Artificial intelligence (AI) has appeared as a revolutionary tool in plant taxonomy, increasing the accuracy and efficiency of plant classification and identification. This paper focused on application and advancement of AI technique, Deep Learning (DL) and Machine Learning (ML) algorithm in visual image recognition and extraction of image features for plant identification. This review evaluates the efficiency and accuracy of these AI techniques to overcome traditional method challenges such as human error, time consuming etc. Additionally, this paper focus on limitation of deep learning and machine learning in plant taxonomy, including biased dataset, struggling in identification of similar species or rare species and relying on good quality pictures. By addressing these strengths and limitations, the study provides awareness of the current potential of AI and focuses on its potential to bridge the gaps in classical methods, promoting interdisciplinary approaches to more robust plant classification systems.