AI as Prediction: Key Ideas from Dr. Joshua Gans’ “The Microeconomics of Artificial Intelligence”

In this episode, host Deepak Bhatt speaks with Dr. Joshua Gans, Jeffrey S. Cole Chair of Technical Innovation and Entrepreneurship and Professor of Strategic Management at the Rotman School of Management, University of Toronto, about key ideas from his book The Microeconomics of Artificial Intelligence and what they mean for organizations and markets. Dr. Gans frames AI primarily as a prediction technology (advanced statistics at scale) rather than simple automation and introduces a practical “prediction + judgment” lens: AI can improve predictions, but humans still supply judgment about goals, trade-offs, and preferences. The conversation also outlines four modes of AI deployment replacement, augmentation, unreliable, and antagonistic highlighting the counterintuitive case for “unreliable AI” in high-stakes settings where over-trusting near-perfect systems can reduce human vigilance. Beyond decision-making, Dr. Gans discusses how AI prediction may reshape insurance through finer-grained risk assessment and explores supply-chain implications such as “ship then shop” (anticipatory fulfillment), emphasizing that AI’s value often depends on complementary changes in systems and processes. This podcast is brought to you by Global Management Consultancy. For more information, please visit www.globalmanagementconsultancy.com. Disclaimer: A. The background music used in this video is the property of its respective developer and is protected by Copyright. Although it is a free version, Business Talk, Global Management Consultancy and Deepak Bhatt do not hold the rights to this music. B. Dr. Joshua Gans offered thoughtful perspectives from his acclaimed book, “The Microeconomics of Artificial Intelligence”, in his conversation on the Business Talk podcast channel. The uploaded video contains copyrighted material; therefore, any modifications to graphics, music, or the presence of the author or host are strictly prohibited.