Title: Integrating artificial intelligence into supply chain management: promise, challenges and guidelines

Authors: Henry Adobor; Iddrisu Awudu; Mario Norbis

Addresses: Department of Strategy and Entrepreneurship, School of Business, Quinnipiac University, Hamden, CT 06518, USA ' Department of Management, School of Business, Quinnipiac University, Hamden, CT 06518, USA ' Department of Management, School of Business, Quinnipiac University, Hamden, CT 06518, USA

Abstract: This paper argues that AI can improve supply chain efficiency, and transform supply chain management by providing tools for managing the functions across all the stages of a supply chain. Despite the promise, organisational and managerial challenges may limit AI and SCM integration. We explore the challenges of AI use in SCM and offer some guidelines for its successful integration. We propose that organisations need to make an economic case for AI adoption, develop a plan for AI implementation, including developing core capabilities and system trust for coordinating behaviour across the stages of the supply chain. In addition, organisations need to manage the nexus of people and technology to reduce human-machine conflict, as the goal is for AI to augment human capabilities, not to replace them. We provide the implications of the paper for theory and practice.

Keywords: artificial intelligence; supply chain management; stages of supply chains; emerging technology; promise; framing; challenges; guidelines.

DOI: 10.1504/IJLSM.2023.130782

International Journal of Logistics Systems and Management, 2023 Vol.44 No.4, pp.458 - 488

Received: 31 Aug 2020
Accepted: 03 Feb 2021
Published online: 07 May 2023 *

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