AI-Driven Threat Detection in Business Intelligence Systems
Maen Marwan Alzubi, Mohammad Almseidin, Mouhammd Sharari Alkasassbeh, Murad Bashabsheh, Jamil Al‐Sawwa, Ashraf S. Mashaleh · Advances in computational intelligence and robotics book series · 2025
Business intelligence systems operate in environments increasingly exposed to complex and evolving security threats. Traditional detection mechanisms lack the adaptability required for identifying anomalies in real time across diverse and high-volume data flows. This chapter investigates how artificial intelligence supports threat detection in BI systems through predictive analytics, machine learning models, and automated response mechanisms. It analyzes integration strategies involving data pipelines, cloud platforms, and enterprise reporting tools, illustrating how AI components embed across BI workflows. Case studies demonstrate improved detection accuracy, reduced response times, and enhanced decision support. Key challenges—such as data quality, model interpretability, and integration complexity—are examined alongside emerging innovations, including autonomous threat hunting and adaptive learning. The chapter contributes a framework for embedding AI into BI systems as a foundation for secure and responsive analytics environments.