INSTITUTIONAL READINESS, IMPLEMENTATION CHALLENGES, AND STRATEGIC POLICY FRAMEWORKS FOR AI-DRIVEN CUSTOMS MODERNIZATION IN NIGERIA
Abstract
This study quantitatively examined institutional readiness, implementation challenges, and strategic policy frameworks for Artificial Intelligence (AI)-driven customs modernization within the Nigeria Customs Service. A descriptive survey design was employed, with data collected from approximately 500–600 customs officers selected through stratified random sampling. Structured questionnaires measured technical, organizational, and regulatory challenges, officer readiness, and policy strategy preferences using a five-point Likert scale. Data were analyzed using descriptive statistics (frequencies, means, and standard deviations). Findings reveal a moderate level of implementation challenges (Grand Mean = 2.92), with the most significant constraints being lack of skilled personnel (Mean = 3.03), budget limitations (Mean = 3.02), and insufficient technical infrastructure (Mean = 2.99). Officer and stakeholder readiness was also moderate (Grand Mean = 2.72), although gaps were observed in training adequacy (Mean = 2.48) and digital literacy program implementation (Mean = 2.43). Conversely, there was strong agreement on strategic interventions required for AI integration (Grand Mean = 3.16), particularly in training and capacity building (Mean = 3.27), legal/ethical frameworks (Mean = 3.23), and structured policy development (Mean = 3.19). The study concludes that while institutional momentum toward AI adoption exists, successful implementation is constrained by human, technical, and regulatory deficits. However, strong stakeholder support for structured reforms indicates high potential for scalable AI integration if policy and capacity gaps are addressed.
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References
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