Trisatin Panggabean; Salsabila Yusra; Sri Ratna Dewi
This research explores the implementation of computer vision technology in AI-based e-commerce platforms to enhance product identification and improve user experience. The study specifically examines the use of deep learning algorithms, particularly Convolutional Neural Networks (CNN), to automate product recognition and classification. The results indicate that AI-driven image search features significantly increase the speed and accuracy of product search, leading to greater customer engagement. However, challenges such as the need for high-quality datasets, varying image quality, and high initial investment costs were identified as barriers to effective implementation. The findings suggest that overcoming these obstacles can lead to improved operational efficiency and customer satisfaction. The success of AI in e-commerce depends on robust infrastructure, data quality, and skilled workforce training.