Aswath Damodaran on The AI Spending Spree: Bubble, Boom, or Both? | #619
My guest today is Aswath Damodaran, a professor at NYU, where he teaches corporate finance and equity valuation. In today’s episode, Professor Damodaran explains why he trimmed two Magnificent Seven stocks. He digs into AI’s real impact on valuations and moats, why big software incumbents face an Innovator’s Dilemma, and why the biggest risk isn’t tech spending itself, but overconfidence and debt-fueled capex that could ripple beyond tech. He also weighs in on corporate Bitcoin balance sheets, sports franchises as “trophy assets” driven by billionaire demand rather than cash flows, and the rise of prediction markets.
Key Points
- Investors should be cautious about overconfidence and the potential risks of high capital expenditure in the AI sector, especially when funded by debt.
- The valuation of professional sports teams is driven more by their status as trophy assets for billionaires than by traditional financial metrics.
- Increased skepticism and loss of trust in traditional financial institutions are driving interest in alternative investments like gold, silver, and cryptocurrencies.
Follow Aswath: Website; LinkedIn; X
Resources: To Bitcoin or not to Bitcoin? A Corporate Cash Question! Musings on Markets - Data Update 1 for 2026: The Push and Pull of Data! Musings on Markets - Data Update 2 for 2026: Equities get tested, and pass again! Musings on Markets - Data Update 3 for 2026: The Trust Deficit - Bonds, Currencies, Gold and Bitcoin! Musings on Markets - Data Update 4 for 2026: The Global Perspective! Musings on Markets - Data Update 5 for 2026: Risk and Hurdle Rates Musings on Markets - Data Update 6 for 2026: In Search of Profitability! Musings on Markets - Data Update 7 for 2026: Debt and Taxes
Aswath's appearance on the podcast in November 2024 Aswath's appearance on the podcast in May 2019 The Best Investment Writing Volume 3: Aswath Damodaran – The Perils of Investing Idol Worship: The Kraft Heinz Lessons! in August 2019
Chapters
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| 0:34 | |
| 7:26 | |
| 16:07 | |
| 23:10 | |
| 33:43 | |
| 45:12 | |
| 47:42 | |
| 52:27 |
Transcript
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