AI & Investment Research

Way too often, I am seeing instances of analysts leveraging AI in investment research the wrong way. Yes, it is still early, and many are still learning to use it properly, but we should at the very least understand the following: 1. Claude is unlikely to generate a durable edge from widely available information because the same tools and data are available to everyone else. Even if you feed it every AlphaSense expert call, 10-K, and earnings call, it has a very hard time giving you a truly differentiated view. I am not saying that alternate data or expert calls are the key to a truly differentiated view. What I would say is that it is often necessary (but not sufficient) for one. 2. Claude, however, does have practical use cases in automation and explanation. This is as simple as putting company filings into a Claude project and giving you an **overview** (not a thesis) of a business. Perhaps you do not fully understand the business, and you would like AI to explain it using an analogy. This can save you **hours** a week, and what you do with said time is up to you. 3. imho, this time should be spent investigating the highest-value uncertainties in the thesis—whether through management conversations, customers, competitors, suppliers, experts, or primary research. **AI will never be able to replicate this (**unless experts eventually end up being okay with having channel checks with Wall-E)**.** *The bottom line here is: The edge has been, and will always lie in interpretation. Asking ourselves things like:* “What assumption on X KPI is consensus missing, and why?” “Am I thinking about the bear case hard enough? How do I actually know if I am?” “If I’m wrong, how much am I really losing?” ***So what will investment research look like in 5, 10, even 20 years from now?*** I can only imagine that AI’s use cases for summarizing, identifying anomalies within documents, and modelling will continue to develop at an unprecedented scale. The analyst who spends 20 hours manually summarizing filings will likely lose to the analyst who spends 2 hours using AI and 18 hours talking to customers, competitors, industry experts, etc). But the one asking the questions will always be the analyst. As information processing becomes commoditized, judgment will become more and more valuable. And remember. Investing has always been, and always will be, a judgment business. *Thanks for reading!* P.S: I am not trying to really self-promote here, but I do have a substack where I talk a lot about trends affecting investing, and how institutions and retail investors can adapt. I am also very happy to chat here or on DM!