Article contents
AI in Retail: A Technical Review of Customer Experience Enhancement
Abstract
The retail industry undergoes unprecedented transformation through artificial intelligence technologies that fundamentally reshape customer interactions and operational efficiency paradigms. This technical review examines contemporary implementations of AI systems across retail environments, focusing on customer experience enhancement through intelligent automation and personalization capabilities. Modern retail organizations increasingly recognize artificial intelligence as essential infrastructure rather than experimental technology, driving widespread adoption across diverse retail segments from e-commerce platforms to traditional brick-and-mortar establishments. The integration encompasses comprehensive technological ecosystems, including machine learning algorithms, computer vision systems, natural language processing capabilities, and predictive analytics frameworks that operate synergistically to create adaptive retail environments. AI-driven personalization technologies utilize sophisticated recommendation engines employing deep learning models, dynamic pricing algorithms leveraging reinforcement learning principles, and automated marketing systems generating personalized content at scale. Virtual and augmented reality integration introduces immersive shopping experiences through AR-powered virtual try-on systems and advanced 3D product visualization platforms. Intelligent customer service implementations include transformer-based chatbots, smart store technologies utilizing IoT sensors and computer vision, and automated checkout systems combining sensor fusion with machine learning algorithms. Advanced inventory management leverages predictive analytics for demand forecasting, supply chain optimization through operations algorithms, and emerging voice commerce capabilities enabling hands-free shopping experiences. These technological implementations demonstrate the maturation of AI from experimental applications to core retail infrastructure components.
Article information
Journal
Journal of Computer Science and Technology Studies
Volume (Issue)
7 (8)
Pages
806-913
Published
Copyright
Open access

This work is licensed under a Creative Commons Attribution 4.0 International License.