AI-driven business analytics and decision making
1 Robert H Smith School of Business, University of Maryland, USA.
2 Department of Technology, Illinois State University, USA.
3 School of Management, University of Bradford, United Kingdom.
4 College of Innovation, John Wesley School of Leadership, Carolina University, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 616–633
Publication history:
Received on 23 August 2024; revised on 05 October 2024; accepted on 07 October 2024
Abstract:
The rapid advancement of Artificial Intelligence (AI) and Machine Language (ML) has revolutionized business analytics, transforming the way organizations make decisions. This paper explores the integration of AI-driven technologies into business analytics to enhance decision-making across various industries. By leveraging predictive and prescriptive analytics, AI enables organizations to not only analyse historical data but also forecast future trends, allowing for more informed, proactive strategies. Machine learning plays a pivotal role in automating data-driven decisions, offering real-time insights that help businesses respond quickly to changing market dynamics. This automation significantly reduces manual intervention, increases efficiency, and enhances the accuracy of predictions. The paper further discusses the integration of AI with Business Intelligence (BI) tools to deliver deeper insights from complex datasets in real time. These insights empower companies to optimize enterprise resources, improve supply chain management, and drive operational excellence. Case studies from AI-driven analytics within Systems, Applications, and Products in Data Processing (SAP) environments highlight the practical applications of AI in real-world business contexts, demonstrating its impact on decision-making and overall performance. The paper concludes with best practices for implementing AI in business analytics, focusing on data quality, system integration, and workforce readiness to embrace AI-enabled decision-making frameworks. The findings underscore the potential of AI as a game-changer in modern business landscapes, fostering smarter, faster, and more effective decision-making processes.
Keywords:
AI-driven analytics; Predictive analytics; Business intelligence; Machine learning; SAP integration; Decision-making optimization
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0