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Key Takeaways
- For large, established companies that can benefit from its capabilities, artificial intelligence is in many ways a sustaining innovation, not a disruptive one.
- High-quality businesses tend to remain high quality even during periods of technological change or rapid innovation.
ChatGPT was not the first game-changing artificial intelligence (AI) application, and it certainly won’t be the last. Yet, it has grabbed the world’s attention. Last November, OpenAI introduced the fourth generation of ChatGPT, an easy-to-use consumer chatbot that uses AI to generate human-like responses, drawing on a vast ocean of online data.
Since then, the pace of change has been dizzying. ChatGPT passed a million users within one week, while other rapidly growing apps took months to achieve the same level of adoption.1 Microsoft (MSFT) saw its stock surge after investing $10 billion in OpenAI and adding ChatGPT to Bing, a direct shot across the bow of Alphabet’s (GOOG) search dominance. Google, meanwhile, has launched its own generative AI app, Bard. Other stocks, like online-learning company Chegg (CHGG), tumbled after warning that ChatGPT could hurt their businesses.
For years, AI has quietly powered everyday features, from Google’s search engine to Netflix recommendations to cybersecurity detection. Other AI applications people use daily include smartphone facial recognition, targeted Facebook ads and Google language translation, while others like autonomous vehicles remain works in progress. The technology has become a game-changing force of disruption, creating new opportunities for winners and new risks for laggards, depending on how AI can benefit or challenge their businesses. That’s in part because ChatGPT has quickly become the “killer app” for AI. There are also other generative AI apps, including digital-image generators such as DALL-E and Midjourney.
Our Core Equity portfolio has had longstanding or significant positions in large cap established tech leaders that are positioned to benefit from the potential growth in AI, including Microsoft, Nvidia (NVDA), Alphabet, Salesforce (CRM) and Adobe (ADBE). Our recently launched Growth Equity portfolio has also invested in some of these companies. Given these investments, as well as the current state of the market, our clients frequently ask for our views on AI. In this piece, we share our take on investment opportunities and risks in generative AI.
Quality Still Matters
In short, our approach to the transformative new technology delivered by AI is a traditional one: The old rules still apply. We evaluate every sector of the economy to find high-quality companies and deeply understand their competitive advantages. Those that meet our high standards and are trading at attractive prices are candidates for our highly concentrated portfolios of approximately 40 stocks. We tend to avoid single-product companies or companies that don’t have a strong competitive advantage, leading us to more established players as investment opportunities.
The key attributes we seek are companies with strong competitive advantages, products or services that are poised to gain market share, a strong management team that can skillfully navigate changing markets and a consideration of how these business models may affect society or the environment. High-quality businesses tend to remain high-quality even during periods of technological change or rapid innovation.
Three Key Categories of Generative AI Solutions
We think that for large, established companies that can benefit from its capabilities, artificial intelligence is in many ways a sustaining innovation, not a disruptive one. That means that these new AI applications can become features or products that are a core part of the business. But in our view, it doesn’t necessarily mean that they will upend the structure of a lot of the industries in which we are invested.
High-quality businesses tend to remain high quality even during periods of technological change or rapid innovation.
We evaluate the applications of generative AI in three key areas: “pick and shovel” providers, proprietary data owners, and industry standard bearers.
Pick and Shovel Providers. Companies that provide the tools for others to use present a clear investment opportunity. In AI, this primarily means the makers of powerful chips as well as software platforms like Microsoft that integrate powerful AI apps into their offerings. Microsoft’s strategic investment in OpenAI, for example, provides it an opportunity to rent shovels to other companies hoping to explore the potential of AI.
We like chipmaker manufacturers Nvidia and AMD (AMD) that can churn out the powerful graphics processing units (GPUs) capable of handling the heavy work of training AI models and generating outputs based on their learning. Nvidia is a holding we first added to our Core Equity portfolio in 2018 and was an inaugural holding in our Growth Equity Fund launched last year. The company has a strong competitive advantage over nearly every other chipmaker thanks to its early focus on GPUs, which are ideally positioned to handle the intensive work behind the machine learning that drives powerful AI models. Nvidia’s early head start and investment in their software platform has given the company a wide moat in terms of a strong brand and high switching costs.
Proprietary Data Owners. If picks and shovels are needed to deploy AI, then proprietary data is the lifeblood that powers it. Regardless of how AI capabilities evolve, we believe companies that own massive amounts of unique, useful and valuable proprietary data are positioned to benefit from it. For example, S&P Global (SPGI) owns financial markets data and analytics, widely used market benchmarks, a credit rating agency and vehicle data unit Carfax. Regardless of which AI capabilities prevail, S&P Global’s high-signal data will be in demand among participants in the bond, commodities and other financial markets. Much of S&P Global’s data is hard to replicate, fortifying a wide moat around the company.
Another example of a proprietary data owner is Salesforce, one of our Core Equity portfolio’s largest holdings in 2023. The cloud-based software company has collected millions of granular datapoints over years on customer engagements and conversations that can yield deep insights into which customer interactions are most effective. Salesforce also uses AI to automate workflows and time-consuming tasks—one of the key efficiency benefits of AI applications.
Industry Standard Bearers. This group includes companies that have established themselves as scaled leaders and incumbents with large user bases. They are positioned to take advantage of AI adoption. Enterprise software companies, such as Adobe (among others), are a prime example of scale distribution. Their applications are already deeply woven into the daily workflows of millions of workers around the world, which leads to high switching costs. Once technologies like AI evolve beyond chatbots—and we’re already seeing this happen—we think the winners are going to be the companies with large-scale distribution like Adobe. Companies like this, with scaled distribution and deep workflow integration, are most likely to deliver and capture value from the adoption of AI.
Tempering the Hype
While some of this year’s hype around AI may be warranted, not all of it is. AI will roll out at different paces in different industries, and much like cloud computing, AI could take a decade or two to be fully adopted by other industries. In the meantime, promising new technologies like AI can lead to manias like early Internet stocks saw during the dot-com bubble, which could lead to volatile times in the interim. A lot of unexpected changes can happen before then.
That’s why we believe that keeping a long-term focus is an important aspect of our active-management investment philosophy. Our view is that it’s especially important right now to temper the hype and invest based on first principles and a clear investment thesis. Holding large, well-established tech players, as we do in our Core Equity and Growth Equity portfolios, offers investors the exposure to AI innovations and the potential for reduced risk if the application doesn’t live up to its promise. AI innovations will continue, and we believe our portfolios are well positioned for both the opportunities and the risks.
Applying Principles to AI
In addition to investing in companies for their long-term performance potential, we seek companies that treat their employees well and have a positive impact on their communities and the world around them. Sometimes we dig deeper to better understand how a company’s products are made and how they are being used.
We believe it is the responsibility of companies working with AI to ensure that these products are fair and equitable, accountable and transparent, and that they do not worsen existing disparities. Our Stewardship Team has identified potential algorithmic harms, such as bias and privacy risks, as topics of concern.
For example, we engaged medical records provider Cerner on the potential of AI to exacerbate unfair treatment of marginalized groups. We also work with other like-minded investors through the Interfaith Center on Corporate Responsibility to engage other healthcare companies on AI bias. We continue to engage other industries to create better governance structures around AI impacts.
June 2023
1 UBS Investment Research.
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