Artificial Intelligence Interventions for Circular Economy by the 10R Framework
人工知能による循環経済介入：10Rフレームワークに基づいて (AI 翻訳)
Ambika Zutshi, Diane Zandee, Andrew Creed
🤖 gxceed AI 要約
日本語
本論文は、人工知能（AI）を循環経済（CE）への移行を促進する重要な手段と位置づけ、10Rフレームワークを用いて各循環度におけるAIの適用可能性を探る。AIは、材料削減、製品寿命延長、価値保持の機会を特定し、Scope 3 CO2排出削減や規制対応から価値創造への転換を支援する。
English
This paper positions AI as a critical enabler for the transition to a circular economy, using the 10R framework to explore AI applications across circularity levels. It highlights how AI can identify opportunities for material reduction, product life extension, and value retention, while supporting Scope 3 emissions reduction and shifting from compliance-driven reporting to proactive value creation.
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
日本の循環経済政策（プラスチック資源循環促進法など）やSSBJのScope 3報告に直面する企業にとって、AI活用によるCE実践と排出削減の統合アプローチを示唆。
In the global GX context
The paper bridges AI and circular economy, offering a structured approach via 10R. Relevant for global firms facing CSRD/ISSB disclosure and seeking data-driven CE strategies.
👥 読者別の含意
🔬研究者:Provides a conceptual framework linking AI capabilities to circular economy strategies, useful for further empirical study.
🏢実務担当者:Offers a practical entry point (10R) for operationalizing CE with AI, including Scope 3 emission reduction.
🏛政策担当者:Highlights AI's role in CE transition, relevant for shaping regulatory frameworks that encourage data-driven sustainability.
📄 Abstract（原文）
<div> The transition towards a circular economy (CE) confronts decision-makers with increasing levels of complexity driven by the need to coordinate between extended value chains within multi-actor ecosystems. This article positions artificial intelligence (AI) as a critical enabler for navigation of complexity and to support informed, data-driven decision-making. Building on the 10R framework, the article explores how AI can be applied thematically across each level of circularity to identify opportunities for material reduction, product life extension, and value retention. By linking AI capabilities to specific circular strategies, the 10R framework serves as a practical entry point for organizations seeking to operationalize CE principles within their business models and supply chains. Moreover, the article proposes AI as an analytical tool, and a catalyst for collaboration. There is potential for AI to provide a foundation for engaging value chain partners in joint efforts to reduce resource use and Scope 3 CO₂ emissions. These gains through purposeful intervention will support a shift in organizational discourse from compliance-driven reporting, as required by emerging regulatory frameworks, toward proactive value creation and continuous improvement. The article invites decision-makers to embrace AI as an intervention tool to move beyond complexity, foster ecosystem-level collaboration, and accelerate the transition from linear to CE systems. </div> <p><span></span></p>
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.2139/ssrn.6574959first seen 2026-06-11 04:45:09
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