The Convergence of Supply Chain Management and Artificial Intelligence: Challenges and Opportunities

( Vol-11,Issue-6,November - December 2025 )

Author(s): Farjana Nawrin, Prince David Hayibor, Owen Atsu Soglohu, Kofi Mensah Adams, Terry Muringo Muriithi, Farhad Akter, Josephine Arthur

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Page No: 199-209
DOI: 10.22161/ijaems.116.19

Keywords:

Artificial Intelligence, Supply Chain Management, Machine Learning, Digital Twins, Governance, Resilience, Large Language Models, Responsible AI

Abstract:

Artificial Intelligence (AI) is rapidly transforming the architecture and performance of global supply chains. The convergence of data-rich operations with machine learning (ML), reinforcement learning (RL), and generative large language models (LLMs) enables unprecedented levels of automation, foresight, and adaptability in supply chain management (SCM). This paper synthesizes recent literature (2023–2025) to examine how AI technologies reshape core SCM functions, forecasting, inventory optimization, logistics routing, procurement, and risk management, while identifying the governance and organizational challenges that shape adoption outcomes. Findings indicate that AI integration delivers measurable efficiency and resilience gains but also introduces new risks related to data interoperability, explainability, cybersecurity, and ethical governance. A governance-first operating model is proposed, emphasizing transparency, human oversight, and regulatory compliance as key enablers of sustainable AI deployment. The study concludes with a phased implementation roadmap and a future research agenda focused on responsible, interdisciplinary innovation at the intersection of AI and SCM.

Received: 25 Nov 2025; Received in revised form: 24 Dec 2025; Accepted: 27 Dec 2025; Available online: 31 Dec 2025

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