Messy jobs:
The work that AI Cannot Reach
By
Luis Garicano, Jin Li, and Yanhui Wu
“The authors use simple, powerful logic to illuminate how AI will reshape work and organizations.”
— Bengt Holmström, Nobel Prize-winning economist (2016)
on sale June 2026
Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. When people hear that AI can now write, code, and diagnose, many jump to a scary conclusion: If machines can think, human work is doomed. Messy Jobs argues that this gloomy belief gets the economics of work wrong.
Economists Luis Garicano, Jin Li, and Yanhui Wu show that the future of work will be shaped by the messy parts of jobs that machines struggle to master: judgment, coordination, accountability, tacit knowledge, and human relationships.
Drawing on organizational economics, recent evidence, and examples across industries, the authors show which careers are most vulnerable, which will endure, and how workers and organizations can adapt when cognition becomes cheap.
Messy Jobs is a clear and optimistic guide to work, opportunity, and human value in the age of AI.
What People Are Saying
-
Messy Jobs is a brilliant application of price theory ... When intelligence becomes cheap, judgment, coordination, trust, and responsibility become more valuable. The authors use this simple, powerful logic to illuminate how AI will reshape work and organizations.”
— Bengt Holmström, Nobel Prize-winning economist (2016) and MIT professor of economics
-
A rigorous, original, and engaging account of how AI will reshape organizations and labor markets, and what it will take to thrive in them.
— Raffaella Sadun, Charles Edward Wilson Professor of Business Administration, Harvard Business School
-
The economics analysis is lucid and penetrating, and the book pinpoints where human agency will remain paramount. The book is hopeful and practical for anyone charting a career in the coming decade.
— David Autor, MIT professor of economics
-
Messy Jobs is the definitive text on how AI will affect the labor market. The book is an impressive feat of combining academic rigor with clear explanations and concrete examples. I would recommend this book to anyone interested in learning about what comes next.
— Alex Imas, director of AGI Economics at Google DeepMind and professor of economics and applied AI at the University of Chicago Booth School Business
-
This book isn’t just some economist’s armchair theorizing; it’s a practical guide. I hope you get as much out of it as I did.
— Evan Guo, CEO of Zhaopin Group, the largest career development platform in China
-
There is a lot of wooly thinking on the topic of AI and jobs. This excellent book contains by far the most thoughtful and economically literate account that has yet been written.
— Patrick Collison, CEO, Stripe
-
AI is not going to lead to mass unemployment, and this is the best book to explain why not. It also illuminates how labor markets are likely to evolve. It is short, to the point, eminently readable, and of extreme relevance.
— Tyler Cowen, professor of economics at George Mason University
About the authors
-
Luis Garicano
Luis Garicano is a professor at the London School of Economics whose work focuses on how technology affects organizations, expertise, and the economy as a whole.
-
Jin Li
Jin Li is a professor at the University of Hong Kong where he leads the Centre for AI, Management, and Organization. His research focuses on organizational economics, career dynamics, management and strategy.
-
Yanhui Wu
Yanhui Wu is a professor at the University of Hong Kong and the head of its department of economics. His research spans organizational economics, media economics, and digital economy. Prior to his academic career, he was an award-winning journalist in China.
Messy Jobs: The Work That AI Cannot Reach
© 2026 by Luis Garicano, Jin Li, and Yanhui Wu
Published by Upriver Press
ISBN Paperback: 9798995221906
ISBN Ebook: 9798995221913