Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic disparities, poor sanitation, and environmental factors such as recurrent flooding. This narrative review examines cholera outbreaks in Nigeria, exploring epidemiological trends, socioeconomic and meteorological drivers, and advancements in diagnostic technologies. Emphasis is placed on the role of artificial intelligence (AI) in transforming cholera management through predictive modeling, early detection, and resource optimization. Rapid diagnostic tests (RDTs), molecular diagnostics, and biosensors are highlighted as tools for enhancing surveillance and improving outbreak response. Despite these advancements, Nigeria faces significant challenges, including inadequate laboratory infrastructure, insufficient environmental monitoring, and limited access to diagnostic tools in rural areas. Recommendations include strengthening diagnostic capacity, integrating AI-driven tools, and implementing proactive environmental surveillance. The manuscript underscores the importance of coordinated efforts among federal and state health agencies, international partners, and local communities to address the persistent cholera burden. By leveraging these strategies, Nigeria can improve its outbreak preparedness and mitigate the morbidity and mortality associated with cholera. This review provides actionable insights for public health interventions and policy-making, offering a forward-looking perspective on combating cholera through innovation and collaboration.