Artificial intelligence (AI) and blockchain technology have become game-changing tools that can solve most of the underlying supply chain management challenges and improve end-to-end visibility in global supply chains by providing predictive approaches for risk mitigation in manufacturing. The present study attempts to quantify the link between AI-enabled visibility and important supply chain performance metrics by concentrating on predictive methodologies and offers evidence that can be used to influence the adoption of new innovative technologies. The findings revealed a statistically significant correlation between industry sector and the belief that AI risk scores accurately detect delayed shipments or products (χ²(8, N = 50) = 67.39, p <.001). The results of the ANOVA demonstrated that the regression model accounted for all of the variance in the dependent variable.  From a substantive perspective, the findings show how crucial AI-driven risk management solutions are to facilitating seamless data flow integration amongst different supply chain systems.   The results suggest that when risk ratings are precise, timely, and operationally sound, integration across ERP, WMS, TMS, MES, and supplier portals is fully achieved.