(“Why AI Will Never Replace Great Investors” was originally published on Keenan’s Substack. Read more of Keenan’s published work here: https://substack.com/@ksugarte)
The skill of being a great investor is half art and half science and people within the industry know this. The science—advanced math, economics, and financial modeling (among other examples)—is less than half of what’s required to be a good investor today. With recent advancements in AI, the emphasis on science continues to diminish.
I believe investing is very much like entrepreneurship in how opportunities are assessed based on risk/return scenarios, especially in early-stage investing. The initial screening and assessments are similar; however, the execution is where the two diverge. Investors back the jockey, while entrepreneurs back the horse. Both play in the same race, aiming for the same outcome: achieving outsized non-normal returns on their capital. Since entrepreneurs take on more risk, they should expect a much higher return.
That said, I believe the skills needed to be a great investor are essential to being a great entrepreneur. These include knowing who to partner with (or who to back), understanding markets (and knowing how to size them), and having a strong grasp of unit economics (including financial statements). All these skills are a must for for both entrepreneurs and investors alike.
What drives financial models?
Assumptions we make about the world and how it works.
When studying a project’s feasibility, we typically look at return metrics like NPV, IRR, Payback, MOIC, etc. These are determined by future revenues, which in turn, are based on assumptions about individual human behavior—specifically, how people might purchase your product and why, and the frequency of those purchases.
Understanding human behavior is an art, mainly because there are no fixed variables that determines every person’s actions, and how patterns can emerge based on those actions. We are all different and no formula can predict how humans will react to certain outcomes. Anticipating how people will react to new information is also an art—one that is partially driven by intuition and instinct.
Sure, AI can analyze past patterns of similar transactions and determine value based on previous deals or projects. However, not all projects are the same, especially in the world of early-stage investing.
I worked in investment banking and I wasn’t the best at financial modeling. I knew how to read models and understood the formulas, and that brings me more value today than being able to bust out 20-tab complex Excel models. It was a game where the beauty of a deck and model took priority over the actual purpose of those outputs, which is either raising capital or getting a deal done. Why? To be paid as an investment banker, you needed to show “value” to your clients. In this world, showing value meant fancy decks and financial models. That justified the work done for corporate clients to pay high fees.
What shocks me is that many analysts today seem to lack the view of the forest (the bigger picture opportunity) since most are focused on the trees (the decks and financial models). That said, the very fabric of investment banking—the nature of understanding what drives deals and the nuts and bolts of finance—brings tremendous value to anyone planning to pursue a life of entrepreneurship. Having an eye for what works and what doesn’t based on financial drivers is critical for anyone, especially CEOs. But does one need to know how to create complex financial models to understand this? Not at all. I would argue that it is more important to understand the math and the logic behind the models. This allows one to be able to dissect opportunities as they come. This has helped me tremendously and I encourage any founder to spend time understanding financial theory.
One of the greatest investors of all time, Joel Greenblatt, mentions:
“You are tilting your head a different way. There are a lot of smart people out there. A lot smarter than me. But if you look at things from 40,000 feet or from a different angle, that’s where I’ve tended to have my most success. You tell yourself “yes everyone is looking at it this way, but I don’t think that’s the right way to look at it” and when you recognize that you have this other way to look at it and all the pieces fit, those are the greatest opportunities. In my career, I’ve tried to look at things differently. It didn’t come from being better at analyzing businesses, it came from finding opportunities that other people weren’t recognizing, and having some ability, to evaluate based on how others would if they found it too.
You can watch more of it in the Farnam Street podcast:
What is more important in finance—especially in early-stage investing—is understanding human behavior. This understanding comes from experience outside of boardrooms. It’s about being on the ground, feeling the market’s pulse, and recognizing what drives human behavior. If you look at all the top investors, they tend to discuss philosophy more than financial metrics for this reason.
If you read The Alchemy of Finance, The Most Important Thing, and even Security Analysis, you’ll notice there is hardly any math in them. At most, you might find basic algebra. This is because finance is an art, and investing is an art.
What I love about investing (and entrepreneurship) is the ability to test your hypotheses about the world. Investing allows anyone to hold a view of the world and validate it through action, not mere words. The outcome—whether a win or a loss—determines if you were right or wrong. This is why Buffett says, “You are neither right nor wrong because the crowd disagrees with you. You are right because your data and reasoning are right.”
To be a great investor, you must often bet against the crowd. And for the most part, AI is the crowd. It’s beta.
I love ChatGPT for how it helps you understand consensus. It allows you to see what the crowd has thought in the past and what they are currently thinking. By analyzing pre-existing information, it projects those insights into the future.
If Picasso were around he would have amazing tools and who knows how his art might evolve with all the new technology available. His work might have taken a different direction, but one thing is certain: he couldn’t simply ask AI to create it for him.
Business is an art, and understanding human behavior is an art developed through experience. This is where real-world experience becomes essential—understanding human nature beyond the classroom and knowing how people react to new developments. It’s about learning how to adjust model assumptions and crafting scenarios that are unique to your specific opportunity.
This is what AI cannot replace.
