Independent Researcher, USA, Olamidotun Nurudeen Michael, Omodolapo Eunice Ogunsola
Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing data-driven decision-making, improving resource utilization, and supporting sustainable food production. This review explores how AI-based tools—such as machine learning, computer vision, and predictive analytics—are reshaping decision processes across key agricultural domains including crop management, livestock monitoring, soil optimization, and supply chain logistics. It examines the integration of AI with Internet of Things (IoT) sensors, drones, and satellite imaging to enable precision agriculture and real-time adaptive strategies. Furthermore, the paper evaluates the ethical, infrastructural, and technical challenges associated with implementing AI-driven systems, particularly in developing regions. Through a synthesis of current literature and emerging case studies, this review highlights the potential of AI to reduce uncertainty, support policy formulation, and foster resilience against climate variability. The paper concludes by identifying future research directions focused on explainable AI (XAI), edge computing, and the democratization of agricultural intelligence systems to ensure inclusivity and global scalability.