Abstract

Artificial Intelligence (AI) is transforming agriculture by improving precision, efficiency, and sustainability. Key technologies like machine learning, deep learning, computer vision, and remote sensing enable early pest and disease detection, real-time crop monitoring, and precision practices such as variable-rate inputs, soil mapping, and autonomous machinery. AI-driven decision support integrates climate, soil, and market data for yield prediction and harvest planning. Case studies highlight scalable applications, while challenges include technical limits, data privacy, ethics, and socioeconomic barriers. AI offers a path to resilient, sustainable, and globally secure food systems.