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August 19, 2026Business Strategy and the Environment

Artificial Intelligence and ESG Disclosure Quality: A Boundary Conditional Analysis Using Quantile Regression

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Authors

DBDesmond BayongDZDejun ZhouAAAndrews Osei Agyemang

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Overview

Panel analysis demonstrates AI adoption enhances ESG disclosure quality in G7 manufacturing firms, highlighting the amplifying role of regulatory pressure and governance.

Key Points

  • To evaluate the impact of artificial intelligence adoption on ESG disclosure quality and determine how governance and institutional factors moderate this relationship.
  • Analyzed a panel dataset of 5,600 firm-year observations from manufacturing companies across G7 economies from 2017 to 2024.
  • Employed distribution-sensitive quantile regression and complementary robustness tests to evaluate heterogeneous effects across disclosure distributions.
  • Artificial intelligence adoption demonstrated a consistently positive relationship with ESG disclosure quality across all quantile tiers, improving reporting accuracy, timeliness, and credibility.
  • The positive impact of AI on disclosure quality was significantly strengthened by stakeholder engagement, regulatory pressure, and institutional ownership.

Cite This Study

Bayong et al. (2026) studied this question.

synapsesocial.com/papers/6a85633c03308d306e2d64edhttps://doi.org/10.1002/bse.71425
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