Avoiding Concentration Risk in AI: Is It Time for a Reality Check?

Introduction

The rise of artificial intelligence has captivated the minds of consumers and attracted the investments of market participants worldwide. A group of AI-related stocks dubbed the “Magnificent Seven” dominated market performance through last year as exuberance grew around the transformative potential of AI. While we agree that AI will create game-changing outcomes, we also believe that unbridled enthusiasm can expose investors to concentration risk. In fact, markets may be beginning to provide a reality check. Here we explore the assumptions driving the run-up in AI valuations and share how we position our portfolios with a long-term perspective.

A Rising Tide Will Lift All Boats, Right?

Over the past year or so, it seems that investors have been willing to grant a higher multiple to just about any and every company that mentions the word AI. In this environment, we’ve watched big technology firms publish splashy headlines about their latest efforts and have observed companies across a wide range of industries scramble to declare themselves AI-centric (we’re still a little puzzled after hearing a major cosmetics company declare themselves an AI company in a meeting). Many firms and market participants seem to be operating under the blanket assumption that AI, in any manifestation, will fuel earnings growth – they believe the rising tide of AI will lift all boats. At some point, however, investors need to go back and reexamine vastly different individual business models: Does each company stand to benefit from AI in the same way and to the same extent?

Information Technology and Professional Services Lead the Way with AI Adoption, but No Sector Is Immune

Source: U.S. Census Bureau, Business Trends and Outlook Survey, October 23-November 5, 2023

We’d highlight two key points to think about when discerning the winners and losers…

First, it is important to realize that not every company is going to get it right. Initially, it was easy for investors to give credit for any hint of AI adoption. However, as we enter the next chapter of this technological revolution, investors need to adopt a more discerning approach. It’s no longer sufficient for companies merely to tout their AI involvement; they must now demonstrate concrete results. The onus is on these enterprises to showcase tangible progress in transforming their AI aspirations into profitable ventures. Investors will increasingly demand evidence of AI-driven revenue growth, cost savings, and enhanced competitiveness. Companies that fail to deliver on their AI promises may struggle to maintain investor confidence and market valuation. As the AI landscape matures, the true winners will be those who can successfully bridge the gap between vision and execution, translating AI’s potential into measurable business outcomes.

Overcoming the Mismatch Between Expectations and Reality

Second, investors should consider the timeframe for generating productive results in the AI arena. Markets are coming to the important realization that AI won’t solve every problem in the world within the next 12 months. Some of the more impactful results will likely take a long time to come to fruition, and many solutions will be much more challenging to achieve than initially expected. Many firms are now experiencing the disappointment of sitting down with AI for the first time and getting less out of it than they expected (the initial version of Microsoft Copilot is a little underwhelming, for example).

AI certainly has some early positive productivity-advancing impacts (we happily use it ourselves a fair bit) but, by and large, it may be falling short of the sales hype in the near term. Undoubtedly, things will improve dramatically, but it will likely be a long-term evolution. Both firms and investors are now realizing that – and are now left to figure out which companies will “win” directly in the AI space and which companies will outperform by harnessing AI’s potential effectively in other ways.

Positioning for Long-Term Success in AI

At Thornburg, this weeding-out process is already happening. In seeking to thoughtfully curate and diversify our approach and, ultimately, exposure to AI, we start with the foundations: Which companies must do well for AI to succeed? What is required to realize the wide range of revolutionary possibilities? Our team seeks to identify the essential players and invest in the most compelling opportunities based on our belief that AI is an important technology over a multi-year time horizon — we see this as a marathon, not a sprint.

In addition to identifying the foundational players, we also explore AI’s second and third-order effects to uncover less obvious opportunities. Our goal is to understand how AI can trickle down to various sectors of the economy and how companies can integrate AI innovations into their operations to enhance their products and achieve gains in day-to-day activities. By applying the discipline required to dig deep and analyze these ripple effects, we aim to identify promising AI-related opportunities that may emerge over a longer timeframe.

One such example is in the healthcare space, where AI can improve the efficiency and effectiveness of drug discovery processes for identifying and developing new therapeutics. AI can accelerate traditionally complex and labor-intensive endeavors with significant financial consequences. As more computing power and relevant data become available, companies are applying AI at various stages in the drug discovery pipeline, including target identification and compound optimization, such as substituting high-powered models and simulations for costly lab work.

AI can also help consumer businesses enhance customer experiences to drive sales and profitability. Luxury brands, for example, pour massive amounts of financial resources into marketing and design to foster long-term relationships with valued customers. Today, AI solutions are helping brands deliver custom-tailored online shopping experiences and bespoke designs that build brand loyalty and strengthen emotional connections through imagery, advertising and copy. From a marketers’ perspective, personalized experiences, long considered the “Holy Grail” for achieving brand loyalty, are deliverable at costs far below early expectations.

Conclusion

We are still only in the initial innings of the AI evolution. Over the past year or so, this technology has burst into the mainstream, captivating firms and investors alike with its potential to reduce costs, boost efficiency, and expand margins. However, we anticipate a turning point on the horizon where the surge of expectations will inevitably collide with the realities of implementation. Perhaps that process is already underway in the first few months of 2024. Regardless, it’s crucial to recognize that the AI transformation is not an overnight phenomenon but rather a gradual evolution that we believe will yield success over time.

So, equipped with a long-term perspective, we aim to identify how AI will permeate various sectors of the economy and capture AI’s primary, secondary, and tertiary benefits with an eye toward overconcentration risk in the market. We acknowledge that volatility may punctuate the path forward but remain steadfast in our commitment to navigating this exciting yet challenging landscape.