From adoption to empowerment: How artificial intelligence enhances firm productivity

IF 5.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences Pub Date : 2026-10-01 Epub Date: 2026-09-28 DOI:10.1016/j.seps.2026.102619

Wantong Yang, Ning Zhang

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引用次数: 0

Abstract

This study examines how artificial intelligence (AI) adoption reshapes firm productivity and supports organizational and environmental transformation. Drawing upon a firm-level panel dataset covering Chinese publicly traded companies between 2003 and 2022, we develop a firm-level AI adoption indicator based on asset structure and apply a multi-dimensional fixed effects model with double machine learning to identify causal effects. Results show that AI significantly enhances total factor productivity (TFP), with stronger impacts in state-owned, high-technology, pollution- and capital-intensive firms, and in regions with weaker institutional environments. Mechanism analysis suggests that AI facilitates internal restructuring, supply chain optimization, and operational efficiency gains. Moreover, AI adoption is linked to nonlinear stock market responses and lower pollution intensity, revealing both financial and green spillovers. This study sheds light on the economic implications of AI adoption from a micro-level perspective and provides empirical foundations for understanding the organizational restructuring and performance feedback associated with digital transformation in firms.

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从采用到授权：人工智能如何提高企业生产力

本研究探讨人工智能（AI）的采用如何重塑企业生产力，并支持组织和环境转型。利用涵盖2003年至2022年中国上市公司的企业层面面板数据集，我们开发了基于资产结构的企业层面人工智能采用指标，并应用具有双重机器学习的多维固定效应模型来识别因果关系。结果表明，人工智能显著提高了全要素生产率，在国有企业、高技术企业、污染密集型企业和资本密集型企业以及制度环境较弱的地区，这种影响更为明显。机制分析表明，人工智能有利于企业内部重组、供应链优化和运营效率提升。此外，人工智能的采用与非线性股票市场反应和较低的污染强度有关，揭示了金融和绿色溢出效应。本研究从微观层面揭示了人工智能应用的经济影响，并为理解企业数字化转型相关的组织重组和绩效反馈提供了实证基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Socio-economic Planning Sciences OPERATIONS RESEARCH & MANAGEMENT SCIENCE-

CiteScore

9.40

自引率

13.10%

发文量

294

审稿时长

58 days

期刊介绍： Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry. Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution. Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.