Real-time personalization in retail: A blueprint for AI-driven digital transformation

The retail sector is experiencing a digital transformation driven by artificial intelligence (AI), with real-time personalization becoming a key strategy for enhancing customer experiences. This paper explores the concept of AI-driven real-time personalization in retail, focusing on its components, applications, and the ethical challenges associated with its implementation. We propose a comprehensive framework that includes data collection and integration, AI-driven analysis, personalized customer experiences, and ethics management. This framework aims to guide retailers in leveraging AI to provide tailored recommendations, dynamic pricing, and customized marketing strategies, while addressing issues such as data privacy and algorithmic bias. Despite its potential, AI-driven personalization faces several limitations, including technical challenges, consumer trust concerns, and ethical implications. We discuss these limitations and propose future research directions in the areas of privacy-preserving techniques, bias mitigation, and omni-channel personalization. This study provides valuable insights into the opportunities and challenges of AI-driven personalization in retail, offering a roadmap for future developments in this rapidly evolving field.