The high-rate demand for food security and sustainable agriculture in Nigeria; the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) into farming practices is essential. This study presents a smart farming framework that leverages on AI-powered analytics and IoT-enabled sensing technologies to enable real-time monitoring, predictive decision-making and automation of agricultural operations. Using environmental sensor data and machine learning models, the system accurately predicts irrigation needs, detects pest infestations and forecasts produces. A pilot case study on tomato farming in Kaduna revealed that a 25% reduction in water usage leads to a 15% increase in harvest; it validated through comparative analysis with traditional farming methods. Apart from technical improvements, the framework enables smallholder farmers through democratizing access to digital decision-support tools. The findings highlight the transformative potential of AI and IoT- agriculture in improving food security, resource efficiency and climate resilience in Nigeria. Policy pathways and national implementation guidelines are also proposed.