Artificial Intelligence (AI) in Agriculture

AI analyzes massive datasets to predict outcomes—like yield forecasts, pest risks, and optimal harvest time. Machine learning models can detect early disease signs from leaf images or satellite data. AI drones are now capable of scanning thousands of hectares, identifying nutrient deficiencies within seconds. In logistics, AI forecasts demand and optimizes distribution routes to reduce waste. Example: Plantix and IBM’s Watson Decision Platform for Agriculture help farmers make data-driven decisions. Future outlook: AI will soon act as a “digital agronomist,” customizing advice for each farm.