Harnessing Artificial Intelligence for the Integration and Advancement of Circular Economy Practices

Christopher  Kronenberg; Sezi Cevic  Onar; Saman Sarbazvatan

doi:10.55845/joce-2025-3277

Authors

Christopher Kronenberg University of Applied Sciences BFI Vienna Author https://orcid.org/0000-0002-1487-9103
Sezi Cevic Onar École des Ponts Business School Author https://orcid.org/0009-0004-2942-8120
Saman Sarbazvatan École des Ponts Business School Author https://orcid.org/0000-0002-6072-5631

DOI:

https://doi.org/10.55845/joce-2025-3277

Keywords:

Artificial Intelligence, Urban Waste Management, Circularity

Abstract

Urban waste management faces growing challenges as municipal solid waste is projected to reach 3.4 billion tons by 2050. This study examines how artificial intelligence applications contribute to circular economy transitions in urban waste management through a systematic literature review of 150 peer-reviewed studies and an analysis of commercial implementations. Using the PRISMA framework, we identified AI methods, waste management stages, and circular economy outcomes across academic research and practical deployments. Results reveal that while AI demonstrates strong technical capabilities – particularly in sorting and classification and forecasting – only 31% of studies report circular economy outcomes such as recycling rate improvements or reducucing resource inputs. Both academic research and commercial implementations remain concentrated in downstream recycling activities rather than upstream prevention strategies. The findings highlight a critical gap between technical performance and systemic circular transitions, suggesting that AI adoption must be integrated with governance frameworks, standardized outcome measurement, and multi-stage coordination to effectively advance urban circular economy goals.

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