AI-Driven Strategies for Rebuilding Food Security in Post-Conflict Northern Nigeria: Opportunities, Challenges, and Policy Implications

Abstract

Due to years of conflict that have uprooted communities, damaged agriculture, and disturbed markets, Northern Nigeria's food systems are in dire need of repair.  These complicated issues cannot be resolved by traditional rehabilitation techniques alone.  In order to reconstruct food security in post-conflict situations, this article investigates the potential of artificial intelligence (AI) as a transformative instrument. AI can boost agricultural productivity, facilitate prompt decision-making, and increase the resilience of food systems by utilizing technologies like predictive modeling, climate monitoring, automated crop assessment, and data-driven supply-chain management. The study also takes into account the barriers to AI adoption, such as inadequate infrastructure, technological skill gaps, and governance issues, and highlights the significance of context-sensitive approaches. The results indicate that responsible and locally tailored AI strategies have the potential to speed up recovery, fortify early-warning systems, and develop sustainable food security solutions for Northern Nigeria following conflict.