Diffusion, Early Adoption, and Triangulating TAM

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.

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The 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 Future
https://www.morganstanley.com/im/en-us/institutional-investor/insights/consilient-observer/bayes-and-base-rates.html

The Impact of Intangibles on Base Rates
https://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdf

Measuring the Moat: Assessing the Magnitude and Sustainability of Value Creation
https://www.morganstanley.com/im/publication/insights/articles/article_measuringthemoat.pdf

One Job: Expectations and the Role of Intangible Investments
https://www.morganstanley.com/im/publication/insights/articles/article_onejob.pdf

Capitalism Without Capital: The Rise of the Intangible Economy
https://books.google.com/books/about/Capitalism_without_Capital.html?id=J3SYDwAAQBAJ

A Better Estimate of Internally Generated Intangible Capital
https://pubsonline.informs.org/doi/10.1287/mnsc.2022.01703

Underestimating the Red Queen: Measuring Growth and Maintenance Investments
https://www.morganstanley.com/im/publication/insights/articles/article_underestimatingtheredqueen.pdf

Explaining the Recent Failure of Value Investing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3442539

Guest Links:

Michael Mauboussin Twitter

Topics Covered:

• Why OpenAI’s projected growth would be unprecedented in market history

• How base rates provide a reality check on AI expectations

• The role of diffusion models and adoption curves in forecasting technology

• Why massive capital investment in AI may follow past boom-bust cycles

• Lessons from large-scale infrastructure projects and why timelines break

• How intangible assets change the distribution of business outcomes

• The rise of “fat tails” and why more companies now massively win or fail

• Who captures value in AI across the stack from chips to applications

• Why competition may drive AI profits toward consumers, not producers

• How accounting distorts intangible investment and misleads investors

Timestamps:

00:00 Intro and OpenAI growth expectations vs historical base rates
04:32 Why no company has ever achieved 100%+ sustained growth at scale
08:47 Lessons from megaprojects and AI infrastructure buildouts
13:18 Intangible assets and why outcomes now have fatter tails
18:36 Why big tech is growing faster than historical precedents
23:52 Where value accrues in AI and why consumers may benefit most
28:21 Barriers to entry in AI including capital, talent, and scale
32:47 The risk of overinvestment and historical parallels to past bubbles
37:26 Game theory and competitive signaling in AI capital spending
41:58 Why investment returns—not “asset light” narratives—drive value
46:12 How accounting fails to capture intangible investment properly
50:44 Breaking down SG&A into maintenance vs investment spending
55:03 Why understanding reinvestment and ROI is the core investing skill
59:18 Final thoughts on uncertainty, expectations, and base rates in AI