INTEGRATING ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN RISK MANAGEMENT: IMPLICATIONS FOR REGIONAL TRADE IN SOUTHEAST NIGERIA

Abstract

Global supply chains are increasingly exposed to complex risks arising from infrastructural fragility, regulatory inconsistencies, and market volatility, particularly in emerging economies. This study investigates the role of Artificial Intelligence (AI) in enhancing Supply Chain Risk Management (SCRM) and advancing regional trade competitiveness in Southeast Nigeria. Adopting a quantitative research design, data were collected from 400 supply chain practitioners, logistics managers, and SME operators across the five southeastern states. The study employed descriptive statistics, Pearson correlation, and multiple regression analysis using SPSS v26. The findings reveal a statistically significant positive relationship between AI adoption and supply chain performance outcomes: operational risk mitigation (r = 0.979), resilience improvement (r = 0.985), and trade efficiency (r = 0.988), all at p < 0.001. These results confirm that AI tools such as predictive analytics, real-time monitoring, and autonomous decision support act as dynamic capabilities that enhance responsiveness, resilience, and competitiveness in fragile trade environments. Theoretically, the study extends the Dynamic Capabilities Theory (DCT) by contextualizing AI as a resilience-enabling competence, while the Technology-Organization-Environment (TOE) framework explains adoption pathways under infrastructural and institutional constraints. Practically, the study provides managers with evidence-based insights for investing in AI-enabled solutions, while policymakers are urged to establish regulatory harmonization, digital skills development, and ethical AI frameworks to scale adoption.