AI-Driven Cybersecurity Intelligence Dashboards for Threat Prevention and Forensics in Regulated Business Sectors

Abstract

This review explores the transformative role of AI-driven cybersecurity intelligence dashboards in enhancing threat prevention and forensic capabilities across highly regulated business sectors such as finance, healthcare, and critical infrastructure. The increasing sophistication of cyber threats necessitates real-time threat intelligence, anomaly detection, and incident response systems that integrate artificial intelligence, machine learning, and advanced analytics. These dashboards consolidate heterogeneous data sources, enabling dynamic visualization, predictive risk scoring, and automated alerting mechanisms while ensuring compliance with regulatory standards such as GDPR, HIPAA, and SOX. The study evaluates core architectural frameworks, data integration pipelines, and visualization models that support proactive security posture management. Additionally, it investigates the application of explainable AI for forensic analysis, root cause investigation, and compliance audits. By surveying current technological innovations and deployment case studies, the paper identifies key trends, limitations, and future directions in developing intelligent cybersecurity dashboards for mission-critical operations.