The Economics of Transformative AI
S · Shapes the field NBER conference volume edited by Agrawal, Brynjolfsson and Korinek with chapters by Athey, Restrepo, Stiglitz, Mullainathan, Jones and others; it sets the research agenda for the economics of advanced AI.
Summary based on the abstract only·Original: about 10 hours to read
In short
The Economics of Transformative AI is an NBER volume edited by Ajay Agrawal, Erik Brynjolfsson and Anton Korinek, published by the University of Chicago Press in September 2026. It asks what happens to an economy when machines can think as well as or better than humans, across sixteen studies on innovation, market structure, employment, inequality and human purpose. This digest is based on the publisher description and table of contents; the chapters themselves were not read, and no open PDF was found.
Key numbers
- 16studies in the volume, each with a published discussant comment
- 18-19 September 2025NBER conference the volume comes from; published September 2026 by University of Chicago Press
As reported by the source.
English·Web page·opens digitaleconomy.stanford.edu
What it reports
What the description and contents show, without chapter findings:
- Value and growth: Agrawal, Gans and Goldfarb on "Genius on Demand"; Benjamin F. Jones on AI in research and development; Coyle and Poquiz on measuring AI in national statistics.
- Markets and firms: Athey and Scott Morton on competition and welfare; Hadfield and Koh on an economy of AI agents; Shahidi, Rusak, Manning, Fradkin and Horton on market design with AI agents ("The Coasean Singularity?"); Chatterji, Rock and Talamàs on transformative AI and firms.
- Work: Manning and Aguirre on how adaptable American workers are to AI-induced displacement; Restrepo on work and growth in an AGI world ("We Won't Be Missed"); Stevenson on what there is to fear after AGI.
- Knowledge and science: Brynjolfsson and Hitzig on AI's use of knowledge in society; Mullainathan and Rambachan on science; Ludwig, Mullainathan, Pink and Rambachan on algorithms and behavioral economics.
- Policy and risk: Stiglitz and Ventura-Bolet on the information ecosystem; Korinek and Lockwood on public finance; Charles I. Jones on how much to spend reducing existential risk.
How they got it
Papers were presented at an NBER conference on 18-19 September 2025; each chapter carries a comment from a second economist (for example Luis Garicano, Bronwyn Hall, Catherine Tucker, Neil Thompson). Methods vary by chapter, from theory to empirical work; they could not be checked here.
Limits
- Only the description and contents were accessible; no findings or numbers from the chapters are reported.
- Many chapters assume AI that matches or exceeds human cognition, which is a scenario, not a forecast.
- Conference drafts are a year older than the publication date.
Why it matters for companies
This volume is where the economists that policymakers listen to set out how they will frame advanced AI: agents as market participants, firms reorganised around AI, worker adaptability and tax policy. Three chapters bear most directly on management decisions: Chatterji, Rock and Talamàs on firms, Manning and Aguirre on displacement and adaptability, and Hadfield and Koh on agent economies. Read those first once the text is available.
Summary based on the abstract only. Read the original for the full argument and data.Read the original on digitaleconomy.stanford.edu