Executive AI Capability and Strategic ESG Decision-Making: Evidence from Chinese Listed Firms

Rui Zhang; Chongfeng Lan; Huanyong Ji

doi:10.31081/dmame8120251697

Authors

Rui Zhang Business School, Beijing Information Science & Technology University, Beijing, China
Chongfeng Lan School of Economics, Fuyang Normal University, Fuyang, China
Huanyong Ji Business School, Beijing Information Science & Technology University, Beijing, China

DOI:

https://doi.org/10.31081/dmame8120251697

Keywords:

Executives Artificial Intelligence Ability; ESG Performance; Political Dependence; Redundant Resources; Ownership Structure

Abstract

This study investigates the influence of executives’ artificial intelligence (AI) capability on firm-level Environmental, So-cial, and Governance (ESG) outcomes within developing economies, recognising that such dynamics may diverge from those observed in advanced markets. Focusing on China as a representative context, the analysis explores the underlying pathways linking executives’ AI capability with ESG per-formance, while also examining the contingent effects of political dependence dimensions, including resource redun-dancy and ownership structure. Grounded in a strategic deci-sion-making perspective, the study posits that executives’ AI capability primarily informs ESG-oriented managerial judgements and investment allocations, rather than directly determining ESG outcomes. Utilising panel data spanning 2011 to 2023, the findings reveal three key insights. First, executives’ AI capability exerts a positive effect on ESG performance. Second, the presence of redundant resources weakens this relationship, whereas private ownership en-hances it. Third, additional examination shows that execu-tives’ AI capability is positively associated with symbolic environmental performance, but demonstrates no statistically significant linkage with substantive environmental perfor-mance, thereby indicating a strategic trade-off between sym-bolic and substantive ESG engagement. Collectively, these findings contribute to a more nuanced understanding of how managerial competencies at the individual level shape ESG outcomes in developing-country settings, while also offering practical implications for both corporate leaders and policy-makers.

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