Resilient Supply Chains in Industry 5.0: Leveraging AI for Predictive Maintenance and Risk Mitigation

Abstract

This integrative literature review investigates the transformative impact of artificial intelligence (AI) on supply chain management, addressing the pressing need for efficiency and robustness through AI-driven predictive maintenance, machine learning (ML), and decision support systems. By examining current literature, the study highlights AI's potential to automate and revolutionize supply chain operations, enhancing speed, accuracy, and risk management capabilities while identifying significant challenges such as bias mitigation, algorithmic transparency, and data privacy. The methodology involves a comprehensive review of scholarly articles, reports, and academic publications, focusing on AI applications in predictive maintenance, risk mitigation, and decision-making processes. The analysis reveals significant improvements in operational efficiency and accuracy due to AI, alongside concerns about biases, transparency, and implementation issues. The findings confirm AI's transformative potential in supply chain management but emphasize the necessity for ongoing supervision, regular audits, and the development of AI models capable of detecting and rectifying operational anomalies. The study proposes creating roles such as AI Supply Chain Oversight Officer (AISCO), AI Supply Chain Compliance Officer (AISCCO), and AI Supply Chain Quality Assurance Officer (AISQAO) to ensure responsible AI utilization, maintaining the integrity and efficiency of supply chain operations while addressing implementation challenges. The review concludes that AI is promising for transforming supply chains; however, careful implementation is crucial to uphold operational integrity and resilience. Future research should prioritize longitudinal studies to evaluate AI's long-term impact, focus on addressing implementation concerns, and ensure fair and transparent integration of AI technologies. These findings have significant implications for practice and policy, underscoring the need for robust frameworks and regulatory measures to guide the effective use of AI in supply chains.

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