From ESG to ESGI
ESGからESGIへ：AIが変革するサステナブルファイナンス (AI 翻訳)
Zaheda Daruwala
🤖 gxceed AI 要約
日本語
本論文は、ESG投資に人工知能（AI）を統合した新たなパラダイム「ESGI（ESG with Intelligence）」を提案する。自然言語処理や説明可能AIなどの手法を用い、静的なESG評価をデータ駆動型の動的システムへ変革する概念フレームワークを提供する。
English
This paper introduces ESGI (ESG with Intelligence), a paradigm integrating AI into ESG investing. Through systematic literature review, it proposes a dynamic, data-driven ecosystem using NLP, XAI, and other AI methods to enhance transparency and materiality in sustainable finance.
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
日本でもESG情報の質向上が求められる中、AI活用による分析精度向上はSSBJ開示や投資家対応に示唆を与える。ただし、本稿は概念提唱に留まり、実証や日本固有の制度への言及はない。
In the global GX context
As global ESG disclosure frameworks evolve, this conceptual piece highlights how AI can transform static assessments into dynamic, evidence-based systems—relevant for ISSB and transition finance debates, though it lacks empirical grounding.
👥 読者別の含意
🔬研究者:Provides a conceptual foundation for integrating AI into ESG research, particularly for those exploring ML applications in sustainable finance.
🏢実務担当者:Offers a framework for corporate sustainability teams to consider AI-driven tools for improving ESG data analysis and reporting.
🏛政策担当者:Raises regulatory implications for AI use in ESG ratings and disclosure, though no specific policy recommendations.
📄 Abstract（原文）
The integration of artificial intelligence into sustainable finance signifies a critical imperative of analytical foundations for ESG investing. This chapter introduces the concept of ESGI (ESG with Intelligence) as an emergent paradigm that systematically embeds AI-driven analytical methods into the evaluation, implementation, and optimization of ESG investments. It moves beyond traditional financial metrics by integrating unstructured information sources, enabling stakeholders to identify material ESG risks and opportunities. Using systematic literature review and conceptual analysis, it establishes how ESGI transforms investment decision-making into a dynamic data-driven system that aligns value with sustainability. It uses AI-driven applications of Natural Language Processing, Long Short-Term Memory, Explainable AI, Reinforcement Learning, Predictive Analytics, Semantic AI, IoT sensors. The study underscores the pivot from static ESG assessment to a dynamic AI-driven evidence-based ecosystem, enabling a more transparent, measurable, and impactful ESG finance architecture.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.4018/979-8-2600-1348-9.ch007first seen 2026-05-14 23:49:00
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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。