Modak, Rahul (2025) Generative AI for automated business report generation and analysis. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 894-901. ISSN 2582-8266
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Abstract
This research paper explores the application of generative artificial intelligence (AI) in automating business report generation and analysis. The study investigates the potential of various AI models, including natural language processing (NLP) and machine learning (ML) techniques, to streamline the process of creating comprehensive business reports. We examine the effectiveness of these AI-driven approaches in extracting relevant information from diverse data sources, generating insightful analyses, and presenting findings in a coherent and user-friendly manner. The research also addresses the challenges and limitations associated with AI-powered report generation, as well as the potential impact on business decision-making processes. Our findings suggest that generative AI has the potential to significantly enhance the efficiency and quality of business reporting, leading to more data-driven and timely decision-making in organizations.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.2.0610 |
Uncontrolled Keywords: | Generative AI; Business Reports; Automated Analysis; Natural Language Processing; Machine Learning |
Depositing User: | Editor Engineering Section |
Date Deposited: | 04 Aug 2025 16:24 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/3620 |