I had the privilege of attending the executive programme on AI at the Massachusetts Institute of Technology (MIT). It was an extraordinary two weeks spent alongside 60 business leaders from more than 20 countries, representing a wide range of industries, being taught by some of the world’s brightest minds on the subject.
Amara’s Law states that we tend to overestimate the impact of new technology in the short term and underestimate it in the long term. Given the present level of hype about AI, the idea that we might still be underestimating the long-term implications is hard to take in. But two weeks at MIT made it clear to me that we probably are.
AI has already matched or exceeded human performance across a wide range of expert tasks, in some cases by a big margin. That gap will widen. Hundreds of billions of dollars are being invested, and the scaling laws that have driven recent progress still hold. Whatever you think AI can do now, it will do more in future.
This leaves an obvious question: what is left for us? The instinct is to answer by listing the things AI cannot do. But that is the wrong approach. AI’s capabilities will keep changing, and any answer based on what it cannot do now will be out of date soon enough. The better question is this: what should remain human, and why?
In the investment management industry, one of the obvious answers is engaging with management teams. Spending real time with the people running a business builds an understanding that no transcript or filing can replicate. You get a read on how they think, how they respond to pressure and who they are, not just what they say.
This is a small example of a far larger pattern. The most valuable information in investing, and I would argue in most serious work, is rarely the existing information. It is the information that emerges from interaction. From two people with different perspectives pressing on the same problem. From the moment one person sees what another has missed. From the debate that forces a sharper answer than either started with.
Recent research from Harvard Business School, conducted in collaboration with Procter & Gamble and Wharton, makes the point directly. They ran a large experiment comparing individuals and teams, with and without AI. Individuals using AI matched the average quality of human teams without AI, which is a striking result on its own. But the more important finding was about exceptional output. Teams using AI were about three times more likely than the control group to produce top-decile solutions. Individuals using AI were not. AI alone raises the floor. Teams with AI raise the ceiling.
The implication for investment management is significant. The traditional model of a single portfolio manager, however experienced, making every investment decision is unlikely to survive this transition. At Marriott, for more than 20 years, we have run all our portfolios through an investment committee rather than a lead fund manager. The committee seeks consensus on every decision. That choice was made for reasons that had nothing to do with AI, but the logic that supported it then is the logic AI is now making unavoidable.
AI may already be smarter than any individual portfolio manager. However, it is not smarter than a team of people with different perspectives, because a team is not a single intelligence but the friction between several. What remains after the analytical edge has been commoditised is the value of that friction. The implication is profound: if AI can raise everyone’s analytical baseline, competitive advantage no longer comes from access to intelligence. It comes from the diversity of perspectives applied to it.
Which means the question stops being how many people you have and starts being how different they are from each other and from the AI they are working with. You only have to look at the Springboks to see what this can look like. Head coach Rassie Erasmus did not build the most diverse squad in world rugby because it was admirable. He built it because he believed it was the only way to win at the level required. And he was right. The variety of backgrounds, languages and styles of play was not something the team had to overcome to succeed. It was the reason they succeeded.
The enduring value of being human
This is what I came back from MIT thinking about. AI, no matter how brilliant, will ultimately be a commodity, because everyone will have it. In time, the architectures we build around it will commoditise too. The advantage cannot lie in either. It will live where it has always lived, in the people. Not in the same way as before and not doing the same things as before, but in the human capacity for creativity, interaction, and genuine variety of thought, sharpened by tools and channelled through the systems we design around them.
What makes us different is what makes us valuable ― now more than before.
• Matthews is chief investment officer at Marriott Investment Managers.
Business Day
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