Enhancing Security in Enterprise Networks: Implementing Zero Trust and AI-Driven Threat Detection

In an era of increasing cyber threats and complex enterprise network environments, traditional perimeter-based security models have become inadequate. This study explores the integration of Zero Trust Architecture (ZTA) and AI-driven threat detection systems to enhance enterprise network security. By adopting the Zero Trust principle of "never trust, always verify," combined with advanced AI capabilities for real-time threat detection and response, organizations can achieve a robust and adaptive security posture. The study demonstrates that this integrated approach improves threat detection rates, reduces incident response times, and minimizes false positive and negative rates. Statistical analyses reveal strong correlations between AI capabilities and Zero Trust measures, highlighting their synergistic benefits. Despite challenges such as implementation complexity and cost, this unified framework offers a scalable and effective solution for mitigating modern cybersecurity risks. The findings provide actionable insights for organizations seeking to enhance their security resilience.