Not all AI opportunities are created equal

Right now, there’s no bigger buzzword than AI, and for good reason. This technology has massive power to transform how we live and work, and its rise in recent months has been nothing short of meteoric.

It’s still early days in terms of AI’s impact on the world. We’ve already seen how AI can serve as a better search engine, but we know it can and will do more over time. Given the scope of what AI could empower, I see AI not as a short-term trend, but a long and durable shift in computer architecture. The AI investment opportunity is big, largely still ahead of us, and has the potential to generate significant alpha in the coming years.

While AI is likely a winning technology — capable of helping enterprises either increase efficiency by doing more work with fewer people, or grow more effectively with the same number of people becoming more productive — not all AI-related companies will be winners in the long term. In this piece, we seek to provide a simple framework for assessing which companies can sustainably benefit from AI across the entire economy.

How to assess the impact of AI

I believe the key to understanding which stocks might benefit from AI lies not only in asking who can benefit, but also who can’t benefit. AI may be a rising tide, but it won’t lift all boats equally. So, how do investors determine which companies are uniquely positioned to benefit from AI? We believe there are five criteria investors should consider when analyzing potential AI winners and losers:

• Culture, leadership, and mentality: The speed of new technology adoption often augurs future success. Companies that integrate new technology earlier and better than their peers usually have a culture of risk-taking and innovation from the management level outward. So, examining company culture is important.
• Scale: Something we’ve learned from past innovations like the cloud and machine learning is that having the right tools and talent to understand, develop, and implement new technology is critical. Companies with the capital and scale to cull and cultivate talent effectively and in larger numbers may be at an advantage.
• Data: To leverage AI, you need data. To do so better than competitors, you need differentiated data. Stronger data allows companies to produce better models faster, which is a self-perpetuating advantage that can grow with time. Swift implementation of differentiated data is what sets today’s most successful large-language models apart from their peers. The same could be true of smaller models and other use cases going forward.
• Industry norms: Regulatory bodies — the SEC for financial services, FDA for biotech, HIPPA for healthcare, etc. — can limit or materially slow down AI adoption. Companies in industries are more likely to prefer to hold off on implementing AI if it means staying on the right side of regulatory risk. This is something to consider when assessing which companies are most likely to benefit from AI.
• Workflows: Many companies have complex, specialized processes that rely on deep human expertise that can be hard for AI to replicate or automate. Since these companies may take longer to adapt, investors may not see immediate opportunities.

Investment implications

Think within this framework…
As AI adoption becomes more widespread and AI capabilities more robust, some companies will fare better than others. However, most companies will likely see their competitors doing the same things they are doing, and ultimately the value will not accrue to shareholders. Examining companies through the lenses outlined above may help investors parse out the most compelling, standout opportunities.

…and outside the box…
Creative thinking is essential at the beginning of any new tech cycle. It’s one thing to recognize the transformative power of a technology, and another to think beyond the first use cases. Of course, AI will impact tech-related sectors, but how could it transform others? How will companies and jobs evolve once AI is part of their fabric? How will human skill sets evolve to leverage new ways of working? I believe the answers to these questions could be very broad. Any number of sectors could transform. Companies and jobs could evolve massively. People could develop skill sets that are as unimaginable to us today as using a smartphone might have been to our grandparents. Thinking outside the box opens one’s eyes to the vastness of the opportunity set within AI.

…with an active manager.
While no one can divine the future (when it comes to AI or otherwise), active managers who have learned from other tech investment cycles and have access to deep wells of research may be poised for relative success when it comes to AI investment. A long-term understanding of investment strategy will be crucial in a market as competitive as AI, so experienced active managers may have an edge. Thus, investors seeking to capitalize selectively on the AI opportunities with the strongest long-term potential may do well to lean into an active approach.