Artists are usually influenced by the artists who came before them. But the best ones don’t just copy, they develop their own unique style. Investors work the same way. They start by learning from other investors, but over time, they create their own approach.
Take musicians. When you ask a great musician who influenced them, they’ll name a few legends from the past. But they don’t just imitate them, they take aspects of their style and evolve. It’s the same with investing. Ask a great investor who inspired them, and they’ll list names too. But their actual strategy and style will be unique to them, especially the great ones.
Blindly following someone else will only lead to average returns. By the time you replicate what another investor has done, it’s already been copied by everyone else. You’re just playing catch-up.
Imagine a musician trying to imitate Frank Sinatra’s style in its exact form. Would people buy his album? Maybe, but his success wouldn’t be remarkable. Why? Because people have already heard Frank Sinatra. They’d rather listen to the original.
In finance, this is called beta. What you copy is what’s been seen and copied by everyone else. You get average. Nothing great. Nothing bad.
What investors seek are non-average returns—what they call alpha. Alpha is typically achieved through actions that go against the crowd. If you study the greatest investors of our time, you’ll notice their philosophies and market approaches are so different that they occupy opposite ends of a spectrum. George Soros, Don Valentine, Marc Rowan, and Warren Buffett are examples of great investors with distinct styles, yet all consistently deliver alpha (above average returns).
Some investors align closely with one philosophy or another, but even within schools of thought, such as value investing, growth investing, and macro investing, the approaches are far from identical. This is where you discover the next Taylor Swifts and Ed Sheerans of the investing world. Those who break away from convention to create something uniquely their own.
What’s interesting about investing is that what has been seen is “probably” more efficient than what hasn’t been seen. I use the word “probably” to acknowledge that even in public markets, where positions are more liquid and visible, many investors still find arbitrage opportunities. In my view, it’s very hard to win in an arena where opportunities are widely observed, or where the odds are high that others will spot them before you do.
This is why I don’t invest in the stock market (unless arbitrage is obvious due to extreme irrationality). I’m drawn to more opaque, illiquid, and less visible private markets—particularly smaller companies in emerging markets. These are markets that are more fragmented, with less data and visibility. Chances are, Wall Street won’t spot them. They demand on-the-ground knowledge and an investor’s ability to hear, touch, see, and smell opportunities, rather than relying solely on Bloomberg terminals in a skyscraper office.
Why am I saying this? Because being a good investor requires a non-conformist view of the world—one that often involves working with new data, or data that hasn’t been widely seen. Without complete data, AI models can only take you so far. Recognizing new opportunities and gathering the unique data to feed those models becomes far more important.
The skill of inputting this data (models) and digesting it to justify opportunities will become commoditized. If you are an analyst who is an expert in Excel and Bloomberg but lacks the creativity to identify unique opportunities from 40,000 feet, your days are numbered. The next question is “how do you become good at identifying new opportunities?” I don’t have an answer. This is like asking a great guitarist how he became great. Sure, learning the basics of a guitar works, but there is something more that makes him great.
What’s interesting is finding what works or has worked, and combining it with your own unique insights, style and approach. The top investors each have ideas and philosophies that set them apart, beliefs that no one else fully shares. That’s what makes them special. No AI model can replicate this kind of individuality, unless AI models become sentient and reach the point of singularity. That’s another topic altogether.
Many people today think finance is an endeavor reserved for number crunchers and can be eaten away by AI. I would argue that number crunching (the aspect that will be taken by AI) is a small portion of what’s needed to be a great investor. Being a great investor requires the eye of an entrepreneur to understand the true nature of a business and its environment.
There’s also a big virtue-signaling component to investing. Understanding human nature and what it means to be a “good” person is just as important as understanding IRRs and NPVs. Without a strong sense of virtue, one cannot fully appreciate what it means to be a good leader or a good person. This insight is crucial—not only for assessing companies to invest in but also for choosing the right partners in any endeavor.
As Jim Collins says in his first book Beyond Entrepreneurship:
“There are seldom enough facts or data to eliminate all risk or to make a decision based solely on those facts. Furthermore, all business analysis is dramatically affected by your assumptions. Two people looking at the same set of facts will often come to entirely different conclusions about those facts. Why? Because they come at those facts with different assumptions.
We’re not suggesting that you should be thoughtless about your actions and run off in a blind fury of impulsive activity. Facts, analyses, and probabilities all have their place in decision making. Just remember that the objective is to make a decision, not to pulverize it with analysis.
In the world of entrepreneurship and investing, success depends on the outcomes you seek and being able to spot them before the crowd does, not just the analysis you perform. If your expertise lies solely on Excel or other tools used for decision-making, I would be concerned, as those skills are likely to be automated. However, critical thinking and creativity cannot be streamlined. The analysts who excel at both will thrive. This is the time for creatives to shine.
ABOUT THE AUTHOR
Keenan Ugarte is Managing Partner at DayOne Capital Ventures, an independent private holding company that invests in and builds high-growth, early-stage businesses that serve the underserved Philippine mass market. He is also the Co-Founder of The Independent Investor, a media platform spotlighting early-stage companies and innovation within the Philippine startup ecosystem.