AI-Enhanced Governance for ESG Reporting Integrity: A Sector-Specific Framework Balancing Algorithmic Detection and Human Judgment
ESG報告の完全性向上のためのAI強化ガバナンス：セクター別枠組みとアルゴリズム検出と人間判断のバランス (AI 翻訳)
Mohsin Khan, Wendy Ashurst
🤖 gxceed AI 要約
日本語
本論文は、ESG報告の品質向上におけるAIの役割を検討し、セクター別のハイブリッドガバナンスフレームワークを提案する。環境指標はAI検証に適しているが、社会・ガバナンス報告では人間の判断が重要であると論じる。AIは補完的なガバナンスメカニズムとして位置づけられる。
English
This paper examines the role of AI in enhancing ESG reporting quality, proposing a sector-specific hybrid governance framework. It finds environmental metrics are more amenable to AI verification, while social and governance disclosures require human judgment. AI is reconceptualized as a complementary governance mechanism, not a substitute.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ基準の導入が進む中、ESG報告の信頼性向上が課題となっている。本論文のフレームワークは、AIと人間判断のバランスを提示し、日本の開示実務に示唆を与える。
In the global GX context
Globally, with mandatory ESG disclosure regimes like CSRD and ISSB, ensuring reporting integrity is paramount. This paper offers a practical hybrid model balancing algorithmic efficiency with human oversight, relevant for companies and assurance providers.
👥 読者別の含意
🔬研究者:Provides a conceptual framework situating AI within governance theory for ESG reporting.
🏢実務担当者:Offers guidance on how to deploy AI for ESG verification while retaining board oversight and expert judgment.
📄 Abstract（原文）
Purpose: This paper aims to develop a sector-specific governance framework to understand the application of artificial intelligence in enhancing the quality of ESG reporting, while recognizing the value of human judgement in high-risk disclosure environments. Design/methodology/approach: This conceptual paper uses a theory-driven qualitative approach. It draws on a critical review of the literature and discourse analysis of 120 corporate sustainability reports from the energy, financial services and consumer goods industries. Findings: Environmental disclosures have the highest verification potential on AI since metrics are more benchmarkable and standardized. It's worth is reduced in social and governance reporting where narrative interpretation and judgement in context are vital. It is also revealed that sectoral conditions have their role as operationally measurable industries would be easier to place under AI-based review as compared to financially oriented narrative reporting. Originality/value: The paper re-conceptualizes AI not as a technical solution but as a limited governance mechanism based on legitimacy, stakeholder and agency theory. It offers a workable hybrid approach where algorithmic detection is used to complement, not substitute for, board oversight, assurance and judgement in ESG reporting.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.2139/ssrn.6681979first seen 2026-06-11 05:17:23
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。