Operationalizing ESG-as-Code: Automating ESG Compliance and Regulatory Reporting Pipelines Using Containerized AI Workflows on Kubernetes–OpenStack Infrastructure.
ESG-as-Codeの運用化:コンテナ化されたAIワークフローを用いたESGコンプライアンスと規制報告パイプラインの自動化 (AI 翻訳)
Isaiah Oluwasegun Owolabi
🤖 gxceed AI 要約
日本語
本論文は、CSRDやSDR、SEC規制などのESG規制テキストを機械実行可能なコンプライアンスロジックに変換する「ESG-as-Code」フレームワークを提案。コンテナ化されたAIワークフローにより、監査可能でスケーラブルなESGコンプライアンスパイプラインを実現する。
English
This paper presents an ESG-as-Code framework that translates ESG regulatory texts (CSRD, SDR, SEC) into machine-executable compliance logic. It demonstrates how containerized AI workflows on Kubernetes-OpenStack enable automated, auditable, and scalable ESG compliance and regulatory reporting pipelines, with cross-jurisdictional harmonization.
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SSBJによる開示基準の策定が進む中、本論文の提案するクロスジャンクション対応のESGコンプライアンス自動化アーキテクチャは、日本企業のグローバルな開示対応に示唆を与える。特に、規制テキストのコード化とクラウドネイティブな実行基盤は、日本における開示インフラの効率化に応用可能である。
In the global GX context
As CSRD, SDR, and SEC climate rules tighten globally, this paper offers a blueprint for automating multi-jurisdictional ESG compliance. The ESG-as-Code approach provides a reference for any enterprise needing scalable, auditable reporting systems, and highlights the role of cloud-native AI in regulatory technology.
👥 読者別の含意
🔬研究者:The paper contributes a novel architecture for translating regulatory text into executable rules, bridging legal and AI/ML research for automated compliance.
🏢実務担当者:Corporate sustainability teams can leverage the framework to automate ESG reporting pipelines, reducing manual effort and ensuring auditability across jurisdictions.
🏛政策担当者:Policymakers may consider the digitalization of regulatory compliance as a means to enhance transparency and reduce reporting burden, especially for cross-border rules.
📄 Abstract(原文)
Environmental, Social, and Governance (ESG) compliance is increasingly governed by binding regulatory regimes across jurisdictions, including the EU Corporate Sustainability Reporting Directive (CSRD), the UK Sustainability Disclosure Requirements (SDR), and emerging U.S. Securities and Exchange Commission (SEC) climate disclosure rules. Despite this regulatory shift, prevailing ESG compliance practices remain largely manual, document-driven, and opaque, limiting scalability, auditability, and regulatory assurance. This paper presents a cloud-native architecture for operationalizing ESG-as-Code™, a regulatory technology framework that transforms ESG regulatory text into machine-executable compliance logic. The framework formalizes ESG obligations through regulatory clause segmentation, threshold extraction, domain-specific language (DSL) generation, and rule compilation, enabling deterministic, explainable, and traceable compliance evaluation against structured ESG data inputs. Building on this framework, the paper demonstrates how containerized artificial intelligence workflows and orchestrated execution environments can be used to deploy ESG-as-Code rule artifacts as automated ESG compliance and regulatory reporting pipelines. The proposed architecture supports continuous regulatory updates, cross-jurisdictional rule harmonization, and scalable execution while preserving end-to-end lineage from legal source text to compliance outcomes. The contribution of this work lies in bridging regulatory logic abstraction with cloud-native execution, providing a reference implementation for scalable, auditable, and infrastructure-agnostic ESG compliance systems suitable for enterprise and regulatory contexts.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.63084/algora.v2i2.60first seen 2026-07-09 04:43:21
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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。