Transforming Grocery Retail and E-Commerce Through Large Language Models

Abstract

In light of the rise of multimodal AI and big language models, the landscape for grocery, physical retailers, and e-commerce is rapidly changing. By leveraging complex models, digital commerce, omnichannel, and supply chain operations can benefit from natural language understanding, the ability to process information from multiple modalities, and the ability to make autonomous decisions. Recent work shows the effectiveness of conversational LLM experiences for product discovery, website navigation, and customer experiences through live meal preparation, optimized shopping baskets, personalized promotions, and smart product substitutions in online buying experiences. In addition, LLM applications have proven effective in automating e-commerce workflows, such as summarizing customer feedback, improving search and recommendation systems, and automating product classification. These are key functions for the online merchandising at scale. LLM-based solutions help improve the resiliency of the supply chain via dynamic inventory management, demand forecasting, and fulfillment routing. Omnichannel, computer vision, last-mile logistics, and robotics deliver additional capabilities to improve product identification and picking accuracy for online grocery fulfillment. This essay discusses how grocery retail and digital businesses are evolving due to the growing prominence of LLM technologies, with the support of recent academic and business literature. It resolves planned, operational, and ethical issues for future AI-enabled environments.