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Building ESG Reporting Architecture & Capabilities through Artificial Intelligence (AI): Dynamic Capabilities Perspective-enabled ESG Reporting in Museums

人工知能（AI）によるESG報告アーキテクチャと能力の構築：動的能力の視点から見た博物館におけるESG報告 (AI 翻訳)

Teri Grimmer, Wookyoung Kim, Harim Jung, Mike Eom

Journal of the Association for Information Systems📚 査読済 / ジャーナル2026-08-13#AI×ESGOrigin: Global対象セクター: other
原典: https://aisel.aisnet.org/amcis2026/sig_lead/sig_lead/4

🤖 gxceed AI 要約

日本語

本研究は、資源制約のある博物館においてAIがESG報告をどのように強化するかを検討。リソース・ベースド・ビューとダイナミック・ケイパビリティ理論に基づき、AI対応ESG報告を戦略的組織能力として概念化。東アジアの博物館の事例研究と米国の博物館の定量分析を組み合わせ、AIによるESG報告アーキテクチャを提案。

English

This study examines how AI-enabled analytics enhances ESG reporting in resource-constrained museums. Using resource-based view and dynamic capabilities theory, it conceptualizes AI-enabled ESG reporting as a strategic organizational capability. Mixed-method design: qualitative case studies of two East Asian museums and quantitative analysis of 50 U.S. museums. Proposes an AI-enabled ESG reporting architecture integrating diverse data sources, real-time analytics, and explainable AI.

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

日本の博物館・文化施設はESG情報開示の機運が高まる中、リソース不足が課題。本論文のAI活用アプローチは、限られた予算・人材で効果的な報告を実現する枠組みとして示唆に富む。SSBJ対応が進む企業だけでなく、非営利組織にも応用可能性。

In the global GX context

Globally, ESG reporting is expanding to non-profits and cultural institutions. This paper demonstrates how AI can overcome resource constraints and fragmented data, improving transparency and operational efficiency. The proposed architecture is relevant for organizations with limited resources seeking to enhance their ESG disclosure under frameworks like ISSB or GRI.

👥 読者別の含意

🔬研究者:Provides a dynamic capabilities framework for AI-enabled ESG reporting in resource-constrained settings, contributing to the literature on AI-ESG integration and organizational theory.

🏢実務担当者:Offers a practical architecture for museums and similar entities to implement AI for ESG data integration and reporting, improving donor relations and operational efficiency.

🏛政策担当者:Highlights the need for scalable ESG reporting standards for non-profits and the potential of AI to reduce reporting burdens, relevant for regulators developing guidelines for diverse organizations.

📄 Abstract（原文）

This study examines how artificial intelligence (AI)–enabled analytics enhances Environmental, Social, and Governance (ESG) reporting in resource-constrained museums. Drawing on the resource-based view and dynamic capabilities theory, we conceptualize AI-enabled ESG reporting as a strategic organizational capability. Using a mixed-method design, we combine qualitative case studies of two East Asian museums with quantitative analysis of 50 U.S. museums using Candid transparency ratings as a proxy for ESG disclosure. Results show that greater reliance on donor contributions increases incentives for transparency, particularly in competitive urban environments. However, fragmented data, weak governance, and organizational inertia limit ESG effectiveness. To address these challenges, we propose an AI-enabled ESG reporting architecture integrating diverse data sources, real-time analytics, and explainable AI. The findings demonstrate how AI can transform ESG reporting into a decision-support capability that improves transparency, operational efficiency, and funding sustainability.

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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。