Intangible Capital
Jonathan Haskel and Stian Westlake's Capitalism Without Capital documented the rising share of intangible investment in advanced economies and the systematic failure of national accounts to measure it adequately. Intangible assets are difficult to measure because they are non-rival (my use does not diminish yours), because they generate spillovers (their benefits extend beyond the firm that created them), and because their value is context-dependent (a patent is worth millions in one market and nothing in another). These characteristics make market valuation unreliable and accounting valuation essentially arbitrary. The AI transition intensifies every dimension of the intangible measurement problem.
In the AI Story
When Segal argues that value has migrated from code to judgment — from the tangible artifact of software to the intangible capacity to decide what software should exist — he is describing, in a builder's language, the shift from tangible to intangible capital that Coyle, Haskel, and Westlake have been documenting for a decade. Code is measurable: lines written, functions deployed, tests passed. Judgment is not measurable by any metric currently existing.
The 2008 revision of the UN System of National Accounts reclassified R&D as investment rather than expenditure — a major step forward in intangible measurement. But R&D is the most measurable form of intangible investment. The harder categories — organizational capability, managerial expertise, customer relationships, brand equity, design — remain largely outside the accounts. Coyle's advocacy for intangible measurement runs through her Bean Review work and her collaborations on investment measurement.
The AI economy makes intangibles central in a way they have never been. The judgment economy that Segal describes is an economy of intangibles — where the measurable output is increasingly commodity and the scarce input is the human capacity for evaluation, integration, and decision. A measurement system that cannot see intangibles will systematically undervalue the economy's most productive capital.
Coyle's February 2026 essay 'AI Will Transform Business, Not Just Jobs' extends this framework to organizational transformation. If AI's primary impact is on how firms make decisions rather than what they produce, then organizational capability — an intangible — becomes the determining variable of economic performance. Measuring it is harder than measuring output, but the measurement difficulty does not make the capability less consequential.
Origin
Intangible capital measurement developed from the 1960s onward through economists including Fritz Machlup and Edwin Mansfield. Carol Corrado, Charles Hulten, and Daniel Sichel produced the first systematic aggregate estimates in 2005. Haskel and Westlake's Capitalism Without Capital (2018) synthesized the literature. Coyle's engagement runs through her Bean Review contributions and her institutional work on measurement reform.
Key Ideas
Rising share. Intangible investment now exceeds tangible investment in most advanced economies, but national accounts capture it poorly.
Measurement properties. Non-rivalry, spillovers, and context-dependence make market valuation unreliable.
AI intensification. The shift from code to judgment accelerates the move toward intangibles that metrics cannot see.
Organizational centrality. If AI transforms decision-making, organizational capability becomes the determining intangible — and the hardest to measure.
Appears in the Orange Pill Cycle
Further reading
- Jonathan Haskel and Stian Westlake, Capitalism Without Capital: The Rise of the Intangible Economy (Princeton University Press, 2018)
- Carol Corrado, Charles Hulten, Daniel Sichel, 'Measuring Capital and Technology: An Expanded Framework', in Measuring Capital in the New Economy (NBER, 2005)
- Jonathan Haskel and Stian Westlake, Restarting the Future: How to Fix the Intangible Economy (Princeton University Press, 2022)