Intelligent Supply Chains 5.0: The Role of Artificial Intelligence in Building Predictive, Sustainable and Adaptive Logistics Systems

Abstract

The rapid evolution of supply chain management has necessitated the adoption of advanced technologies to enhance operational efficiency, sustainability, and resilience. This study investigated the role of artificial intelligence (AI) in building Intelligent Supply Chains 5.0, focusing on predictive analytics, adaptive logistics, and sustainable operations. Employing a mixed-methods research design, data were collected through structured surveys from supply chain professionals and semi-structured interviews with key stakeholders in organizations that had implemented AI-driven logistics systems. Quantitative findings indicated significant improvements in demand forecasting accuracy, real-time inventory management, and disruption response, while qualitative insights revealed enhanced decision-making capabilities, operational resilience, and environmental performance. AI-enabled predictive models facilitated precise demand estimations, reducing stockouts and optimizing inventory levels. Adaptive logistics applications allowed dynamic route adjustments and rapid response to unforeseen disruptions, thereby strengthening supply chain resilience. Sustainability outcomes included reductions in carbon emissions, energy consumption, and waste, highlighting AI’s contribution to environmentally responsible operations. Despite these benefits, challenges such as data quality issues, integration complexities, and ethical considerations were identified as critical barriers to successful implementation. The study concludes that AI serves as a strategic enabler for Intelligent Supply Chains 5.0, aligning operational performance with organizational sustainability and resilience objectives. Recommendations include workforce training, enhanced data governance, and ethical AI frameworks to support long-term adoption.