Darshan Desai
Applied Analytics Program, School of Professional Studies, Columbia University, New York, USA.

Ashish Desai
Enterprise Data Architecture & Enablement Strategy, Bristol Myers Squibb, Princeton, New Jersey, USA.

DOI https://doi.org/10.33889/IJMEMS.2025.10.3.036

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Abstract

Business Intelligence (BI) workflows benefit from the improved access to insights that Generative Artificial Intelligence (GenAI) can bring, allowing for swifter democratization of data access and improved decision-making across various domains such as finance, retail, life sciences, education technology (EdTech), etc. Although existing literature discusses theoretical models or particular case studies, it does not provide a practical framework to integrate GenAI into BI. This study fills the gap by devising a pragmatic framework employing the qualitative research method featuring semi-structured interviews with professionals in varied disciplines. The results show that GenAI can improve the effectiveness of the interaction between technical experts and business users. Successful adoption, however, hinges on clarity of the organizational goals, effectiveness of the data management, user training, and system integration. Organizations can apply the proposed framework to integrate GenAI into BI systems to focus on operational excellence and support for real-time, data-driven decisions. These insights serve to advance BI practices, and act as a precursor to the future research in the domain of AI-integrated BI workflows.

Keywords- Generative AI, Augmented analytics, Business intelligence, Data democratization, Business value.

Citation

Desai, D., & Desai, A. (2025). Integrating Generative AI in Business Intelligence: A Practical Framework for Enhancing Augmented Analytics. International Journal of Mathematical, Engineering and Management Sciences, 10(3), 704-728. https://doi.org/10.33889/IJMEMS.2025.10.3.036.