AI adoption, ESG disclosure quality and sustainability committee heterogeneity: evidence from Chinese companies

Purpose - The purpose of this study is to examine the impact of adopting artificial intelligence (AI) on the quality of corporate sustainability reporting. The role of sustainability committees, including specialist environmental, social and governance (ESG) committees, in moderating this dynamic is also examined. Design/methodology/approach - Regression analysis is used to analyze the quality of ESG/sustainability disclosures of listed Chinese companies from 2015 to 2022. Robustness is ensured through fixed effects analysis, while endogeneity concerns are addressed using one-year lagged measures and the three-stage least squares (3SLS) approach. Sustainability committees are categorized based on their ESG specific focus areas, and aligned with the corresponding ESG disclosure pillars. In addition, for the governance pillar, the analysis is extended by segmenting the sample based on state ownership status. Stakeholder theory and the dynamic capability view are used to frame the analysis. Findings - The results reveal that AI adoption enhances overall sustainability reporting quality and pillar-specific ESG disclosure quality. This positive effect is amplified by the presence of sustainability committees. Examining the heterogeneous impact of these committees revealed stronger associations between sustainability committee specialization and relevant ESG pillar disclosure quality (except for governance), suggesting that use of specialist committees can improve disclosure outcomes. Notably, within non-state-owned enterprises, governance-focused committees positively moderate the AI−disclosure relationship, highlighting a nuanced effect based on ownership structure. Practical implications - The findings offer empirical support for companies to leverage AI in sustainability reporting. This study finds evidence to support the creation of sustainability committees, as a key corporate governance mechanism to drive corporate sustainability reporting. The use of specialist sustainability committees can drive improvements in disclosure quality relating to specific ESG pillars. The research indicates that disclosure over governance remains poor and will require additional regulatory effort to encourage entities to provide higher quality governance-related disclosures. In terms of ownership structure, the study found that non-state-owned enterprises are more efficient in using specialist sustainability committees to improve disclosure quality. Social implications - The findings highlight the potential of AI in supporting high-quality sustainability reporting and the strategic role of sustainability committees in this dynamic. The publication of high-quality sustainability reports is critical in meeting stakeholder demands for transparency and corporate accountability on sustainability. Originality/value - The findings offer insights into AI’s role in supporting high-quality sustainability reporting. By examining the moderating effects of sustainability committees, the research goes beyond examining a general impact to exploring how corporate governance mechanisms impact this relationship. In addition, the unique data on Chinese companies highlights differences between state-owned and non-state-owned enterprises, with the latter exhibiting greater potential to leverage specialist sustainability committees for improving sustainability reporting.