Enhancing Accountability While Preserving Privacy

Abstract

Supply chain systems increasingly rely on digital technologies to enhance transparency and efficiency, yet this often conflicts with the need to protect sensitive data. Traditional verification mechanisms typically require full data disclosure, raising concerns related to privacy and security. This study proposes the use of zero-knowledge proofs (ZK-proofs) as a privacy-preserving solution within AI-driven supply chains. By enabling verification without revealing underlying data, ZK-proofs help maintain trust while safeguarding confidentiality. Using a conceptual and analytical approach, this research develops an integrated framework combining artificial intelligence, blockchain, and ZK-proofs within a governance structure. The findings suggest that this integration enhances transparency, strengthens security, and supports ethical and regulatory compliance, making it a promising approach for future digital supply chain systems.