QUALITY AGRICULTURAL EDUCATION IN CRISES CONTEXTS:  THE ROLE OF ARTIFICIAL INTELLIGENCE (AI) IN OVERCOMING INSECURITY CHALLENGES IN NIGERIA

Nigeria’s agricultural educational sectors currently facing multiple challenges, including a traditional instructional model that limits the development of 21st -century competencies and a volatile socio-technical environment marked by persistent regional insecurity. This instability, particularly in the Northern and rural areas, has disrupted physical access to learning environments and contributed to high levels of out-of-school children, with implications for Nigeria’s long-term human capital development. The paper examines the potential of Artificial Intelligence (AI) as a tool for sustaining quality agricultural instruction in conflict-affected contexts.  The study explores the integration of an AI-driven Adaptive Learning System (ALS) and an Intelligent Tutoring System (ITS) to support flexible and personalized agricultural education. Findings indicate AI functions as a “pedagogical amplifier’’ by enabling personalized remote tutoring and automated feedback, which can reduce the need for physical attendance in high-risk conflict zones. Furthermore, the use of precision AI tools such as drones for crop monitoring and machine learning models for disease detection can modernize agricultural curricula and reduce the perception of farming as labor-intensive, potentially increasing youth interest in vocation agriculture. The study concluded that leveraging AI in crisis contexts can help reduce educational inequality and support the continuity of agricultural education, contributing indirectly to national security resilience. This research provides a framework for policy makers to integrate technology-based crisis-responsive approaches into the national agricultural curriculum.