Leveraging AI for real-time sustainable supply chain visibility: Benefits and implementation barriers

Nyamekeh, Richmond and Yusuf, Samuel Omokhafe and Afoakwah, Bernard and Oluwadare, Olaitan Ebenezer and Yusuf, Nathan and Eyaru, Joshua (2025) Leveraging AI for real-time sustainable supply chain visibility: Benefits and implementation barriers. World Journal of Advanced Research and Reviews, 26 (2). pp. 422-434. ISSN 2581-9615

This study explores the role of Artificial Intelligence (AI) in enhancing real-time sustainable supply chain visibility, addressing its benefits and implementation challenges. With supply chains becoming increasingly complex and globalized, the need for transparency, efficiency, and sustainability has never been greater. AI-powered systems offer transformative potential by enabling real-time tracking, predictive analytics, and data-driven decision-making, which improve operational efficiency and support sustainability goals. However, the adoption of AI in supply chains faces significant barriers, including high costs, data integration challenges, resistance to change, and ethical concerns. The research employs a comprehensive literature review to analyze existing studies on AI applications in supply chain management, focusing on demand forecasting, logistics optimization, waste reduction, and sustainability. The study identifies key benefits of AI, such as improved decision-making, enhanced transparency, cost reduction, and environmental impact mitigation. It also highlights critical implementation challenges, such as financial constraints, data quality issues, workforce upskilling needs, and cybersecurity risks. Key findings reveal that AI can significantly enhance supply chain visibility and sustainability but requires strategic planning, investment in infrastructure, and collaboration among stakeholders. The study concludes that while AI holds immense potential for transforming supply chains, addressing implementation barriers and ethical considerations is crucial for its successful adoption. Future research should focus on empirical studies, long-term sustainability impacts, and the integration of AI with emerging technologies like blockchain and IoT. This paper contributes to the growing body of knowledge on AI-driven supply chain management, offering practical insights for organizations aiming to leverage AI for sustainable and resilient operations.