AI-Driven Recommendations: A Systematic Review of the State of the Art in E-Commerce

Electronic commerce has a strong connection with recommendation processes. There are various forms of recommendations, ranging from virtual assistants to online suggestions made in real time. Different algorithms and technologies are utilized for each form, and the choice of technique is dependent on the task at hand. For instance, artificial intelligence may utilize deep learning or machine learning techniques. The type of data also plays a role in determining the techniques used. Predictive modeling is applied to textual data, while image data requires image processing followed by AI algorithms for prediction. This study aimed to investigate the extent to which artificial intelligence is utilized in recommender systems for electronic commerce, as well as the current and future trends in the field. This was achieved through a systematic literature review of scientific articles from the past decade, using WosViewer for data collection and the Bibliometrix R package for analysis. The findings demonstrate that artificial intelligence works in conjunction with other technologies, such as blockchain, virtual reality, and augmented reality, to enhance the consumer experience throughout the e-commerce process.

Automated summary

Electronic commerce is closely connected to recommendation processes, which can take various forms such as virtual assistants and real-time online suggestions. Different algorithms and technologies are used for each form, depending on the task at hand. This study investigates the utilization of artificial intelligence in e-commerce recommender systems and explores current and future trends in the field through a systematic literature review and data analysis. The findings reveal that artificial intelligence, combined with other technologies like blockchain, virtual reality, and augmented reality, enhances the consumer experience in the e-commerce process.