Michael Mauboussin | AI, Base Rates, and Investing in the New Economy episode artwork

EPISODE · Apr 2, 2026 · 1H 1M

Michael Mauboussin | AI, Base Rates, and Investing in the New Economy

from Excess Returns · host Excess Returns

In this inaugural episode of our new show, The Intangible Economy with Kai Wu, we explore how AI, intangible assets, and unprecedented capital investment are reshaping the future of markets. Michael Mauboussin joins Kai to break down why today’s AI expectations may be historically unmatched—and what that means for investors trying to assess risk, returns, and who ultimately captures value.Subscribe on SpotifySubscribe on AppleThe conversation moves from base rates and AI growth expectations to competitive dynamics, capital cycles, and the fundamental shift toward intangible-driven business models that are changing how we think about valuation, moats, and market structure.Papers and Resources Discussed:Bayes and Base Rates: How History Can Guide Our Assessment of the Futurehttps://www.morganstanley.com/im/en-us/institutional-investor/insights/consilient-observer/bayes-and-base-rates.htmlThe Impact of Intangibles on Base Rateshttps://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdfMeasuring the Moat: Assessing the Magnitude and Sustainability of Value Creationhttps://www.morganstanley.com/im/publication/insights/articles/article_measuringthemoat.pdfOne Job: Expectations and the Role of Intangible Investmentshttps://www.morganstanley.com/im/publication/insights/articles/article_onejob.pdfCapitalism Without Capital: The Rise of the Intangible Economyhttps://books.google.com/books/about/Capitalism_without_Capital.html?id=J3SYDwAAQBAJA Better Estimate of Internally Generated Intangible Capitalhttps://pubsonline.informs.org/doi/10.1287/mnsc.2022.01703Underestimating the Red Queen: Measuring Growth and Maintenance Investmentshttps://www.morganstanley.com/im/publication/insights/articles/article_underestimatingtheredqueen.pdfExplaining the Recent Failure of Value Investinghttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3442539Guest Links:Michael Mauboussin TwitterTopics Covered:Why OpenAI’s projected growth would be unprecedented in market historyHow base rates provide a reality check on AI expectationsThe role of diffusion models and adoption curves in forecasting technologyWhy massive capital investment in AI may follow past boom-bust cyclesLessons from large-scale infrastructure projects and why timelines breakHow intangible assets change the distribution of business outcomesThe rise of “fat tails” and why more companies now massively win or failWho captures value in AI across the stack from chips to applicationsWhy competition may drive AI profits toward consumers, not producersHow accounting distorts intangible investment and misleads investorsTimestamps:00:00 Intro and OpenAI growth expectations vs historical base rates04:32 Why no company has ever achieved 100%+ sustained growth at scale08:47 Lessons from megaprojects and AI infrastructure buildouts13:18 Intangible assets and why outcomes now have fatter tails18:36 Why big tech is growing faster than historical precedents23:52 Where value accrues in AI and why consumers may benefit most28:21 Barriers to entry in AI including capital, talent, and scale32:47 The risk of overinvestment and historical parallels to past bubbles37:26 Game theory and competitive signaling in AI capital spending41:58 Why investment returns—not “asset light” narratives—drive value46:12 How accounting fails to capture intangible investment properly50:44 Breaking down SG&A into maintenance vs investment spending55:03 Why understanding reinvestment and ROI is the core investing skill59:18 Final thoughts on uncertainty, expectations, and base rates in AI

Episode metadata supplied by the publisher feed · Published Apr 2, 2026

Embed this episode

NOW PLAYING

Michael Mauboussin | AI, Base Rates, and Investing in the New Economy

0:00 1:01:44

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of Excess Returns?

This episode is 1 hour and 1 minute long.

When was this Excess Returns episode published?

This episode was published on April 2, 2026.

Can I download this Excess Returns episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!