大模型驱动的智能客服在电子商务中的应用与挑战

Applications and Challenges of Large Language Model-Driven Intelligent Customer Service in E-Commerce

摘要: 随着电子商务不断发展，客户服务需求变得规模化且多样化，传统依靠规则和检索的智能客服在理解语义、服务深度上逐渐呈现出自身的局限性。近年来，人工智能技术在自然语言处理方面取得进展，给电子商务智能客服带来新的发展契机。由大模型驱动的智能客服能靠更强大的语义理解与生成能力，达成高效解答问题、个性化推荐以及多语言交流，既提升用户体验和服务效率，又为企业节省人力成本、优化运营流程创造可能性。但大模型用于电商客服还存在知识幻觉、数据安全、隐私保护以及昂贵算力成本等问题。本文通过对大模型智能客服的应用场景与优势进行梳理，剖析其在电子商务实践里的实际困境，给出未来改进的方向与办法，期望能为智能客服的研究与实践给予具有实际意义的参考。

Abstract: With the continuous development of e-commerce, customer service demands have become increasingly large-scale and diverse. Traditional rule-based and retrieval-based intelligent customer service systems are showing limitations in semantic understanding and service depth. In recent years, advances in artificial intelligence, particularly in natural language processing, have brought new opportunities for intelligent customer service in e-commerce. Large language model–driven customer service systems, with their powerful semantic understanding and generation capabilities, can provide efficient problem-solving, personalized recommendations, and multilingual interactions. These advantages not only enhance user experience and service efficiency but also enable enterprises to reduce labor costs and optimize operational processes. However, challenges remain in applying large models to e-commerce customer service, including hallucinated knowledge, data security, privacy protection, and the high cost of computational resources. This paper reviews the application scenarios and advantages of large-model-based intelligent customer service, analyzes the practical challenges in e-commerce contexts, and proposes directions and approaches for future improvement, with the aim of providing meaningful references for both research and practice in this field.