Artificial Intelligence (AI) is rapidly transforming agricultural geography in India by integrating spatial analytics, climate data, and digital technologies to enhance farm productivity and income in a sector that supports over 54.6% of the workforce. This study examines the application of AI-driven tools such as remote sensing, Geographic Information Systems (GIS), machine learning, drones, and smart irrigation systems in enabling precision farming and data-driven decision-making. Empirical evidence indicates that AI-based precision agriculture can increase crop yields by up to 30%, while improving resource efficiency and reducing input costs. Additionally, nearly 70% of farmers adopting AI technologies have reported around a 20% improvement in operational efficiency and productivity. AI applications such as crop monitoring, weather forecasting, and advisory platforms contribute to productivity gains of 10–35% and cost reductions of 10–30%, while also reducing crop losses by 15–30% through early detection of pests, diseases, and climatic risks. Furthermore, AI enhances farmers’ income by 10–35% and improves market price realization by 10–20% through better market integration and access to real-time information. Government initiatives, including AI-based monsoon forecasting systems, have already reached over 3.88 crore farmers, while the Digital Agriculture Mission has created a robust data ecosystem with millions of farmer records and mapped crop plots. Despite these advancements, AI adoption remains limited to only 20–25% of farmers due to financial constraints (60–70%), digital literacy gaps (55–70%), and inadequate infrastructure (50–65%). The study concludes that although AI has strong potential to promote sustainable, efficient, and climate-resilient agriculture, its widespread impact depends on inclusive digital access, capacity building, and supportive policy frameworks to ensure equitable agricultural development in India.