The rapid evolution of generative artificial intelligence (AI) using large language models, such as ChatGPT, has led to its application in various business domains. However, business tasks in which we can use generative AI applications effectively are still unclear. Therefore, in this study, we consider the applicability of generative AI applications and propose a method for identifying business goals for generative AI applications based on knowledge distribution models and the GQM (Goal Question Metrics)-strategies approach. Through an example analysis in an insurance industry, we confirm the effectiveness of the proposed method.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Method for Identifying Business Goals for Generative Artificial Intelligence Applications Based on Knowledge Distribution Models and GQM+Strategies

  • Hironori Takeuchi,
  • Ralf-Christian Härting,
  • Shuichiro Yamamoto

摘要

The rapid evolution of generative artificial intelligence (AI) using large language models, such as ChatGPT, has led to its application in various business domains. However, business tasks in which we can use generative AI applications effectively are still unclear. Therefore, in this study, we consider the applicability of generative AI applications and propose a method for identifying business goals for generative AI applications based on knowledge distribution models and the GQM (Goal Question Metrics)-strategies approach. Through an example analysis in an insurance industry, we confirm the effectiveness of the proposed method.