AI Management for Strategic Resilience in Global Trade

Abstract

Geopolitical tensions, supply chain disruptions at the time of the pandemic, and rapid technological advancements have all highlighted key shortcomings in the global trading system. This article explores the ways in which AI management frameworks can contribute to strategic resilience in global trade networks. Based on World Trade Organization, 2024, McKinsey Global Institute (2023) and the International Monetary Fund (IMF) World Economic Outlook (2025), we examine patterns of AI adoption in 47 multinational companies in Asia-Pacific trade corridors between 2021 and 2025. The results show that companies that adopted AI-based supply chain risk management tools reported a 34% cost savings in disruption related costs and a 28% increase in demand forecast accuracy over non-AI adopting companies. We propose a three-pillar Strategic Resilience AI Framework (SRAIF) of predictive analytics, autonomous supplier diversification and real-time trade compliance monitoring. Policy implications for policy makers, trade practitioners and management scholars are discussed.