Adaptive Zero Trust Security: Integrating Artificial Intelligence for Dynamic Cloud Security

Abstract

Zero Trust Architecture(ZTA) has become a widely adopted security approach for modern cloud and hybrid systems, built on the principle that no user, device, or service should be trusted by default. While this model has improved security compared with traditional perimeter-based methods, it still faces multiple challenges. They frequently depend on static access policies, tightly coupled identity and access management systems, and complex integration across heterogeneous platforms. As organizations expand into multi-cloud environments, edge computing, and highly distributed workloads, these limitations make it difficult for ZTA to keep pace with real-world complexity. This article presents a conceptual view on the evolution of Zero Trust beyond static policy enforcement. The article highlights why current architectures struggle to adapt changes in user behavior, workload context, and threat conditions. Artificial Intelligence can play a critical role in strengthening Zero Trust by helping systems interpret behavioral signals, understand patterns, and adjust policies more dynamically. Instead of treating Zero Trust as a fixed architecture, this perspective frames it as a continuously adapting trust model supported by AI-driven insights. This article outlines a path toward more resilient, context-aware, and scalable security in cloud environments.