Department of Industrial Engineering, Faculty of Engineering, Texas A&M University, Kingsville, Texas, United States of America.
Received on 20 April 2023; revised on 25 May 2023; accepted on 28 May 2023
Supply chain visibility (SCV) is critical for improving transparency, traceability, and responsiveness in global supply networks. Traditional methods often struggle to provide end-to-end visibility due to fragmented data sources, manual tracking, and lack of trust among stakeholders. This paper proposes a hybrid framework that integrates Blockchain technology and Artificial Intelligence (AI) to enhance SCV. Blockchain provides an immutable, decentralized ledger to improve trust and data sharing, while AI enables predictive analytics, anomaly detection, and automation. Through a combination of conceptual modeling and case-based analysis, the study explores how Blockchain-AI synergy addresses data silos, enhances decision-making, and promotes real-time insights across procurement, logistics, and inventory functions. The findings indicate that the integrated system improves operational efficiency, reduces fraud, and strengthens compliance. This research offers practical guidelines for implementing Blockchain-AI systems and outlines future directions for scalable and ethical adoption. By situating this study in the post-pandemic global supply chain landscape, it responds to growing industry calls for resilient and adaptive technologies that support sustainability and data integrity.
Supply Chain Visibility; Blockchain; Artificial Intelligence; Transparency; Predictive Analytics; Smart Contracts
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Oluwatumininu Anne Ajayi. Integrating Blockchain and Artificial Intelligence to improve supply chain visibility. World Journal of Advanced Engineering Technology and Sciences, 2023, 09(01), 476–479. Article DOI: https://doi.org/10.30574/wjaets.2023.9.1.0165