What is Power and Prediction: The Disruptive Economics of Artificial Intelligence about?

Power and Prediction is the second book from Ajay Agrawal, Joshua Gans, and Avi Goldfarb — the economists behind Prediction Machines — and it takes a more pointed look at what cheap AI-driven prediction actually disrupts. Where Prediction Machines argued that AI reduces the cost of prediction, Power and Prediction asks what happens when that cost reduction starts threatening the rules, roles, and power structures that were built around expensive prediction.

The core argument is that AI creates disruption at the system level, not just at the task level. The authors introduce a distinction between point solutions — AI tools that improve a specific decision within an existing workflow — and system solutions — redesigns of entire decision-making architectures made possible by cheap prediction. Most current AI deployments are point solutions: they make an existing process faster or more accurate without changing the underlying structure. The disruptive wave comes when organizations and industries redesign their rules, roles, and workflows around what AI can now do cheaply.

This is where power enters the analysis. Existing institutions, professional bodies, and incumbents often have their power rooted in controlling prediction. Doctors decide treatment because diagnosis was expensive and required expert judgment. Judges sentence because predicting recidivism required interpretation. Managers allocate because forecasting outcomes required experience. When prediction becomes cheap and accurate, the distribution of decision-making authority can — and eventually will — change. The question is whether incumbents will capture the gains from AI or whether disruption will shift power to new entrants or directly to end users.

The authors are economists first and the writing reflects that: the argument is precise and the frameworks are clear, but the book is more analytical than narrative. It is less concerned with what AI will do at the task level than with who will benefit from AI at the institutional level. For strategists, policymakers, and anyone thinking about what AI does to competitive advantage, the analysis is sharper and less breathless than most of the genre.