Abstract Artificial Intelligence plays a key role in this by optimizing resource utilization and improving crop management. Through advanced data analytics and machine learning, AI can analyze soil health, weather patterns, and crop performance. The most effective use of AI in agriculture is predictive analytics. AI-powered analytics tools analyze historical and real-time data to predict future outcomes. AI's ability to process large amounts of data, identify patterns, and automate decision-making can dramatically increase efficiency. AI is used in agriculture for land use mapping and crop detection, crop yield monitoring, flood-prone area detection, pest and disease monitoring, drought prediction, soil quality analysis, and soil productivity detection. AI and drones are not here to replace farmers they are here to support them. These tools reduce manual labour, increase profits, and help conserve natural resources. AI can play a key role in this by optimizing resource utilization and improving crop management. Through advanced data analytics and machine learning, AI can analyze soil health, weather patterns, and crop performance to predict crop yields.
Ashok Shamrao Patil (2025) studied this question.