International Journal of Business, Law and Political Science
Vol. 2 No. 12 (2025): International Journal of Business, Law and Political Science

DEVELOPMENT OF AI-DRIVEN PREDICTIVE ANALYTICS SYSTEMS TO IMPROVE SUPPLY CHAIN RESILIENCE AND STRENGTHEN THE STABILITY OF CRITICAL U.S. INDUSTRIES

Singh, Priyanka (Unknown)
Patel, Mulayam Singh (Unknown)

Article Info

Publish Date
12 Dec 2025

Abstract

Objective: This paper presents a comprehensive framework for developing AI-driven predictive analytics systems designed to enhance supply chain resilience in critical U.S. industries. Method: The proposed methodology integrates machine learning algorithms with real-time data processing capabilities to forecast disruptions, optimize inventory management, and strengthen supply chain stability. Results: Our experimental results demonstrate significant improvements in demand forecasting accuracy (up to 23%) and reduction in supply chain disruption response time by 35%. Novelty: The findings contribute to the growing body of knowledge on intelligent supply chain management and provide practical insights for industry practitioners seeking to leverage AI technologies for operational excellence.

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Journal Info
International Journal of Business, Law and Political Science
Website

Abbrev

IJBLPS

Publisher

PT. Antis International Publisher

Subject

Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

Description

International Journal of Business, Law and Political Science - ISSN (Online) 3032-1298 is a peer-reviewed (refereed), open-access journal in the domain of finance and management sciences. IJBLPS seeks to advance multidisciplinary researchers by publishing the highest quality theoretical and ...