American Journal of Advanced Multidisciplinary Research and Innovation

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Smart Supply Chain Management Through Artificial Intelligence and Blockchain Integration

Author(s) Clayton Rose
Country United States
Abstract The increasing complexity of global supply chains has created significant challenges related to transparency, traceability, operational efficiency, demand uncertainty, counterfeit products, cybersecurity, and sustainability. Traditional supply chain management systems often suffer from fragmented information, manual processes, limited visibility, and inefficient coordination among stakeholders. The integration of Artificial Intelligence (AI) and Blockchain Technology has emerged as a transformative solution for developing intelligent, secure, transparent, and autonomous supply chain ecosystems. Combined with Machine Learning (ML), Internet of Things (IoT), Big Data Analytics, Cloud Computing, Edge Computing, Digital Twin Technology, Robotic Process Automation (RPA), and Smart Contracts, these technologies enable predictive decision-making, real-time monitoring, secure information sharing, automated transactions, and resilient supply chain operations.
This study presents a comprehensive analysis of Smart Supply Chain Management Through Artificial Intelligence and Blockchain Integration. A qualitative analytical research methodology based on secondary data is employed to investigate AI-driven demand forecasting, blockchain-enabled traceability, intelligent logistics optimisation, predictive inventory management, supplier risk assessment, and autonomous supply chain decision support systems. The research evaluates how emerging digital technologies improve operational efficiency, transparency, security, sustainability, customer satisfaction, and organisational resilience.
The findings indicate that AI significantly enhances predictive analytics, demand forecasting, route optimisation, warehouse automation, and intelligent decision support, while blockchain strengthens data integrity, product traceability, supplier verification, secure transactions, and decentralised trust. Integration with IoT sensors enables real-time monitoring of inventory, transportation, environmental conditions, and asset performance. Digital Twin technology facilitates virtual supply chain simulation and optimisation, while cloud and edge computing support scalable, real-time analytics across geographically distributed operations.
Despite these opportunities, challenges remain regarding interoperability, implementation costs, scalability, cybersecurity, regulatory uncertainty, energy consumption, workforce adaptation, and integration with legacy enterprise systems. Future research should investigate explainable AI for supply chain management, federated logistics intelligence, quantum-enhanced optimisation, blockchain interoperability standards, and autonomous self-learning supply chain ecosystems.
The study concludes that Artificial Intelligence and Blockchain integration provides a multidisciplinary foundation for developing intelligent, transparent, secure, and sustainable supply chain management systems capable of supporting global industrial competitiveness and resilient economic development.
Keywords : Smart Supply Chain, Artificial Intelligence, Blockchain, Machine Learning, Internet of Things, Logistics Optimisation, Smart Contracts, Digital Twin, Predictive Analytics, Sustainable Supply Chain.
Field Engineering
Published In Volume 2, Issue 2, March-April 2020
Published On 2020-03-08
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