"Marketing economist studying what organizations actually do with cheap prediction."
Avi Goldfarb is a professor of marketing at the University of Toronto's Rotman School of Management, where he studies how digital technologies reshape marketing and competitive strategy. With longtime co-authors Ajay Agrawal and Joshua Gans, he helped popularize the idea of AI as a drop in the cost of prediction in Prediction Machines, and in Power and Prediction turns to why that cheaper prediction so often fails to translate into organizational advantage. His research consistently asks not just what AI can do, but what it's economically rational for an organization to do with it.
Our in-depth summaries and reviews of his work
Power and Prediction summary & review: Agrawal, Gans & Goldfarb's sequel to Prediction Machines argues the real AI payoff comes from redesigning…
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Prediction Machines by Agrawal, Gans & Goldfarb explains AI as a drop in the cost of prediction — and why human judgment…
Read Summary →Goldfarb studies how digital technologies change marketing, competitive strategy, and consumer behavior.
In Power and Prediction, he helps explain why system-level AI redesign threatens existing power structures, not just habits.
With Agrawal and Gans, Goldfarb helped reframe AI adoption as an economic question of when prediction becomes cheap enough to change behavior.
"Resistance to a system solution is rarely about the technology — it's about who holds power over the decision."— Power and Prediction
Power and Prediction summary & review: Agrawal, Gans & Goldfarb's sequel to Prediction Machines argues the real AI payoff comes from redesigning decision systems, not just cheaper predictions.
Prediction Machines by Agrawal, Gans & Goldfarb explains AI as a drop in the cost of prediction — and why human judgment becomes more valuable, not less. Summary, key concepts, and a 7-day plan.
