TITLE:
Generative AI-Driven Business Value Insights in Industry Report Development: A Case Study of AI Education Sector Reports
AUTHORS:
Junsong Chen
KEYWORDS:
Generative Artificial Intelligence, Industry Report, AI Education, PESTMI Framework, Prompt Engineering, Business Model Analysis, Social Structure, User Behavior
JOURNAL NAME:
Modern Economy,
Vol.16 No.11,
November
13,
2025
ABSTRACT: In recent years, the application of Generative Artificial Intelligence (GAI) technology has rapidly expanded in the fields of knowledge production, text generation, and information analysis. Particularly in industry research and business consulting scenarios, GAI is increasingly regarded as an important tool for enhancing information integration efficiency and insight quality. This paper takes the AI education industry as an example to explore the application logic, methodological pathways, and theoretical significance of GAI in industry report R & D. By introducing an extended PESTMI (Political, Economic, Social, Technological, Market, Industry) analysis framework, combined with Prompt Engineering and multi-tool collaboration strategies, this paper constructs a human-machine collaborative report generation model and analyzes its advantages and limitations in structured writing, data analysis, and knowledge integration. Research indicates that GAI can effectively enhance the speed and topic coverage of initial draft generation for industry reports; however, it still requires human intervention and knowledge graph assistance in areas such as fact-checking, data citation, and deep insight generation. Theoretically, this paper further discusses how GAI reshapes the knowledge production mechanism and proposes a future knowledge governance path of “algorithm-human co-creation” for industry report R & D.