Large Language Models (LLMs) in E-Commerce

Large language models (LLMs) have emerged as highly influential technologies in e-commerce, offering possibilities for complex applications in customer interaction, business efficiency, and decision-making. LLMs such as GPT-4, BERT and t5 have demonstrated high accuracy in natural language processing with transformer-based deep learning architecture and contribute to personalized recommendations, content creation and intelligent customer engagement. Existing literature has shown that LLM-based chatbots have the potential to solve more than 80% of common customer questions. Similarly, the recommendations made by LLMs have shown a significant contribution in terms of revenue growth for e-commerce businesses. Despite these potential applications, there are still major challenges in implementing LLMs in e-commerce, including privacy, cost and ethics issues. The purpose of this paper is to systematically study the application of LLMs in e-commerce, including its advantages, disadvantages and potential. With comparative case study approaches for Amazon's three e-commerce giants, Alibaba and Shopify, and by analyzing emerging trends in multifaceted AI and voice commerce, while considering the key implementation challenges, the research seeks to provide valuable insights to optimize the application of LLMs in e-commerce.