INTEGRATING STRATEGIC MANAGEMENT PRACTICES WITH AI FOR PROACTIVE RISK MITIGATION IN GLOBAL SUPPLY CHAIN

Abstract

Due to pandemics, geopolitical uncertainties, and environmental risks, the global supply chains have experienced unprecedented disruptions over the past years. The traditional risk management approaches such as safety stocks, and backup suppliers have reactive characteristics which are insufficient to efficiently respond to those unprecedented uncertainties. This study highlights the importance of shift towards proactive risk management approaches and presents a conceptual review. With the application of framework-based research design, the significance of AI-driven decision making is highlighted through conceptual framework. The framework conceptualizes a practical relationship between integration of AI with strategic management practices and proactive risk mitigation with supply chain visibility as mediator. Based on cross-case comparison of selected cases, this study interprets that how AI capabilities machine learning, predictive analytics and real-time monitoring can convert traditional decision-making to AI-driven decision making to ensure proactive risk mitigation. Through a structured framework, this study provides theoretical and practical contributions by extending exiting literature and enhancing AI-driven risk mitigation across global supply chains.

Keywords: Artificial intelligence, strategic management practices, proactive risk, predictive analytics, supply chain visibility, risk mitigation.