AI駆動型ESG監査における効率性と人的監督のバランス：AI自動化と意思決定の役割
Balancing Efficiency and Human Oversight in AI-Driven ESG Audits: The Roles of AI Automation and Decision Making (原題)
Ioannis C. Ploumpis, Nikolaos Eriotis, A. Christopoulos, Dimitrios Kenourgios, T. Kounadeas
🤖 gxceed AI 要約
日本語
ESG監査におけるAI活用が効率性・説明責任・透明性に与える影響を、150名の実務家データとPLS-SEMで分析した研究。AI自動化とAI意思決定はいずれも3つの成果を有意に改善し、人的監督が部分的に媒介することが示された。技術的効率と説明責任のバランス、すなわち強固なガバナンスと人間の監督の重要性を実証的に示唆する。
English
This study uses PLS-SEM on survey data from 150 ESG audit professionals to test how AI automation and AI decision making affect audit efficiency, accountability, and transparency. Both AI dimensions improve all three outcomes, with human oversight partially mediating these effects. The findings argue that AI strengthens ESG assurance most when paired with strong governance and human supervision.
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
SSBJ基準・有報でのサステナビリティ保証が議論される日本では、AI監査ツール導入時の人的監督・説明責任の設計が実務課題となる。本稿は保証業務の品質管理や監査法人のガバナンス体制構築に示唆を与える。
In the global GX context
As ISSB/CSRD assurance requirements expand and third-party ESG audit capacity tightens globally, this paper speaks to how AI can scale assurance without eroding accountability. It adds empirical evidence to the emerging AI-enabled ESG assurance literature, relevant to regulators weighing assurance standards and audit-firm governance.
👥 読者別の含意
🔬研究者:AI×ESG保証における人的監督の媒介効果を定量検証した初期実証として、今後のモデル精緻化の出発点になる。
🏢実務担当者:AI監査ツール導入時は自動化と意思決定権限の配分、人的レビュー工程の設計を明示的に組み込むべき。
🏛政策担当者:ESG保証の品質基準策定において、AI利用時の説明責任・透明性要件と人的監督の位置づけを検討する材料になる。
📄 Abstract（原文）
The growing use of artificial intelligence (AI) in Environmental, Social, and Governance (ESG) audits has created new opportunities to enhance corporate governance through faster and more consistent assurance processes. However, concerns remain regarding accountability, transparency, and the role of human oversight in AI-assisted auditing. Prior research has predominantly examined AI adoption in traditional financial auditing, leaving its role in the more qualitative and judgment-intensive context of ESG assurance comparatively underexplored, particularly with respect to how AI decision-making authority should be balanced against human oversight. This study examines the effects of AI automation and AI decision making on audit efficiency, accountability, and transparency, while assessing the mediating role of human oversight. A quantitative research design was adopted, and data were collected from 150 professionals involved in ESG audit-related functions (including ESG auditors, compliance officers, sustainability managers, and AI governance analysts) across private, public, and non-governmental organizations, recruited through purposive and snowball sampling via professional networks, audit forums, and LinkedIn ESG groups. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings indicate that AI automation significantly improves audit efficiency, accountability, and transparency. Similarly, AI decision making within governance structures exerts positive effects on all three outcome dimensions. Furthermore, human oversight partially mediates these relationships, strengthening the overall impact of AI on ESG audit outcomes. These results suggest that AI enhances ESG auditing effectiveness, but its benefits are maximized when supported by strong governance and human supervision. The study contributes to the emerging literature on AI-enabled ESG assurance by demonstrating the importance of balancing technological efficiency with accountability and transparency in corporate governance.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/jrfm19100796first seen 2026-10-13 05:17:50 · last seen 2026-10-14 05:51:57
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