Ai-Driven Blockchain Framework For Transparent And Tamper-Proof Supply Chain Management: A Performance Evaluation

Abstract

The increasing complexity of global supply chains has amplified challenges related to transparency, traceability, fraud prevention, and data integrity. Supply chain fraud, counterfeiting, and operational opacity are estimated to cost the global economy approximately $4.5 trillion annually [1], highlighting the urgent need for secure and intelligent monitoring mechanisms. Traditional centralized supply chain management systems often suffer from limited auditability, lack of real-time visibility, and vulnerability to single-point failures, making them inadequate for modern interconnected ecosystems [2]. This paper presents a novel AI-driven blockchain framework for enhancing transparency and tamper-proof integrity in global supply chains. Supply chain fraud, counterfeiting, and opacity cost the global economy an estimated $4.5 trillion annually [1]. Existing centralized solutions lack auditability and remain vulnerable to single-point failures [2]. The proposed system integrates machine learning anomaly detection with permissioned blockchain ledgers and autonomous smart contracts, achieving 96.1% traceability accuracy a 23.7% improvement over baseline systems. Transaction latency was reduced from 4.8 seconds to 1.2 seconds. A dataset of 120,000 simulated supply chain events across pharmaceutical, food, and electronics sectors was used for validation. The framework demonstrates statistically significant improvements (p < 0.01) across all key performance metrics [3].