How fast could an AI-driven economy grow? Most economists expect a few percentage points at best, comparable to previous general-purpose technologies (Acemoglu (2024)). Those closer to AI development tend to imagine something much more radical (Shulman (2023); Davidson and Hadshar (2025)).

This series aims to ground growth rates in how physical production works. Once human labor is automated, the constraint on growth becomes the speed at which the economy's physical capital can reproduce itself. Government input-output tables track the full supply chain of what it takes to produce every commodity in the economy, and we can use them to compute this self-reproduction rate directly.

In this post, I compute the maximum rate at which an autonomous AI economy could grow, once its production is concentrated in the sectors most important for self-replication. I take the conservative case for this calculation: full automation, but no other technological improvement. Using US input-output data, I find this economy could double in about a year, in line with other estimates that assume full automation (Hanson (2001); Trammell and Korinek (2023); Davidson and Hadshar (2025); Epoch AI (2025)). This holds up even after accounting for resource depletion and construction lags. Some output [...]

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Outline:

(03:45) If labor were free, the economy could grow very fast

(06:50) AGI makes labor approximately free

(12:11) Resource extraction is unlikely to significantly slow growth

(15:13) Construction lags do not prevent rapid growth

(18:27) Consumption does not preclude rapid growth

(20:12) Summary

(22:00) Appendix A: The input-output formulation

(22:05) A.1 The material-balance identity

(24:45) A.2 The balanced-growth path and the Perron eigenvalue

(25:41) A.3 Construction lags

(27:37) A.4 Data sources

(27:42) The intermediate-input matrix

(28:49) The capital-requirements matrix

(31:13) The depreciation matrix

(32:32) Government infrastructure

(33:27) Capacity utilization

(35:44) Robot and compute sectors

(37:59) Appendix B: Von Neumann growth rates are similar across industrial economies

(40:30) Appendix C: Resource extraction

(40:35) C.1 Minerals

(40:50) The grade-cost scaling law

(42:09) Skinners mineralogical barrier

(43:19) Iron

(43:58) Aluminum (bauxite)

(44:41) Copper

(47:50) Nickel

(49:15) Lithium

(49:47) Cobalt

(50:24) Manganese

(50:49) Rare earth elements

(52:11) Platinum group metals

(52:49) Deep-sea mining

(54:01) Summary table

(55:15) C.2 Fossil fuels

(56:17) Oil

(58:30) Natural gas

(01:00:13) Coal

(01:01:28) Summary

(01:02:25) C.3 Electrification

The original text contained 2 footnotes which were omitted from this narration.

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First published:
May 4th, 2026

Source:
https://www.lesswrong.com/posts/rpqGWRoRWvqJ4Hqgn/ai-industrial-takeoff-part-1-maximum-growth-rates-with

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Narrated by TYPE III AUDIO.

“AI Industrial Takeoff — Part 1: Maximum growth rates with current technology” by djbinder

LessWrong (30+ Karma)