Journal of Advances in Developmental Research

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AI-Powered Disruption Prediction and Response Framework for Global Supply Chain Networks Under Geopolitical Uncertainty

Author(s) Mr. Sahil Bansal
Country United States
Abstract Global supply chain networks face unprecedented vulnerability to geopolitical disruptions including trade wars, tariff escalations, sanctions, regional conflicts, and shifting manufacturing policies that create cascading operational failures across interconnected nodes. Traditional risk management approaches rely on reactive, manual assessment processes that detect disruptions only after significant operational and financial damage has materialized. This paper presents an AI-powered predictive framework that leverages Natural Language Processing (NLP), machine learning classification models, and real-time geopolitical signal ingestion to anticipate supply chain disruptions 4–8 weeks before physical impact. The proposed five-layered architecture integrates structured supply chain data with unstructured geopolitical intelligence from news feeds, trade policy databases, regulatory filings, and social media sentiment to generate risk scores, trigger automated contingency plans, and recommend optimal response strategies. A multi-objective optimization engine balances cost, lead time, and resilience objectives when activating alternative sourcing, rerouting, or inventory pre-positioning responses. Organizations deploying this framework report up to 55% faster disruption response times, 40% reduction in disruption-related revenue losses, and 30% improvement in supply chain recovery speed compared to traditional risk management approaches.
Keywords Artificial Intelligence, Supply Chain Disruption, Geopolitical Risk, Natural Language Processing, Predictive Analytics, Supply Chain Resilience, Risk Management, Multi-Objective Optimization
Published In Volume 16, Issue 2, July-December 2025
Published On 2025-12-06
DOI https://doi.org/10.71097/IJAIDR.v16.i2.2130
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Crossref DOI prefix of IJAIDR is 10.71097/IJAIDR

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