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Engineering and Technology OPEN ACCESS

AI-Powered Business Intelligence in IT: Transforming Data into Strategic Solutions for Enhanced Decision-Making

Mohammad Majharul Islam
Department of Business Studies, Lincoln University, California, USA
MD Nadil khan
Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA
Kirtibhai Desai
Department of Computer Science, Campbellsville University, KY 42718, USA
MD Mahbub Rabbani
Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA
Saif Ahmad
Department of Business Analytics, Wilmington University, USA
Esrat Zahan Snigdha
Department of Information Technology in Data Analysis, Washington University of Science and Technology (wust), Vienna, VA 22182, USA
DOI Crossref DOI 10.37547/tajet/Volume07Issue02-09
tajet 2025
VOL. 7 / NO. 02 FEBRUARY
FULL TEXT PP. 59-73
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VOLUME 7
ISSUE 02
YEAR 2025
PAGES 59-73
RESEARCH OVERVIEW

Abstract

Business intelligence receives its revolution from artificial intelligence technologies in IT sector information systems which turn raw big data into strategic action insights for organizational leaders. This research evaluates AI-powered technologies that assist BI frameworks and their ability to improve data analysis and predictive forecasting as well as automate processes. The study performs a full examination of existing documentations alongside industrial implementations and case study evaluations to demonstrate AI-based BI applications for operational efficiency along with expenditure reductions and fact-based decision-making improvements. The analysis methods of this paper use validated secondary data taken from peer-reviewed journals industry reports and case studies which demonstrate principal trends and effects. AI-based BI solutions strengthen decision support because they provide immediate contextual information. The research demonstrates major uses of AI technology which includes machine learning patterns through algorithms as well as natural language processing sentiments and AI dashboard visualizations. Despite these accomplishments the study presents obstacles which involve data security issues and system integration difficulties together with a lack of qualified personnel for AI control operations. This paper introduces innovative BI strategies along with their impact on IT decision-making processes as the main novelty in addition to filling existing research gaps. The research presents implementable guidelines which assist organizations as well as policymakers and academics to leverage AI technology for growing sustainably together with competitive advantage.

RESEARCH TOPICS

Keywords

Business Intelligence Data Analytics Decision-Making

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