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This paper proposes an AI-Based Precision Sprayer system that is used for precise plant disease management in agricultural contexts. The system is meant to be an improvement to conventional methods of spraying pesticides. In typical farming fields, farmers spray pesticides all over the crops in a field. This can result in a lot of inefficiency, higher costs and pollute the environment. This paper proposes to integrate computer vision, machine learning and a sprayer to create a system that can precisely spray the required pesticides to the affected parts of the plants. The proposed system uses a camera for image processing and uses Convolutional Neural Networks (CNNs) to recognize diseases in plants. After the recognition of diseases in plants, the proposed system enables the precision spraying unit to spray the required pesticides only to the affected parts of the plants thus preventing the use of excessive amounts of pesticides that can harm other parts of the plants and the environment. This proposed system will thus facilitate the healthy growth of the crops, promote green agriculture, and enable the farmers to manage plant diseases promptly and productively.