The progress of Artificial Intelligence (AI) in agriculture is substantial, primarily due to its ability to automate data collection, enhance decision-making, increase productivity, and support environmental sustainability. This article focuses on the role of AI in agriculture, which includes precision farming, smart monitoring of crops and soils, innovative irrigation techniques, pest and disease management, and crop yield forecasting. It reviews various functionalities, regional case studies, and AI adoption's socio-economic implications in developed and developing regions. Additionally, the research identifies key challenges such as data availability, high operational costs, low digitalization rates, inadequate infrastructure, and skill shortages, while proposing strategic solutions to overcome these obstacles. The unification of AI with IoT, blockchain, and 5G technologies for creating comprehensive smart farming systems is also explored for potential opportunities. This research aims to assess how AI can be applied to enhance the efficiency, resilience, and sustainability of agricultural practices.