Journal Article

Is Artificial Intelligence Driving Green Transformation? Evidence from GTFP in Chinese Manufacturing Firms

Jiang, Lingling, Wu, Wenlu, Hao, Wenjie

2026

Overview

Artificial intelligence (AI) is rapidly reshaping firms’ production and organisational processes, yet whether it can serve as a driving force for corporate green transformation remains an open question. Using a sample of Chinese listed manufacturing firms from 2012 to 2023, this study systematically examines the relationship between AI and firms’ green total factor productivity (GTFP), and explores potential underlying mechanisms. At the theoretical level, drawing on the task-driven nature of AI as a form of technological innovation, this study proposes that AI may enhance GTFP through two channels, namely the structural labour reallocation effect and the managerial dissipation reduction effect. The empirical results show the following: (1) Firms’ AI technical level is significantly associated with improvements in GTFP. (2) Mechanism tests indicate that AI is significantly related to an increasing share of creative task employees and a declining share of structural task employees, thereby providing empirical evidence for the structural labour reallocation effect. Moreover, from four dimensions, including information dissipation, resource allocation dissipation, process coordination dissipation, and incentive and learning dissipation, this study provides supportive evidence that AI is linked to reduced managerial dissipation. (3) Heterogeneity analysis suggests that this association is more pronounced among firms with greater scope for green improvement, such as non-heavily polluting firms and those characterised by managerial myopia. Overall, this study deepens the understanding of the relationship between AI and GTFP from the perspectives of labour structure and corporate organisation, and emphasises that AI’s contribution to firms’ GTFP is more likely to arise as a systemic facilitation embedded in production and organisational processes, rather than through the direct substitution of specialised green technologies.

• Publisher: MDPI AG
• Subject: Artificial intelligence / Carbon / Chatbots / Computational linguistics / Economic incentives / Efficiency / Green technology / Human capital / Incentives / Innovations / Language processing / Manufacturing / Natural language interfaces / Production factors / Production planning / Productivity / Resource allocation / Technology