Blockchain-Integrated AI for Transparent Supply Chain Management

Abstract

The increasing complexity and globalization of modern supply chains have intensified challenges related to transparency, traceability, trust, and operational efficiency. Traditional supply chain management systems often suffer from fragmented data silos, limited real-time visibility, and vulnerability to fraud and manipulation. To address these limitations, this study proposes a blockchain-integrated artificial intelligence framework for transparent and intelligent supply chain management. Blockchain technology provides an immutable, decentralized, and auditable ledger that ensures data integrity and provenance across multi-stakeholder environments, while artificial intelligence enhances predictive analytics, demand forecasting, anomaly detection, and decision optimization. The synergistic integration of these technologies enables secure data sharing, automated smart contract execution, and real-time monitoring of supply chain events. This paper presents a conceptual architecture outlining data acquisition, blockchain-based transaction validation, and AI-driven analytics layers. Key application scenarios, including supplier evaluation, logistics optimization, counterfeit detection, and sustainability monitoring, are discussed. Furthermore, the study examines implementation challenges such as scalability, interoperability, energy consumption, and regulatory compliance. The findings indicate that blockchain-integrated AI systems have significant potential to enhance accountability, operational resilience, and trustworthiness in next-generation supply chains, thereby supporting data-driven decision-making and sustainable industrial ecosystems.