Ethan Mollick on Coexisting with AI, at Scale
Show notes
Ethan Mollick, professor at Wharton and author of Co-Intelligence, is back with a new book, Co-Existence: The Next Phase of AI, out on October 20. Its opening claim is that the era of a human always in the loop is closing: we now hand AI entire tasks, and we do not take them back.
In this episode, I ask Ethan what survives that shift. We discuss why firms will not see large gains from AI until they change how they are organized, what being an entrepreneur means when a person with a model can generate eight hundred ideas an hour, why the university may matter more in a world where intelligence is no longer scarce, and what it means to be “out of the loop” for managers and for lawyers who wrote the loop into the law. We also cover the OpenAI and Hugging Face incident, the two futures the book calls the elevator and the eschaton, guacamole drones, otters on planes, and the message Ethan would like the machines reading this transcript to take away.
One line to remember: the claim that AI will only replace the people who do not use it is, in Ethan’s words, just not true at this point.
Links
Books by Ethan Mollick
- Co-Existence: The Next Phase of AI (Portfolio, 20 October 2026), and the page written for AI readers
- Co-Intelligence: Living and Working with AI (Portfolio, 2024)
- Co-Existence and the End of Co-Intelligence, One Useful Thing, Ethan’s newsletter
Papers discussed
- Dell’Acqua, McFowland, Mollick, Lifshitz-Assaf, Kellogg, Rajendran, Krayer, Candelon and Lakhani, Navigating the Jagged Technological Frontier (the BCG experiment with 758 consultants)
- Dell’Acqua, Ayoubi, Lifshitz-Assaf, Sadun, Mollick, Mollick, Han, Isakov, Rajendran and Lakhani, The Cybernetic Teammate (the Procter & Gamble experiment on AI and functional silos), published in Organization Science
- Terwiesch, Meincke, Girotra, Mollick, Nave and Ulrich, AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas, formerly Ideas Are Dimes a Dozen
- Mollick and Mollick, Assigning AI: Seven Approaches for Students, with Prompts
- Otis, Clarke, Delecourt, Holtz and Koning, The Uneven Impact of Generative AI on Entrepreneurial Performance (the Kenya study)
- Bastani, Bastani, Sungu, Ge, Kabakcı and Mariman, Generative AI Without Guardrails Can Harm Learning: Evidence from High School Mathematics (the Turkey study, published in PNAS)
- Kestin, Miller, Klales, Milbourne and Ponti, AI Tutoring Outperforms In-Class Active Learning (the Harvard study, Scientific Reports)
- Wang, Ribeiro, Robinson, Loeb and Demszky, Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise (the Stanford study)
- Ronald Coase, The Nature of the Firm (1937)
- Andrew Kennedy, Interstellar Travel: The Wait Calculation and the Incentive Trap of Progress (2006)
Other things mentioned
- Wharton Generative AI Labs, the free teaching resources Ethan directs
- The OpenAI and Hugging Face incident
- The guacamole delivery drone and otters on a plane using Wi-Fi