This paper delves into the application of prompt engineering within the context of Business Process Management (BPM), focusing on the creation of a meticulously designed meta-prompt to facilitate the generation of process reference models via ChatGPT-4, a leading-edge Large Language Model (LLM). By exploring the methodology and efficacy of our approach, we demonstrate the significant potential of utilizing AI to streamline and optimize BPM. Our research highlights the critical role of precise prompt engineering in achieving accurate, relevant, and cost-effective process models, paving the way for broader application and integration with BPM tools for enhanced functionality. This study not only advances the understanding of AI’s capacity to revolutionize BPM but also sets the stage for future explorations into the adaptability and scalability of AI-driven process modeling across various industries.

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

Meta-prompt Engineering in ChatGPT-4 for AI-Generated BPM Reference Models

  • Christoph Piller

摘要

This paper delves into the application of prompt engineering within the context of Business Process Management (BPM), focusing on the creation of a meticulously designed meta-prompt to facilitate the generation of process reference models via ChatGPT-4, a leading-edge Large Language Model (LLM). By exploring the methodology and efficacy of our approach, we demonstrate the significant potential of utilizing AI to streamline and optimize BPM. Our research highlights the critical role of precise prompt engineering in achieving accurate, relevant, and cost-effective process models, paving the way for broader application and integration with BPM tools for enhanced functionality. This study not only advances the understanding of AI’s capacity to revolutionize BPM but also sets the stage for future explorations into the adaptability and scalability of AI-driven process modeling across various industries.