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June 1, 2026Procedia CIRP0 citationsOpen Access

Artificial Intelligence and Circular Economy: An Exploration of the Ecological Infosphere

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CPChristiane PlociennikRRRené H. ReichABAdrien Berthelot

Key Points

  • This study explores the intersection of artificial intelligence and circular economy principles, emphasizing the sustainability of AI systems themselves.
  • Conducted a narrative literature review on AI and circular economy literature.
  • Synthetized insights related to AI's impact on resource use and circularity.
  • Developed a typology of circular economy aspects for AI.
  • Identified gaps in knowledge regarding hardware reuse and software sustainability.
  • Mapped both direct and indirect effects of AI on circularity and resource use.
  • Introduced the concept of the Infosphere to enhance circular sustainability assessments.

Abstract

Artificial Intelligence (AI) is increasingly promoted as a catalyst for the Circular Economy (CE), enabling resource-efficient production, predictive maintenance, sustainable product-service systems, and closing material loops. However, the resource and energy demands of AI systems themselves, especially with the rise of large-scale models, raise concerns about their compatibility with CE principles. This study critically examines the circularity of AI, shifting the focus from AI as an enabler of the CE to AI as an object of CE strategies. Through a narrative literature review, we synthesize fragmented insights pertaining to AI and circularity. We identify significant knowledge gaps, particularly regarding hardware reuse, software sustainability, and the absence of tailored LCA methodologies for AI. Our analysis maps direct and indirect effects of AI on circularity and resource use. We abduct the concept of the Infosphere, i.e., the digital layer of society, to complement the established biosphere and technosphere dichotomy, emphasizing that AI’s impacts extend beyond hardware infrastructure. The introduction of the Infosphere should spark discussions about rethinking the role of software and AI as subjects in system-wide sustainability assessments. By exploring a first typology of the CE of AI, this paper lays a conceptual foundation for future research and policymaking, advocating AI systems that not only enable the transition to a CE but are also designed and governed in circular, sustainable ways.

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Cite This Study

Plociennik et al. (2026) studied this question.

synapsesocial.com/papers/6a1d230d02fbce9130638beehttps://doi.org/10.1016/j.procir.2026.05.012
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