Displacement or Augmentation? The Effects of AI Innovation on Workforce Dynamics and Firm Value

Abstract

This paper studies the effects of Artificial Intelligence (AI) innovation on firm-level employment dynamics and corporate valuation. Applying state-of-the-art large language models (LLMs) and Generative AI to U.S. patent data during 2007-2023, we identify AI-related innovations in seven key functional areas. Using microdata on individual workers’ skills and job transitions, we find that AI innovations related to engagement, learning, or creativity augment human labor, but those related to perception displace it. Augmenting AI innovations raise firm-level productivity, while displacing AI innovations lower operating costs. We also find that augmenting (displacing) AI innovations yield more (less) positive valuation effects when the innovating firm has better access to prospective hires (higher costs of terminating employees). Overall, our findings suggest that AI innovations can bring large potential value gains to innovating firms, but how much of those gains are realized depends critically on what frictions are present in the external labor market.

Keywords: Artificial Intelligence, firm innovation, patents, labor augmentation, labor displacement, large language models, firm value

JEL Classification: G30, G32, O32, O33