Synergizing Generative AI with Enterprise Business Intelligence for Prescriptive Analytics

Authors

  • Manoj Gudala Global Lead IT Business Analyst, Commercial Advanced Analytics Kellanova Plano, Texas, USA Author

DOI:

https://doi.org/10.47363/JAICC/ICMLAIDS2026/2026(5)10

Keywords:

Synergizing , Generative AI

Abstract

Background
The paradigm of Business Intelligence (BI) is shifting from descriptive analytics—reporting on what happened—to prescriptive analytics, which recommends how to respond. This transformation is driven by the 
convergence of Generative AI and structured enterprise data.


This presentation examines the practical integration of Large Language Models (LLMs) within global BI platforms to accelerate commercial decision-making and democratize data insights. Based on extensive 
implementations at Fortune 500 entities, the talk introduces an Adaptive BI Framework that reduces requirements ambiguity by 40% and accelerates “insight-to-action” cycles.

The session explores the technical architecture required to ground Generative AI responses in verified enterprise metadata, mitigating hallucination risks while enabling natural language querying of complex supply chain and sales datasets.

Author Biography

  • Manoj Gudala, Global Lead IT Business Analyst, Commercial Advanced Analytics Kellanova Plano, Texas, USA

    Manoj Gudala, Global Lead IT Business Analyst, Commercial Advanced Analytics Kellanova Plano, Texas, USA

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Published

2026-03-21

How to Cite

Synergizing Generative AI with Enterprise Business Intelligence for Prescriptive Analytics. (2026). Journal of Artificial Intelligence & Cloud Computing, 5(2), 1-1. https://doi.org/10.47363/JAICC/ICMLAIDS2026/2026(5)10

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