By Luis Garicano, Jin Li, and Yanhui Wu

On Sale June 2026

Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. When people hear that AI can write, code, and diagnose, many jump to a scary conclusion: If machines can think, then 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.

About the Authors

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 is a professor at the Hong Kong University where he leads the Centre for AI, Management, and Organization. His research focuses on organizational economics, career dynamics, management and strategy.

Yanhui Wu is a professor at the Hong Kong University 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.

Copyright © 2026 by Luis Garicano, Jin Li, and Yanhui Wu

Published by Endeavor Literary Press

Cover Design: James Clarke (jclarke.net)

ISBN Paperback: 9798995221906

ISBN Ebook: 9798995221913

No AI was used to write, edit, design, or publish this book.