Blockchain-Integrated AI for Transparent and Adaptive Supply Networks
Abstract
Global supply networks are now more prone to volatility, fragmentation, and trust issues, driven by geopolitical risks, sustainability pressures, regulatory demands, and supplier fragmentation. While Artificial Intelligence (AI) has made significant strides in predictive analytics and optimization, its capabilities are still restricted by data silos, lack of transparency, and data integrity issues in global supply ecosystems. On the contrary, blockchain technology offers decentralized trust, immutability, and transparent transaction tracking, but it does not provide adaptive intelligence and predictive capabilities for decision-making. The current research proposes the concept of Blockchain-Integrated Artificial Intelligence (BI-AI), which promises the capability for transparent and adaptive global supply networks. The proposed BI-AI architecture integrates the blockchain technology for building a transparent supply network with Artificial Intelligence for analytics, demand forecasting, risk prediction, and autonomous response capabilities. The current research proposes a multi-layer governance structure that integrates IoT technology for data acquisition, blockchain for building trust, AI for analytics and response, and compliance for regulatory demands. The strategic implications, implementation challenges, and future research directions are also discussed in the context of the proposed BI-AI architecture. The current research contributes to the emerging discussion on the concept of intelligent decentralized global supply ecosystems and offers opportunities for future research and empirical validation for the proposed architecture.
Fields of Study & Subjects
Blockchain Technology Applications and Security
Impact of AI and Big Data on Business and Society
Supply Chain Resilience and Risk Management
Publication details
- Journal / source
- Journal of Mechanical Civil and Industrial Engineering
- Volume
- 7
- Issue
- 3
- Pages
- 01–05
- Publication date
- 17 February 2026
- Language
- EN