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Smart Innovation for a Circular Economy: A Systematic Review of Emerging Trends and the Future of AI in the Sustainable Economy

Author

Listed:
  • Juan Camilo Rua Hernandez

    (Facultad de Ciencias Económicas y Administrativas, Instituto Tecnológico Metropolitano, Medellín 050010, Colombia)

  • Eliana Villa-Enciso

    (Facultad de Ciencias Económicas y Administrativas, Instituto Tecnológico Metropolitano, Medellín 050010, Colombia)

  • Sebastián Cardona-Acevedo

    (Facultad de Ciencias Económicas y Administrativas, Instituto Tecnológico Metropolitano, Medellín 050010, Colombia)

  • Jackeline Valencia

    (Facultad de Artes y Humanidades, Instituto Tecnológico Metropolitano, Medellín 050010, Colombia
    Vicerrectoría de Investigación y Postgrado, Universidad de Los Lagos, Osorno 5290000, Chile)

  • Sofia Velasquez Salas

    (Facultad de Ciencias Económicas y Administrativas, Instituto Tecnológico Metropolitano, Medellín 050010, Colombia)

Abstract

The present study explores the potential of Artificial Intelligence (AI) in driving the sustainable economy forward through the optimization of resources and the mitigation of environmental impacts. However, the study also identifies significant challenges in the conceptual and methodological integration necessary to establish a comprehensive theoretical framework. The heterogeneity of these approaches hinders the discernment of discernible patterns within the scientific literature, thereby impeding the development of efficacious strategies to optimize their impact on sustainability. The present study employs the PRISMA 2020 methodology to analyze trends in scientific production on AI and the sustainable economy, thereby ensuring a rigorous process of identifying and evaluating studies. The mapping of the academic community, the geographical distribution of knowledge, and the evolution of approaches allow us to understand the research dynamics and identify gaps in the literature. This study makes a significant contribution to the field by offering a comprehensive perspective that supports the integration of AI into sustainable models and its application in sectors with high environmental and economic impacts.

Suggested Citation

  • Juan Camilo Rua Hernandez & Eliana Villa-Enciso & Sebastián Cardona-Acevedo & Jackeline Valencia & Sofia Velasquez Salas, 2025. "Smart Innovation for a Circular Economy: A Systematic Review of Emerging Trends and the Future of AI in the Sustainable Economy," Sustainability, MDPI, vol. 17(13), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:5793-:d:1685894
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    References listed on IDEAS

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    1. Khayyam, Hamid & Naebe, Minoo & Milani, Abbas S. & Fakhrhoseini, Seyed Mousa & Date, Abhijit & Shabani, Bahman & Atkiss, Steve & Ramakrishna, Seeram & Fox, Bronwyn & Jazar, Reza N., 2021. "Improving energy efficiency of carbon fiber manufacturing through waste heat recovery: A circular economy approach with machine learning," Energy, Elsevier, vol. 225(C).
    2. Henning Wilts & Beatriz Riesco Garcia & Rebeca Guerra Garlito & Laura Saralegui Gómez & Elisabet González Prieto, 2021. "Artificial Intelligence in the Sorting of Municipal Waste as an Enabler of the Circular Economy," Resources, MDPI, vol. 10(4), pages 1-9, March.
    3. Toluwase Asubiaro & Sodiq Onaolapo & David Mills, 2024. "Regional disparities in Web of Science and Scopus journal coverage," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(3), pages 1469-1491, March.
    4. Abdelhamid Zaidi & Samuel-Soma M. Ajibade & Majd Musa & Festus Victor Bekun, 2023. "New Insights into the Research Landscape on the Application of Artificial Intelligence in Sustainable Smart Cities: A Bibliometric Mapping and Network Analysis Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 287-299, July.
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    Cited by:

    1. Masoud Khakbazan & Hossein Ghanbari & Emran Mohammadi & Ronald Ravinesh Kumar & Amirhossein Ghasemi Abyaneh, 2026. "Exploring the role of AI-driven innovations in circular economy: a comprehensive bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 3177-3222, February.

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