人工智能技术使用如何影响企业ESG责任表现？

——来自A股上市公司的证据

周路路¹　桂家欣¹　赵曙明²　黄海艳³

（1.东南大学；2.南京大学；3.南京审计大学）

内容提要：人工智能技术使用在提升企业生产效率和决策能力的同时，给企业环境、社会和治理（ESG）责任履行带来了新的挑战与机遇。本文使用2010—2023年中国A股上市公司数据，基于资源编排理论实证检验人工智能技术使用对企业ESG责任表现的影响及其作用机制。研究发现，人工智能技术使用对企业ESG责任表现具有促进作用。机制分析结果表明，人工智能技术使用通过提升企业内部控制质量、增强信息透明度和推动绿色创新能力来促进企业ESG责任表现。进一步研究结果显示，在大规模、高管环保认知较高、非重污染的企业中，人工智能技术使用对企业ESG责任表现的提升效果更加明显。本文不仅丰富和拓展了人工智能技术使用与企业ESG责任表现的相关研究，也为推动上市公司更好地实现高质量和可持续发展提供了新的视角。

关键词：人工智能技术使用；ESG责任表现；资源编排理论；高管环保认知；绿色发展

作者简介：周路路，东南大学经济管理学院副教授、博士生导师，南京，210096；桂家欣，东南大学经济管理学院博士研究生；赵曙明，南京大学商学院教授、博士生导师，通信作者，南京，210093；黄海艳，南京审计大学商学院教授，南京，211815。

基金项目：国家自然科学基金面上项目“人机混合团队任务冲突触发机制及演化过程的干预研究”（72372026）；国家自然科学基金专项项目“人-机交互场景下的数智化人力资源开发与管理研究”（72342027）

引用格式：周路路,桂家欣,赵曙明,等.人工智能技术使用如何影响企业ESG责任表现?——来自A股上市公司的证据[J].经济与管理研究,2025,46(7):43-57.

How does AI Adoption Affect Corporate ESG Responsibility Performance？

—Evidence from A-share Listed Companies

ZHOU Lulu¹, GUI Jiaxin¹, ZHAO Shuming², HUANG Haiyan³

(1. Southeast University, Nanjing 210096;

2.Nanjing University, Nanjing 210093;

3. Nanjing Audit University, Nanjing 211815)

Abstract: The ESG (environmental, social, and governance) concept has gradually emerged as an important standard for measuring corporate sustainability. However, challenges remain in how enterprises can improve their ESG performance. Existing research has focused on the impact of traditional factors such as executive characteristics and mergers and acquisitions on ESG, with limited exploration of the role of emerging technologies. The rapid development of the digital economy has positioned artificial intelligence (AI) as the core driver of the new wave of scientific and technological revolution, profoundly reshaping corporate production and operational models. Although existing studies confirmed that AI can enhance production efficiency and environmental governance, its comprehensive impact mechanism on corporate ESG responsibility performance remains unclear. Therefore, exploring how AI adoption empowers corporate ESG responsibility performance not only contributes to expanding theoretical research on technological innovation and sustainable development but also provides actionable pathways for enterprises to achieve the “dual carbon” goals and cultivate new quality productive forces.

Based on the resource orchestration theory and using data from A-share listed companies from 2010 to 2023 in China, this paper investigates the effect of AI adoption on corporate ESG responsibility performance. The findings reveal that AI adoption can enhance corporate ESG responsibility performance, and this conclusion holds after conducting a series of robustness checks. Further analysis indicates that AI adoption has the most pronounced positive effect on social responsibility (S), followed by environmental responsibility (E), and finally governance responsibility (G). Mechanism analysis demonstrates that AI adoption improves corporate ESG responsibility performance by enhancing internal control quality, information transparency, and green innovation capabilities. Additionally, heterogeneity analysis reveals that the positive effect of AI adoption on ESG responsibility performance is more pronounced in large-scale firms, companies with executives who possess higher environmental awareness, and non-heavily polluting industries.

This paper expands the potential pathways to enhance corporate ESG responsibility performance from the perspective of AI adoption and unveils the “black box” of their relationship. It not only provides important insights for enterprises into leveraging AI to promote sustainable development but also offers valuable references for policymakers. Specifically, enterprises should enhance their utilization of AI, fully leverage its resource advantages, and continuously improve their capabilities. They should consider cultivating or recruiting senior executives with a strong awareness of green development and ecological sustainability to achieve high-quality development. The government needs to introduce targeted policies tailored to different types of enterprises to encourage better fulfillment of ESG responsibilities.

Keywords: AI adoption; ESG responsibility performance; resource orchestration theory; executive environmental awareness; green development

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