Title: Artificial Intelligence: Theory, Tools and Real-World Applications
Editors: Prof. Dr. A. Shameem and Dr. J. Rengamani
ISBN: 978-81-69857-67-3
Chapter: 18
DOI: https://doi.org/10.59646/819/16
Author: Dr. S. Sathyapriya
Abstract
Artificial Intelligence (AI) has transformed Business Intelligence (BI) by enabling organizations to analyze large and complex datasets with greater speed, accuracy, and efficiency. Intelligent data analytics combines AI techniques such as machine learning, natural language processing, predictive analytics, and automated data mining to identify patterns, trends, and valuable insights from business data. This approach supports organizations in improving decision-making, forecasting market changes, optimizing operations, understanding customer behavior, and managing business risks. AI-powered BI systems can process structured and unstructured data from multiple sources and provide real-time insights through intelligent dashboards and automated reporting. The integration of AI also reduces manual analytical tasks and enables organizations to move from traditional descriptive reporting toward predictive and prescriptive decision-making. Despite these benefits, challenges related to data quality, privacy, security, algorithmic bias, transparency, and technical expertise must be addressed. The study highlights the practical importance of intelligent data analytics in strengthening business performance and developing data-driven strategies. Effective implementation of AI-enabled BI can provide organizations with a competitive advantage and support sustainable business growth.
Keywords: Artificial Intelligence, Intelligent Data Analytics, Business Intelligence, Machine Learning, Predictive Analytics, Data-Driven Decision Making, Business Analytics, Data Mining, Natural Language Processing, Strategic Decision-Making.