Comment on: Is it AI or data that drives market power?

This paper is a published comment by Miao Ben Zhang (USC Marshall School of Business) on Mihet, Rishabh, and Gomes (2025), “Is It AI or Data That Drives Market Power?” Zhang identifies three contributions of the commented paper and benchmarks each against the existing literature, offering targeted suggestions for strengthening the analysis.

The first contribution Zhang discusses is the commented paper’s distinction between raw data, AI capability, and processed data. Raw data is modeled as a by-product of production linearly related to firm size; processed data is modeled as the abundance of signals improving the precision of firms’ next-period productivity predictions. The commented paper’s key modeling innovation is a formula linking raw data (n_{i,t}), firm-level AI capability (z_i), and processed data (n_{i,t}-tilde): processed data equals a weighted sum of an information entropy effect — e^(-z_i) * (-n_{i,t} * ln(n_{i,t})) — and an AI capability effect — (1 - e^(-z_i)) * n_{i,t} * e^(n_{i,t}). Zhang notes this formula implies that the marginal value of raw data can turn negative for firms with low AI capability, consistent with information-theoretic constraints from the rational inattention literature (Sims, 2003). Zhang requests more empirical support for this equation, specifically asking whether low-AI firms exhibit lower TFP than high-AI firms at similar data-intensity levels, and encouraging discussion of existing measures of data-processing ability such as human capital in data engineering and ML pipeline automation.

Miao Ben Zhang | Macro Paper Warehouse

Comment on: Is it AI or data that drives market power?