Artificial intelligence (AI) is becoming more prevalent in plant science, however it is far from being routinely and effectively utilized in this field. After providing a brief overview of the motivations behind the interest in data science and artificial intelligence in plant science, the paper outlines and addresses eight crucial data management issues that need to be addressed in order to fully realize the potential of AI in crop and agronomic research, particularly the application of Machine Learning (AI), which holds great promise in this domain. Different AI techniques, such as convolutional neural networks, artificial neural networks, and deep learning, have been successfully used for disease detection in rice, wheat, maize, cotton, tomato, peas, potato, cucumber, sweet paper, tea, berries, peaches, grapes, olives, mango, bananas, and so forth. This chapter discusses several AI systems developed and employed in agriculture for plant disease diagnosis, as well as future prospects for precision farming. In this paper, we will discuss. The role of artificial intelligence in the plant.