This study describes an artificial intelligence (AI)-based object identification system for detecting real-world items and superimposing digital information in Augmented Reality (AR) settings. The system evaluates the camera stream from an AR device for real-time recognition using deep learning algorithms trained on a collection of real-world items and their related digital information. Object recognition applications in AR include gaming, education, and marketing, which provide immersive experiences, interactive learning, and better product presentations, respectively. However, challenges such as acquiring larger and more diverse datasets, developing robust deep learning algorithms for varying conditions, and optimizing performance on resource-constrained devices remain. The AI-based object recognition system demonstrates the potential to transform AR experiences across domains, while emphasizing the need for ongoing research and development to fully realize its capabilities.