Transforming sustainable and green supply chains with artificial intelligence: A strategic review and future research opportunities

S. Porkodi

https://orcid.org/0000-0001-9105-5450

Oman

University of Technology and Applied Sciences image/svg+xml

Department of Business Studies
College of Economics and Business Administration

 V.V. Phani Kumar Tantravahi

https://orcid.org/0009-0003-6353-5029

Oman

University of Technology and Applied Sciences image/svg+xml

Department of Business Studies
College of Economics and Business Administration

 

Bassam Khalil Hamdan Tabash

https://orcid.org/0009-0007-8204-0944

Oman

University of Technology and Applied Sciences image/svg+xml

Deputy Vice Chancellor
Administrative and Financial Affairs

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Accepted: 2025-03-22

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Published: 2025-07-30

DOI: https://doi.org/10.4995/ijpme.2025.22632
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Keywords:

Artificial intelligence, supply chain management, sustainability, green practices, logistics, environmental performance

Supporting agencies:

This research was not funded

Abstract:

Supply chain management (SCM) using artificial intelligence (AI) transforms business practices by encouraging sustainability. Gaining insight into AI's role in improving supply chain effectiveness and lowering environmental impact is essential as demand for sustainable practices rises. This study aims to investigate how AI contributes to sustainability in SCM and determine the primary challenges and opportunities associated with implementing AI. The study aims to provide an extensive review of AI's potential to assist sustainable and green supply chain practices. This standard and strategic literature review was conducted employing the Scopus database. The five-stage methodology was adopted in the review process, which includes pilot search, locating studies, study selection, synthesis analysis, and reporting. The choice of 82 relevant studies on AI and sustainable SCM was made during the review after the exclusion of irrelevant articles. The review emphasises AI's significant role in enhancing sustainability in SCM by reducing environmental impact, improving resource efficiency, and promoting green practices. However, the study also highlights the identification of challenges such as integration complexity, implementation cost, and technological limitations and future agenda.

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