An Intelligent Enterprise Cloud Framework Integrating Agentic AI with Predictive Cyber Defense and Zero-Trust Enforcement

Abstract

The rapid adoption of enterprise cloud computing has significantly enhanced organizational agility, scalability, and digital transformation while simultaneously increasing exposure to sophisticated cyber threats. Conventional security mechanisms, which primarily rely on reactive detection and perimeter-based protection, are insufficient to defend against advanced persistent threats, insider attacks, and continuously evolving malware. This research proposes an Intelligent Enterprise Cloud Framework that integrates Agentic Artificial Intelligence (AI), predictive cyber defense, and Zero-Trust enforcement to establish a proactive, adaptive, and resilient cloud security architecture. The framework employs autonomous AI agents capable of continuous monitoring, threat analysis, risk assessment, policy optimization, and automated incident response using machine learning and behavioral analytics. Predictive cyber defense leverages real-time data analysis, anomaly detection, and threat intelligence to identify potential attacks before they compromise cloud resources. Simultaneously, the Zero-Trust model enforces continuous identity verification, least-privilege access control, and micro-segmentation to minimize unauthorized access and lateral movement within enterprise environments. The proposed architecture enhances decision-making, reduces incident response time, improves resource utilization, and strengthens regulatory compliance while maintaining operational efficiency. By combining intelligent automation with predictive analytics and dynamic access control, the framework provides a comprehensive cybersecurity solution capable of addressing the evolving security challenges of modern enterprise cloud infrastructures and supporting secure, scalable, and resilient digital transformation