Data-Driven Automation

2026-06-08

AI Summary

This study investigates the long-run implications of data-driven automation for economic structure, wages, and growth, integrating task heterogeneity of data, endogenous accumulation, and cross-task spillovers within a unified dynamic general equilibrium framework. The model captures data’s dual role in enhancing productivity in already automated tasks and expanding the frontier of automatable tasks. Combining endogenous growth theory with optimal control methods, the analysis reveals that under market equilibrium, labor’s share declines according to a power law and real wages stagnate in the long run. While full automation can generate explosive growth, the decentralized equilibrium is generally inefficient. The paper demonstrates that a social planner can achieve a Pareto improvement by steering the direction of data accumulation toward socially optimal automation pathways.

Abstract

We build a dynamic model of data-driven automation in which data (i) is heterogeneous and task-specific; (ii) accumulates endogenously as a byproduct of economic activity; and (iii) exhibits spillovers such that data generated by one task can augment the productivity of another. Along the transition path of automation, data plays a dual role in simultaneously augmenting the productivity of already-automated tasks and expanding the automation frontier. We derive tight conditions for the economy to be partially versus fully automated in the long-run. In the latter case, automation exhibits rich short-run dynamics that depend on the pattern of data spillovers but is always slow in the long-run: the share of tasks produced by labor decays asymptotically as a power law in time. We show that the economy is generically inefficient and analyze how a planner optimally tilts the direction of data accumulation. With endogenous capital accumulation, data-driven automation generates explosive growth but stagnant long-run wages.

Problem

• data-driven automation
• data spillovers
• endogenous data accumulation
• automation frontier
• economic inefficiency

Innovation

• data-driven automation
• endogenous data accumulation
• data spillovers
• automation frontier
• power-law decay