Generative BI: The Evolution of Business Intelligence Through Generative AI Integration

The rapid advancements in Generative Artificial Intelligence (AI) are ushering in a new era for traditional Business Intelligence (BI) systems. This paper explores the emerging field of Generative Business Intelligence (Generative BI), which represents the convergence of BI and cutting-edge Generative AI technologies. Traditionally, BI has focused on extracting insights from historical data through techniques like data mining, statistical analysis, and reporting. However, the integration of Generative AI is transforming this landscape, empowering organizations to generate novel, contextual, and personalized business insights at scale. Generative AI models, such as large language models and diffusion models, can analyze vast amounts of structured and unstructured data, identify patterns, and synthesize tailored recommendations and forecasts. This enables decision-makers to gain deeper, more nuanced understandings of their business, market trends, and customer behaviors. Furthermore, Generative BI systems can automate the generation of interactive visualizations, natural language summaries, and even hypothetical scenarios to support strategic planning and decision-making. This convergence of BI and Generative AI is poised to revolutionize how enterprises leverage data to drive innovation, optimize operations, and gain a competitive edge in their respective industries. The paper delves into the key technological advancements, use cases, and the potential impact of Generative BI on the future of enterprise intelligence systems. It also explores the challenges and considerations organizations must navigate as they embrace this transformative approach to business analytics.

Authors

Publication Details

Journal
International Journal of Multidisciplinary Research and Growth Evaluation
Published
2025-01-01
DOI
https://doi.org/10.54660/.ijmrge.2025.6.1.2148-2153
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative BI: The Evolution of Business Intelligence Through Generative AI Integration

Dinesh Thangaraju
International Journal of Multidisciplinary Research and Growth Evaluation
Big Data and Business Intelligence
article

Generative BI: The Evolution of Business Intelligence Through Generative AI Integration

Dinesh Thangaraju
article en

Abstract

The rapid advancements in Generative Artificial Intelligence (AI) are ushering in a new era for traditional Business Intelligence (BI) systems. This paper explores the emerging field of Generative Business Intelligence (Generative BI), which represents the convergence of BI and cutting-edge Generative AI technologies. Traditionally, BI has focused on extracting insights from historical data through techniques like data mining, statistical analysis, and reporting. However, the integration of Generative AI is transforming this landscape, empowering organizations to generate novel, contextual, and personalized business insights at scale. Generative AI models, such as large language models and diffusion models, can analyze vast amounts of structured and unstructured data, identify patterns, and synthesize tailored recommendations and forecasts. This enables decision-makers to gain deeper, more nuanced understandings of their business, market trends, and customer behaviors. Furthermore, Generative BI systems can automate the generation of interactive visualizations, natural language summaries, and even hypothetical scenarios to support strategic planning and decision-making. This convergence of BI and Generative AI is poised to revolutionize how enterprises leverage data to drive innovation, optimize operations, and gain a competitive edge in their respective industries. The paper delves into the key technological advancements, use cases, and the potential impact of Generative BI on the future of enterprise intelligence systems. It also explores the challenges and considerations organizations must navigate as they embrace this transformative approach to business analytics.

International Journal of Multidisciplinary Research and Growth EvaluationVol. 6(1)
Openalex Percentile: Top 91%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.