded at a staggering P/S ratio of more than 35 times trailing one-year sales in recent weeks, compared to the S&P 500 index’s average of around two times. As shown in Chart 3, forward returns for stocks with P/S ratios of ten or more have historically underperformed the broader stock market as measured by the S&P 500 Index. This illustrates the risks inherent with chasing popular trends.
Several variables could potentially impact how the use of Generative AI evolves. These factors include, but are not limited to, potentially restrictive regulations, litigation risks due to misinformation spread by AI tools, overpromise of accuracy, and plagiarism. Both the United States (AI Bill of Rights) and the European Union (AI Act) are considering regulations to address issues such as data privacy, algorithmic differentiation, disclosures to consumers, safety from facial recognition, and more.10 While the technology is likely to advance in its adoption, these factors could alter its path and pace of development—as well as the future returns on AI-related investments.
Incorporating these trends into investor portfolios requires careful assessment of both investment risks and potential returns. While these considerations will evolve over time, they can be broadly categorized as follows.
Predicting winners from new technologies is difficult. The 1990s dotcom era showed that excitement around transformational changes can quickly translate into irrational decisions by both corporate executives and investors. Most companies with “.com” in their name had stellar short-term returns but turned out to be long-term failures for investors. There is a need to proceed with caution as we evaluate the long-term potential for sustainable investment returns.
The current AI landscape favors some of the largest companies in the S&P 500 Index. Microsoft, Nvidia, Amazon, Google, and others participate in the AI market on multiple fronts such as hyperscale computing and advanced software and machine learning capabilities. However, AI also levels the playing field for new entrants where rapid innovations enable companies to roll out new software products that add fast growing revenue streams. Beyond these technology leaders, if AI continues to evolve as general-purpose technology, its benefits can be more broad-based, improving corporate profit margins and facilitating GDP growth through enhanced productivity. That will allow the list of AI-related winners to expand beyond the current list of large technology providers.
In summary, integrating AI into investment portfolios necessitates a comprehensive evaluation of investment risks and potential returns. By combining the analysis of AI trends with sound financial analysis of companies, investors can make informed decisions. Prioritizing long-term capital appreciation over short-term trading opportunities and adopting a diversified investment approach has proven to be a prudent strategy over time. As such, the emerging opportunities presented by AI should be considered within the context of a well-rounded investment approach, aligned with individual risk profiles and investment objectives.
1 S&P 500 Index Returns from 12/31/2022 through 6/30/2023, Bloomberg.
2 Google Trends, https://trends.google.com/trends/explore?q=ai.
3 “ChatGPT sets record for fastest-growing user base – analyst note,” Reuters, https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/, February 2, 2023.
4 Open AI, https://openai.com/about.
5 Stock Returns from 12/31/2022 through 6/30/2023. Bloomberg.
6 “Generative AI is a broad term that can be used for any AI system whose primary function is to generate content. … Large language models (LLMs) are a type of AI system that works with language. In the same way that an aeronautical engineer might use software to model an airplane wing, a researcher creating an LLM aims to model language, i.e., to create a simplified—but useful—digital representation.” “What Are Generative AI, Large Language Models, and Foundation Models?”, Helen Toner, Center for Security and Emerging Technology, Georgetown University, https://cset.georgetown.edu/article/what-are-generative-ai-large-language-models-and-foundation-models/.
7 Bloomberg. Based on search term “AI” in earnings call transcripts for S&P 500 Index companies.
8 “Generative AI at Work,” National Bureau of Economic Research (NBER), Erik Brynjolfsson, Danielle Li, and Lindsey R. Raymond, https://www.nber.org/papers/w31161, April 2023.
9 “Language Models and Cognitive Automation for Economic Research,” NBER, https://www.nber.org/papers/w30957, February 2023. “Machines of mind: The case for an AI-powered productivity boom,” Brookings, Martin Neil Baily, Erik Brynjolfsson, and Anton Korinek, https://www.brookings.edu/articles/machines-of-mind-the-case-for-an-ai-powered-productivity-boom/, May 10, 2023.
10 “Blueprint for an AI Bill of Rights,” The White House, https://www.whitehouse.gov/ostp/ai-bill-of-rights/. “What is the EU AI Act?,” https://artificialintelligenceact.eu/.
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