用大模型聊天机器人代替专家访谈，高效获取企业数字化转型需求
Digital Transformation Chatbot (DTchatbot): Integrating Large Language Model-based Chatbot in Acquiring Digital Transformation Needs
- 将工作流指令与大模型推理结合，让聊天机器人像专家一样提问
- 初步测试显示能按预设流程运行，交互效果良好但有改进空间
- 适合需要快速收集需求的企业、咨询机构或数字化转型项目
许多组织通过自动化和数字工具推动数字化转型，以提升运营效率、减少人工负担并优化流程。实现这一目标的前提是全面理解其独特需求。然而，传统方法如专家访谈存在排期冲突、资源受限、结果不一致等问题。为此，本文探索使用大语言模型（LLM）驱动的聊天机器人来采集组织的数字化转型需求。具体而言，该聊天机器人融合基于工作流的指令与大模型的规划与推理能力，可作为虚拟专家进行访谈。本文详细描述了聊天机器人的功能设计与实现方式。初步评估表明，聊天机器人按预期运行，能有效遵循预设工作流，并支持用户交互，但仍存在优化空间。文章最后讨论了使用聊天机器人获取用户信息的潜在价值与局限性。
原文摘要 · Abstract (English)
Many organisations pursue digital transformation to enhance operational efficiency, reduce manual efforts, and optimise processes by automation and digital tools. To achieve this, a comprehensive understanding of their unique needs is required. However, traditional methods, such as expert interviews, while effective, face several challenges, including scheduling conflicts, resource constraints, inconsistency, etc. To tackle these issues, we investigate the use of a Large Language Model (LLM)-powered chatbot to acquire organisations' digital transformation needs. Specifically, the chatbot integrates workflow-based instruction with LLM's planning and reasoning capabilities, enabling it to function as a virtual expert and conduct interviews. We detail the chatbot's features and its implementation. Our preliminary evaluation indicates that the chatbot performs as designed, effectively following predefined workflows and supporting user interactions with areas for improvement. We conclude by discussing the implications of employing chatbots to elicit user information, emphasizing their potential and limitations.
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