AI Driven Transformation of Traditional Data Analytics and Business Intelligence in Computer Science

Abstract

The rapid advancement of Artificial Intelligence (AI) is transforming data analytics and Business Intelligence (BI) across multiple domains of computer science. Traditional analytics and BI tools have long been instrumental for processing structured data and generating reports; however, they often struggle with large-scale, unstructured, or highly complex datasets. This study examines how integrating AI technologies such as machine learning, natural language processing, and deep learning enhances the analytical capabilities, adaptability, and decision-making potential of traditional BI systems. Through comparative analysis and real-world case studies, the research explores technical strategies for embedding AI within existing analytics frameworks and evaluates their effectiveness in improving automation, insight generation, and responsiveness. The integration of AI supports the development of intelligent, adaptive systems capable of detecting anomalies, uncovering hidden patterns, and enabling predictive and prescriptive analytics. The findings offer practical methodologies and design principles to guide organizations and researchers in creating next-generation intelligent data systems aligned with the evolving demands of computer science.

Keywords: Artificial Intelligence, Data Analytics, Business Intelligence, Machine Learning