Effectiveness of Artificial Intelligence in the Detection and Prevention of Violent Crimes in Niger State, Nigeria

This study examined the effectiveness of artificial intelligence (AI) in the detection and prevention of violent crimes in Niger State, Nigeria, with emphasis on evaluating operational outcomes and identifying strategies for strengthening AI integration in the state's security architecture. A quantitative descriptive survey design was adopted. The population comprised operational and intelligence personnel of the Nigeria Police Force (NPF), Nigeria Security and Civil Defence Corps (NSCDC), and Nigerian Vigilante Group (NVG) in Niger State, totalling 1,623 personnel. Using Yamane's formula, a sample of 321 was determined; 350 respondents were targeted to account for attrition, and 327 valid responses were analysed using frequency distribution, mean, and standard deviation. The instrument demonstrated strong internal consistency (overall α = 0.85; sub-scales: 0.82 and 0.88). Findings revealed that AI-driven approaches are currently of limited effectiveness (grand mean = 2.88, below the 3.00 agreement threshold), constrained by minimal deployment, inadequate infrastructure, insufficient training, and weak institutional support. Conversely, respondents strongly endorsed a comprehensive set of enhancement strategies (grand mean = 4.25), prioritising infrastructure investment, institutionalised training, dedicated policy frameworks, inter-agency data sharing, and research partnerships. It is recommended that government and relevant stakeholders urgently invest in AI-enabling infrastructure, develop context-specific AI adoption strategies, and build institutional capacity to support effective AI integration into Niger State's security operations.