Economic Scenarios for Transformative AI - Working Paper No. 2026-02

Sep 18, 2026

Uploaded by Violet

This paper presents a framework for assessing the economic consequences of AI between 2026 and 2030. The model captures how AI automation of cognitive work boosts productivity while displacing workers who must reallocate across occupations. It maps AI capability paths to GDP, labor share, wages, labor reallocation, and unemployment. Three scenarios—modest, substantial, and extreme—quantify growth, unemployment, and labor-share shifts, and the authors also survey US adults’ expectations.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages57

Reading Time2 h 24 min

AccessFree to download

Introduction

Model

Production and factor shares

Innovation

Unemployment

Calibration

Parameters related to production functions

Normal times

The pace of AI

Disruptiveness

What do US adults expect?

Results

The modest change scenario

The substantial change scenario

The extreme change scenario

The scenarios implied by survey responses

Robustness: supply of capital

Robustness: wage rigidity

Conclusions

Appendix

References

Economic Scenarios for Transformative AI∗ Anton Korinek, Charles I. Jones, Szymon Sacher, Tess Cotter, and Peter McCrory The Anthropic Institute Working Paper No. 2026-02 September 2026 Abstract This paper presents a framework for assessing the economic consequences of AI between 2026 and 2030 . In the model, AI automates a growing share of cognitive work, raising productivity and displacing workers who must search for jobs in other occupations. The model maps future paths of AI capabilities into implied paths for GDP, the labor share, wages, labor reallocation, and unemployment. We illustrate the framework by considering three scenarios: modest, substantial, and extreme. Under modest change, AI adds less than half a point to GDP growth by 2030 and raises unemployment by a tenth of a point. In the extreme change scenario, AI has transformative effects, with AI performing almost half of today’s cognitive work by 2030 . GDP growth then rises to 15 percent per year, the labor share of income falls from 60 to 45 percent, and nearly one in five cognitive workers is unemployed. We also surveyed US adults about their expectations for AI. Views vary widely, but the median respondent’s answers are consistent with our substantial change scenario in which, by 2030, GDP rises by 8 percent and cognitive employment declines by 4 percent. The model offers a structured way to compare possibilities for our economic future under different expectations about AI. ∗We would like to thank Daron Acemoglu, Lukas Althoff, David Autor, Tom Cunningham, Lukas Freund, Joe Hazell, Johannes Hermle, Zoë Hitzig, Ben Jones, Pete Klenow, Danial Lashkari, Eva Lyubich, Kurt Mitman, Ben Moll, Emi Nakamura, Tomas Philipson, Pascual Restrepo, David Romer, Jón Steinsson, Chris Tonetti, Ludo Visschers, and David Wiczer for insightful comments on an earlier version of this paper. We used Claude as a research and writing assistant. The views expressed in this paper are those of the authors and do not necessarily represent the views of Anthropic or The Anthropic Institute. Any remaining errors are ours. ECONOMIC SCENARIOS FOR TRANSFORMATIVE AI Contents 1 Introduction 3 2 Model 6 2. 1 Production and factor shares . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.3 Unemployment ................................... 18 3 Calibration 22 3.1 Parameters related to production functions .................... 25 3.2 Normal times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.3 The pace of AI .................................... 27 3.4 Disruptiveness .................................... 27 3.5 What do US adults expect? ............................. 29 4 Results 31 4.1 The modest change scenario ............................ 31 4.2 The substantial change scenario .......................... 32 4.3 The extreme change scenario ............................ 34 4.4 The scenarios implied by survey responses .................... 35 4.5 Robustness: supply of capital ............................ 36 4.6 Robustness: wage rigidity .............................. 37 5 Conclusions 38 Appendix 40 References 52 Suggested citation for this paper: Korinek, Anton, Charles I. Jones, Szymon Sacher, Tess Cotter, and Peter McCrory. 2026.“Economic Scenarios for Transformative AI.” The Anthropic Institute Working Paper No. 2026-02. ECONOMIC SCENARIOS FOR TRANSFORMATIVE AI 1. Introduction AI is likely to reshape the U.S. and global economies in profound ways in the coming decade, but how, and by how much, is extraordinarily uncertain. Published estimates of AI’s future impact on productivity span orders of magnitude, and forecasts of its effect on employment range from negligible to catastrophic. Many of the estimates are based on differing analytical frameworks, which makes the projections hard to compare. Thi

FAQs

What economic outcomes does the model project for 2026 to 2030?

It links future AI capability paths to GDP, the labor share of income, wages, labor reallocation across occupations, and unemployment levels.

How do the modest and extreme change scenarios differ in main results?

Under modest change, AI adds less than half a point to GDP growth by 2030 and raises unemployment by about a tenth of a point; under extreme change, AI performs almost half of today’s cognitive work by 2030, driving GDP growth to roughly 15% per year while unemployment rises sharply and the labor share falls.

How are US adult expectations incorporated into the analysis?

The authors survey US adults about their expectations for AI, and compare scenario outcomes with the survey-implied path, where median responses align with the substantial change scenario by 2030.

Sep 18, 2026

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