Citation:

Nagender Yamsani, 2026. "Designing Trustworthy Enterprise AI Systems through a Zero Trust Intelligence Fabric with a Unified Approach to Identity Centric Governance, Adaptive Policy Automation, and End-to End Data Security ", ESP Journal of Engineering & Technology Advancements  6(2): 116-128.

Abstract:

Rapid adoption of enterprise artificial intelligence systems has introduced significant challenges in ensuring secure, governable, and trustworthy operations across distributed environments. This study addresses the problem of fragmented security models and insufficient governance mechanisms by proposing a Zero Trust Intelligence Fabric that embeds identity centric governance, adaptive policy automation, and comprehensive data protection into AI ecosystems. Research aims to establish a unified framework that aligns security, compliance, and operational efficiency while supporting scalable enterprise deployments. Methodology follows a mixed approach combining conceptual architecture design, comparative analysis of existing governance models, and scenario based validation within enterprise contexts.

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Keywords:

Zero Trust Architecture, Enterprise Artificial Intelligence, Identity Centric Governance, Policy Automation, Data Security, Distributed AI Systems, Security Orchestration, Compliance and Regulatory Frameworks, Identity and Access Management, Adaptive Security Models, AI Lifecycle Management, Threat Detection and Prevention, Privacy Preserving AI, Intelligent Policy Enforcement, Resilient Enterprise Systems.