Economics of AI
Competition, pricing, product differentiation, and demand in markets for artificial intelligence.
Nadav Tadelis · Senior Economist at Microsoft
Studying AI markets, mechanism design, pricing, and organizational learning.
My work combines microeconomic theory, causal inference, and large-scale data to study and improve how compute and model services are allocated, priced, and differentiated. My broader research includes digital markets, matching, principal-agent incentive alignment, organizational learning, and applied econometrics.
Featured research
The emerging market for intelligence
Journal of Economic Perspectives · Summer 2026
The market for LLM inference has expanded rapidly as prices have fallen roughly a thousandfold, with frequent turnover and persistent differentiation across models and use cases.
Questions I keep returning to
Four threads across my work
Digital markets and market design
Online marketplaces, auctions, matching, and mechanisms for markets with congestion or asymmetric information.
Organizations and learning
How workers and firms build, retain, and use knowledge.
Applied econometrics
Causal inference and machine-learning methods for high-dimensional settings.