欧州における企業サステナビリティ報告、人工知能、CDP

Corporate Sustainability Reporting, Artificial Intelligence, and the Carbon Disclosure Project in Europe (原題)

Saeed Askary, Davood Askarany, Hassan Yazdifar, Alireza Vafaei, Marc Olynyk, Alireza Daneshfar

Crossrefプレプリント2026-01-01#AI×ESGOrigin: EU経営インパクト: 調達リスク対象セクター: cross_sector

原典: https://doi.org/10.2139/ssrn.7091878

🤖 gxceed AI 要約

日本語

欧州18カ国を対象に、AI関連の環境認識、ESG報告の任意・義務導入のタイミング、CDP開示品質の関係を分析。義務報告はCDP開示品質をわずかに向上させるが、炭素強度への効果は一貫しない。AI認識と実際の開示品質の相関は弱く、認識と実践のギャップが明らかになった。CSRDやAI法の地域差を考慮した実装への示唆を提供。

English

This study examines the interplay between AI-related environmental perceptions, ESG reporting timing, and CDP disclosure quality across 18 European countries. Mandatory reporting modestly improves disclosure quality, but effects on carbon intensity are mixed. AI perceptions show weak correlation with actual disclosure, revealing a perception-practice gap. Findings inform region-sensitive implementation of CSRD and the EU AI Act.

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開示が始まる中、AIを活用した開示品質向上と認識ギャップの知見は、今後の有報・統合報告書でのAI活用や開示の信頼性確保に示唆を与える。欧州の義務開示の効果が限定的である点は、日本の任意開示中心の現状にも参考になる。

In the global GX context

This paper provides timely evidence for global disclosure scholarship on the effectiveness of mandatory ESG reporting (CSRD) and the role of AI in corporate transparency. The perception-practice gap and regional heterogeneity caution against uniform regulatory approaches, informing ISSB and SEC implementation. It also highlights the need for AI governance in reporting standards.

👥 読者別の含意

🔬研究者:Provides empirical evidence on the perception-practice gap in AI-enhanced sustainability reporting and introduces carbon intensity variance as a proxy for reporting consistency.

🏢実務担当者:Highlights the need for AI capacity-building over perception-driven reporting claims and cautions against over-reliance on AI-enhanced disclosures.

🏛政策担当者:Informs region-sensitive implementation of CSRD and AI Act, emphasizing the need for AI governance frameworks in ESG reporting standards.

📄 Abstract（原文）

Purpose – This paper examines the interplay between artificial intelligence (AI)-related environmental perceptions, the timing of mandatory and voluntary ESG reporting adoption, and corporate carbon disclosure quality across 18 European countries. The study investigates whether AI perception, ESG framework timing, and regional regulatory contexts jointly shape corporate carbon transparency, contributing to the sustainability accounting literature at the intersection of technology adoption and disclosure quality. Design/methodology/approach – A cross-country comparative design is employed, integrating meta-analytic effect-size synthesis, cluster analysis, and Pearson correlation mapping. Three primary datasets are used: the IPSOS 2022 public opinion survey on AI and the environment, CDP disclosure records, and carbon intensity metrics from the PwC Net Zero Economy Index (2024). Countries are analysed at the national level across 18 European nations. Findings – Mandatory ESG reporting modestly improves CDP disclosure quality, though its effects on carbon intensity variance remain mixed. Voluntary early adopters demonstrate more consistent and refined disclosure practices, likely reflecting iterative reporting experience. AI-related environmental perceptions exhibit only weak correlations with actual CDP disclosure quality, revealing a perception-practice gap. Significant regional heterogeneity in AI-ESG integration underscores the limitations of uniform regulatory approaches across Europe. Practical implications – For standard-setters (EFRAG, IFRS Foundation) and regulators implementing the Corporate Sustainability Reporting Directive (CSRD), findings highlight the need for AI governance frameworks embedded within ESG reporting standards. Corporate practitioners should prioritize AI capacity-building over perception-driven reporting claims. Investors should interpret AI-enhanced disclosures cautiously, focusing on verified carbon intensity trends rather than technological assertions. Social implications – Understanding the gap between public optimism about AI's environmental role and actual corporate reporting practice has important social consequences. It underscores that AI-enhanced sustainability reporting must be grounded in transparent, auditable, and stakeholder-aligned systems to genuinely advance accountability, investor confidence, and environmental outcomes across Europe. Originality/value – This study makes an original contribution by empirically evaluating the perception-practice gap in AI-enhanced sustainability reporting at the national level across 18 European countries. It introduces carbon intensity variance as a novel proxy for reporting consistency and provides policy-relevant evidence for the region-sensitive implementation of the EU's CSRD and AI Act.

🔗 Provenance — このレコードを発見したソース

openaire https://doi.org/10.2139/ssrn.7091878first seen 2026-09-01 04:58:46 · last seen 2026-09-21 04:31:24

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