Barriers Related to AI Implementation in Supply Chain Management

Abstract

The primary objective of this paper is to offer a structured and comprehensive list of the barriers associated with implementation of Artificial Intelligence (AI) solutions in Supply Chain Management (SCM). While the broader field of AI has made rapid advances in a relatively short period of time, there are significant barriers that still need to be addressed to harness the true potential of AI. SCM’s dependency on multi-actor collaboration, disparate data sources, unwillingness of actors to embrace AI, change management issues, and lack of AI governance framework poses significant barriers for successful implementation of AI. Drawn from extensive literature review as well as real-world experience, this paper systematically explores and compiles a robust list of barriers of AI implementation in supply chain functions by categorizing them and elaborating their impact at inter- and intra-organizational SCM. Lastly, the paper offers recommendations for practitioners, policymakers, researchers, and governments on how they can work together for AI to be successful.

Predicting the Intention to Adopt Innovation in Supply Chain Finance

“…Over time, models based on artificial intelligence applications, such as artificial neural networks and deep learning, have been highlighted in various scientific studies and applications in different sectors (Chang, Wang, & Chuang, 2022;Du & Shu, 2022;Feng & Chen, 2022;Hossain et al, 2022;Hou et al, 2022;Li, Shang et al, 2022;Paul, Riaz, & Das, 2022;Qiu, 2022;Rashidin et al, 2022;Shrivastav, 2022;Sun et al, 2022;Varsha et al, 2021;Wu, Qiao et al, 2022;Wu, Zhu et al, 2022;Xu, Xiang, & He, 2022;Yang & Wu, 2022;Zhao, 2022). However, the financial sector -FinTech, has shown strong growth in using this method to provide financial solutions.…”

How to Complete Supply Chain Integration and Improve Supply Chain Performance Through Relationship Governance in the Digital Age

“…When enterprises or organizations try to improve SCP, they may face multiple risks and challenges, such as unstable market demand, a shorter product life, and inventory cost pressure. Therefore, enterprises need to make use of SCI (Rajaguru & Matanda, 2019;Wu & Chiu, 2018), supplier relationships, customer relationship management (Ziggers & Henseler, 2016), information technology (Han et al, 2017), information flow (Akcay et al, 2017), top management commitment (Lam & Rahma, 2014;Shrivastav, 2021) and other strategic means to improve SCP.…”

Artificial Intelligence Application in Supply Chain Management in the Government Sector of Pakistan

“…The prompt progressions in the arena of AI have facilitated its development in multiple domains of SCM. Previous research presents a comprehensive overview of the principal domains in which effective implementation of AI has been documented in scholarly liter-ature [11]. The advantages of implementing AI encompass enhanced SCM performance in warehouse management [12], reduced costs, enhanced customer satisfaction through ensuring product availability, and decreased downtime through scheduled maintenance, ultimately leading to increased SCM performance [13].…”