Artificial Intelligence in Sustainability Assurance: Accounting Challenges, Audit Risks and a Conceptual Framework for ESG Verification
サステナビリティ保証における人工知能：会計上の課題、監査リスク、ESG検証のための概念枠組み (AI 翻訳)
Radosveta Krasteva-Hristova, Vanya Georgieva
🤖 gxceed AI 要約
日本語
本概念研究は、CSRD、ESRS、ISSA 5000、EU AI Actを背景に、AIがESG保証業務をどのように支援できるかを検討する。開示特定、ESRSマッピング、異常検知、グリーンウォッシュリスクスクリーニング、外部データ三角測量などの応用とともに、ハルシネーションや説明可能性などの保証リスクを分析。人間参加型の責任あるAI支援サステナビリティ保証フレームワークを提案する。
English
This conceptual article examines how AI can support sustainability assurance under CSRD, ESRS, ISSA 5000, and the EU AI Act. It explores applications such as disclosure identification, ESRS mapping, anomaly detection, greenwashing risk screening, and external data triangulation. It also analyzes assurance risks including hallucination and explainability. The article proposes a Responsible AI-Assisted Sustainability Assurance Framework with human-in-the-loop.
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
日本のSSBJ対応でも、AIを用いた保証業務の効率化やリスク管理が重要になりつつある。本フレームワークは日本企業の有報・統合報告書における内部統制や第三者保証に応用可能な示唆を与える。
In the global GX context
As sustainability assurance becomes mandatory under ISSB and CSRD globally, this framework offers a structured approach for integrating AI into verification processes. It is particularly relevant for practitioners dealing with ESRS and for standard-setters like IAASB.
👥 読者別の含意
🔬研究者:Provides a conceptual foundation for studying AI in sustainability assurance; identifies key risks and a framework for empirical testing.
🏢実務担当者:Offers a practical framework for deploying AI in ESG verification while managing risks such as hallucination and bias, with a human-in-the-loop approach.
🏛政策担当者:Highlights regulatory implications for AI use in assurance under CSRD and the EU AI Act, informing standard-setting for assurance engagements.
📄 Abstract（原文）
This conceptual article examines how artificial intelligence can support sustainability assurance in the transition from voluntary ESG disclosure to regulated, assurance-oriented sustainability reporting. The study is situated in the context of the Corporate Sustainability Reporting Directive, the European Sustainability Reporting Standards, ISSA 5000 and the EU Artificial Intelligence Act. It argues that AI can strengthen ESG verification by supporting disclosure identification, ESRS mapping, anomaly detection, consistency checks, greenwashing risk screening, external data triangulation and working-paper documentation. At the same time, AI introduces specific assurance risks, including data quality risk, reliability and hallucination risk, explainability risk, bias risk, overreliance risk, documentation risk, confidentiality risk, boundary and materiality risk, and accountability risk. The article develops a Responsible AI-Assisted Sustainability Assurance Framework that integrates ESG data inputs, AI analytical procedures, assurance risk assessment, human professional judgement, validation controls and documented assurance outputs. The central conclusion is that AI should be used as an analytical support layer within a human-in-the-loop assurance process, not as an autonomous source of assurance conclusions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.20944/preprints202607.1236.v1first seen 2026-07-23 05:27:35
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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。