AI Brings Cheap Prediction, Expensive Change
Avi Goldfarb
Economist and Co-author of Prediction Machines
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Season 7 Episode 4
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Most organizations are still implementing AI as point solutions, dropping new technology into existing workflows to do the same work, just slightly better. The real value lies in system solutions that completely transform how organizations operate. Avi Goldfarb, economist and co-author of Prediction Machines, joins Robb and Josh to explain why AI adoption follows predictable economic principles and why internal resistance, not technology limitations, is the primary barrier to transformation.
This conversation, recorded back in 2023, reminds us that most organizations continue to struggle with the same issues surrounding systemic change in 2026. Goldfarb’s core argument: AI is fundamentally cheap prediction. Just as the internet made search and copying cheap, AI makes prediction cheap. When something becomes a commodity, the complements, the things that work alongside it, become more valuable. This includes compute power (benefiting Microsoft, Amazon, Google), unique data, and crucially, human judgment.
The problem? System solutions require organizational transformation. They create winners and losers inside companies. When AI enables insurance companies to shift from pricing risk (the domain of powerful underwriters) to reducing risk (requiring marketing and behavior change expertise), the power structure fractures. Vested interests resist. Departments see their importance diminished. For leaders evaluating AI investments, the question isn’t whether to adopt AI, it’s whether you’re willing to pursue system transformation and confront the organizational disruption that creates real value.
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About the guest
Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and Professor of Marketing at the Rotman School of Management, University of Toronto. He is also Chief Data Scientist at Creative Destruction Lab–Toronto, a Research Associate at the National Bureau of Economic Research, a Distinguished Fellow at The Hebrew University of Jerusalem, and a research lead at the Acceleration Consortium.
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