A few weeks ago, I had the pleasure of joining an outstanding event organized by Fordham University Gabelli School of Business. The topic couldn’t be more relevant - AI in Value Investing.
The event featured three panel discussions. The first one, “Generative AI: Competitive Advantage or Competitive Necessity”, was presented by Paul Johnson, the school’s Executive Director.
It was a great introduction to the broader AI landscape, but what I really liked was how Paul broke down the math behind hyperscalers’ earnings and how much they’d have to grow to justify the huge CAPEX being poured into AI infrastructure.
The second panel, “AI Tools Powering the Next Generation of Investment Research”, moderated by Brett Caughran from Fundamental Edge, was full of insights for anyone working with data and equity research.
The speakers, Tarun (Endex AI), Kris (Hudson Labs), and David (Portrait Analytics), shared an interesting perspective: access to data is becoming less monopolized by giants like SPGI 0.76%↑, FDS -1.16%↓, and MORN 0.43%↑. The AI moat is shrinking, and that’s a signal for investors to revalue those businesses. Just look at FDS -1.16%↓ valuation dynamics.
Personally, I took away a lot of ideas for optimizing the stock analysis workflow in my own strategy. Many PMs already have AI tools or even “AI analysts” working for them 24/7 - and that’s where the real advantage in data processing is moving.
The final panel, “Investing with Generative AI”, brought the discussion from theory to practice. Real portfolio managers shared how they integrate AI into their investment process, particularly in analyzing software companies that are either benefiting from or being disrupted by AI - think CRM -0.82%↓.
Panelists included Brett Caughran (Fundamental Edge), Andrew Freedman (Hedgeye), and John Belton (Gabelli Funds).
Big thanks to Gabelli School of Business and Fundamental Edge for putting this together. It was one of the most thought-provoking events I’ve attended this year.
Here’s a photo from the school’s trading floor:
