Artificial Intelligence in Business Intelligence Systems: Leveraging Machine Learning for Predictive Analytics in Decision-Making

Authors

  • Shiva Data Analyst, LatentView, Chennai, India Author

DOI:

https://doi.org/10.63282/3050-9262.IJAIDSML-V1I4P102

Keywords:

Artificial Intelligence, Business Intelligence, Machine Learning, Predictive Analytics, Decision-Making, Data Processing, Data Visualization, Model Training, Feature Engineering, Automated Insights

Abstract

Artificial Intelligence (AI) has revolutionized various sectors, and its integration into Business Intelligence (BI) systems is no exception. This paper explores the role of AI, particularly machine learning (ML), in enhancing predictive analytics within BI systems. The focus is on how ML algorithms can be leveraged to improve decision-making processes in organizations. We discuss the theoretical foundations, practical applications, and the challenges and future directions of AI in BI. The paper also includes case studies, algorithmic examples, and a comprehensive review of the literature to provide a holistic understanding of the topic

References

[1] Domo. (n.d.). AI predictive analytics: Benefits, examples & more. https://www.domo.com/glossary/ai-predictive-analytics

[2] Kerzel, U. (2020). Enterprise AI canvas: Integrating artificial intelligence into business. arXiv preprint arXiv:2009.11190. https://arxiv.org/abs/2009.11190

[3] Siegel, E. (2013). Predictive analytics: The power to predict who will click, buy, lie, or die. Wiley.

[4] The Wall Street Journal. (2025, February 14). How WSJ readers use AI at work. https://www.wsj.com/tech/ai/ai-at-work-readers-59e23819

Published

2020-11-25

Issue

Section

Articles

How to Cite

1.
Shiva. Artificial Intelligence in Business Intelligence Systems: Leveraging Machine Learning for Predictive Analytics in Decision-Making. IJAIDSML [Internet]. 2020 Nov. 25 [cited 2025 Oct. 21];1(4):7-15. Available from: https://ijaidsml.org/index.php/ijaidsml/article/view/19