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Artificial Intelligence in ESG Reporting: Transforming Corporate Sustainability Practices

ESG報告における人工知能：企業の持続可能性実践の変革 (AI 翻訳)

J. Chinna

Journal of Advances in Developmental Research📚 査読済 / ジャーナル2026-05-17#AI×ESG対象セクター: cross_sector
DOI: 10.71097/ijaidr.v17.i1.1916
原典: https://doi.org/10.71097/ijaidr.v17.i1.1916
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🤖 gxceed AI 要約

日本語

本研究は2019年から2025年までのAIのESG報告への影響を分析し、採用率が15%から63%に急増したことを示す。AIは単純なデータ収集から機械学習、NLP、生成AIへと進化し、報告の透明性・正確性・適時性を向上させた。規制要件とステークホルダー期待が主な推進要因である。

English

This study analyzes the impact of AI on ESG reporting from 2019 to 2025, showing adoption surged from 15% to 63%. AI evolved from basic data collection to machine learning, NLP, and generative AI, improving transparency, accuracy, and timeliness. Regulatory mandates and stakeholder expectations are key drivers.

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開示義務化が迫る中、AI活用によるESG報告の効率化と信頼性向上は実務上の重要課題。本論文は日本企業がAI導入を進める際の参考となる。

In the global GX context

Globally, with ISSB and CSRD mandates, AI-driven ESG reporting is becoming essential. This paper provides evidence of AI's transformative role, useful for companies and regulators shaping disclosure standards.

👥 読者別の含意

🔬研究者:AIとESG報告の統合に関する実証的傾向を提供し、今後の研究の基盤となる。

🏢実務担当者:AI導入の進化と利点を理解し、自社のESG報告戦略に応用できる。

🏛政策担当者:規制がAI採用を促進することを示し、政策設計に示唆を与える。

📄 Abstract（原文）

In this work, we examine the impact of Artificial Intelligence (AI) on ESG (Environmental, Social, and Governance) reporting, and the way in which it transformed corporate sustainability practices from 2019 to 2025. It is worth noting that the rate of AI adoption increased significantly from 15% in 2019 to 63% in 2025, suggesting that more organizations are transitioning towards automated and data-driven reporting systems instead of typical reporting systems that utilized manual means. At first AI was used mainly for simple data-collecting and testing purposes. Yet adoption picked up in this period, ramped up drastically from 2021 to 2022 – fueled by an increasing focus on analytics, risk assessment and regulation. On the other hand, the study also discusses the technological trends of AI applications, from basic automation tools to advanced systems like machine learning, big data analytics, Natural Language Processing (NLP), predictive analytics, and generative AI. These technologies have improved ESG reporting quality, increasing the transparency, accuracy and timeliness leading to real-time and AI-driven reporting systems by 2025. Moreover, the drivers of AI adoption are no longer voluntary, but regulatory mandates and strategic needs associated with higher stakeholder expectations and data complexity. AI has seen explosive growth in the market as well, from being a fledgling venture into a multi-billion-dollar market in ESG reporting. A significant implication of the study of AI is that AI has emerged as a critical component for more efficient, reliable, and transparent ESG reporting; AI can be highly beneficial for companies to enhance their sustainability performance and achieve informed decisions.

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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。