Artificial Intelligence (AI) has rapidly emerged as a transformative technology in agriculture, offering innovative solutions to enhance productivity, sustainability, and efficiency. This comprehensive review examines the role of AI in various agricultural practices, including precision farming, crop management, soil health monitoring, pest control, and predictive analytics. By leveraging AI-driven technologies such as machine learning, computer vision, and data analytics, farmers can make data-informed decisions to optimize resource usage, reduce input costs, and minimize environmental impacts. Additionally, AI has proven instrumental in developing automated systems like autonomous tractors, drones, and robotic harvesters, which streamline labor-intensive processes. Despite its potential, the adoption of AI in agriculture faces several challenges, including high implementation costs, data privacy concerns, and the need for adequate infrastructure in rural areas. The paper highlights ongoing research and future directions in AI-powered agriculture, focusing on the development of more accessible and scalable solutions for smallholder farmers. In conclusion, AI is poised to revolutionize agriculture by enabling more efficient, sustainable, and resilient food systems, provided that challenges related to accessibility and ethical concerns are addressed.