The pandemic transformed consumer behaviour, emphasising safety and contactless shopping. To remain relevant, Brick and Mortar (B&M) retailers must innovate by integrating physical and digital experiences. This paper proposes the use of artificial intelligence (AI) to transform B&M retailers, enhancing their efficiency and appeal to modern consumers. The goal is to create a unique walk-in shopping experience that combines physical and digital elements. The study suggests several AI-based implementations. A machine learning-(ML)based K-means unsupervised learning algorithm to analyse customer data, including location and purchase patterns. The K-Nearest Neighbours (KNN) clustering technique guides prospects to nearby stores. An AI-based Voice Assistant (AIVA) at B&M stores to interact with customers, provide product information, and assist sales personnel in product demonstrations. A Satisfaction Assessment System (SAS) using AI to detect customer emotions through facial images upon leaving the store. Digital marketing communication (DMarCom) strategies based on SAS feedback to inform customers about products and services and address customer satisfaction levels. Implementing AI-based K-means clustering will help identify target customer segments. DMarCom efforts will create customer awareness through various digital channels. AIVA will enhance the purchasing experience by explaining product features, while SAS will assess customer satisfaction post-purchase. The data from SAS will be used to improve marketing strategies and customer interactions. By leveraging AI technologies such as clustering algorithms, voice assistants, emotion detection systems, and digital marketing communication, B&M retailers can enhance their efficiency, attract more customers, and ensure long-lasting engagement in a competitive market.