Blockchain-Integrated AI for Transparent and Adaptive Supply Networks

Read full text
Authors: Phani Kumar Gutta, Satya Katragadda
Cited by: 0

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