Alex Wanninger
This paper studies whether the diffusion of generative AI (LLMs) is associated with faster firm-level productivity growth and how complementary assets shape the gains. Using US listed non-financial firms over 2018–2024 (2,318 firms; 16,226 firm-years), we construct (i) a predetermined industry-level LLM exposure index and (ii) a firm-level adoption proxy from EDGAR 10-K disclosures based on LLM-related keyword intensity. We estimate a difference-in-differences specification around the post-2022 generative AI shock. Firms with higher exposure exhibit significantly higher TFP after 2023 (β = 0.017, SE = 0.006). The effect is stronger among intangible-intensive firms (additional η = 0.011, SE = 0.004). At the same time, exposed firms display a decline in labor share (β = −0.007, SE = 0.002), consistent with a shift in rent sharing. The results highlight growth gains that are amplified by intangible capital and accompanied by distributional changes.
Alex Wanninger, Independent Researcher, University of Zurich (UZH), Switzerland.
Wanninger, A. (2026). Generative AI Adoption and Firm-Level TFP Growth: Diffusion, Complementarities, and Rent Sharing in US Listed Firms. Econ Dev Glob Mark, 1(1), 01-08.