Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives

Baslandze, Salomé; Edwards, Zach; Graham, John; McClure, Ty; Meyer, Brent; Sparks, Michael; Waddell, Sonya Ravindranath; Weitz, Daniel J.

doi:10.29338/wp2026-04

Working Paper

Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives

Abstract: We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. These gains are not primarily driven by firms' capital deepening but instead reflect increases in revenue-based total factor productivity, closely associated with innovation- and demand-oriented channels. We document a productivity paradox, in which perceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations. In labor markets, we find little evidence of near-term aggregate employment declines due to AI, though larger companies anticipate AI-driven workforce reductions, while smaller firms expect modest gains. We also find evidence of compositional reallocation of labor both within and across firms, with routine clerical roles declining and a relative demand for skilled technical roles increasing. We develop an index that ranks job functions most negatively affected by AI.

JEL Classification: O33; D22; J24;

https://doi.org/10.29338/wp2026-04

Status: Published in 2026