Agriculture has made significant improvements in recent years thanks to artificial intelligence (AI) technologies. Traditional farming methods have been transformed by AI approaches, such as machine learning, computer vision, and data analytics, which have improved productivity, sustainability, and resource management. The use of machine learning algorithms has improved the ability to estimate crop yield, identify diseases, and manage pests. These algorithms can deliver precise insights for well-informed decision-making by analysing enormous volumes of historical and real-time data such as weather patterns, soil characteristics, and crop growth stages. In order to enable prompt treatments and lower crop losses, computer vision technologies are helping to identify plant illnesses and nutritional deficits. Utilising AI to modify agricultural practices on a per-plant or per-section basis, precision agriculture has emerged as a significant area of advancement. AI-powered solutions enable real-time monitoring of soil moisture levels through IoT devices and sensor networks, enabling precise irrigation techniques that preserve water resources and lower costs. AI algorithms are altering labour-intensive farming chores including planting, fertilising, and harvesting, alleviating the labour crisis and increasing productivity. AI can help in streamlining distribution routes, reducing waste, and assuring on-time delivery by combining data from diverse sources. Additionally, AI-driven platforms provide insights into consumer trends and tastes, assisting farmers in matching their output to market demand.