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<p>As artificial intelligence (AI) reshapes corporate operations, its role in fostering sustainability has garnered increasing attention. This study investigates how AI application affects firms’ Environmental, Social, and Governance (ESG) performance, and how board-level demographic diversity, specifically gender and age, moderates this relationship. Drawing on panel data from 5,637 non-financial A-share listed firms in China (2014–2023), we employ fixed effects and PSM-DID models to address endogeneity. Results reveal that AI application significantly enhances ESG performance. Board gender diversity positively moderates this relationship, which underscores the strategic value of inclusive leadership. In contrast, board age diversity negatively moderates the effect, suggesting that intergenerational misalignment may hinder the effective implementation of AI-driven sustainability. Our findings are grounded in the Resource-Based View, Upper Echelons Theory and further enriched by Tokenism Theory. This study contributes to the governance literature by showing that board diversity is not uniformly beneficial, its impact varies by dimension and context. The findings highlight the need for boards aligned with technological change and support gender-inclusive governance as a lever for sustainable development.</p>

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Artificial Intelligence and Sustainable Governance: The Moderating Role of Board Gender and Age Diversity

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月1日

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  • Shanshan Yue,
  • Norkhairul Hafiz Bajuri,
  • Bin Wang,
  • Husni Samara

摘要

As artificial intelligence (AI) reshapes corporate operations, its role in fostering sustainability has garnered increasing attention. This study investigates how AI application affects firms’ Environmental, Social, and Governance (ESG) performance, and how board-level demographic diversity, specifically gender and age, moderates this relationship. Drawing on panel data from 5,637 non-financial A-share listed firms in China (2014–2023), we employ fixed effects and PSM-DID models to address endogeneity. Results reveal that AI application significantly enhances ESG performance. Board gender diversity positively moderates this relationship, which underscores the strategic value of inclusive leadership. In contrast, board age diversity negatively moderates the effect, suggesting that intergenerational misalignment may hinder the effective implementation of AI-driven sustainability. Our findings are grounded in the Resource-Based View, Upper Echelons Theory and further enriched by Tokenism Theory. This study contributes to the governance literature by showing that board diversity is not uniformly beneficial, its impact varies by dimension and context. The findings highlight the need for boards aligned with technological change and support gender-inclusive governance as a lever for sustainable development.