This article examines the convergence of advanced artificial intelligence methodologies and cloud-native environments in revolutionizing e-commerce personalization. The article presents a comprehensive framework for implementing dynamic, real-time personalization systems that leverage transformer-based models, reinforcement learning, and adaptive neural networks to process extensive customer interaction datasets instantaneously. The article addresses critical implementation challenges through serverless computing architectures, containerization strategies, and elastic resource provisioning while emphasizing the importance of explainable AI for maintaining transparency and customer trust. The article demonstrates that cloud-native AI deployments significantly enhance the capacity to deliver highly personalized customer experiences at scale, enabling e-commerce platforms to adapt continuously to individual customer behaviors and preferences. The proposed approaches not only improve computational efficiency and reduce latency but also provide sustainable solutions for ethical compliance in an increasingly regulated digital marketplace, establishing a foundation for the next generation of intelligent e-commerce systems.
Kodali Prakash (Wed,) studied this question.