The rise of Agentic AI is transforming enterprise workflows, yet significant security gaps remain. Many current architectures use a “God Key” model, where shared, long-lived credentials obscure user identity and authorization. This model is not scalable and poses risks, including the loss of user attribution and over-broad permissions in tool interactions. Transitioning to a delegated identity model with AI-aware enforcement mechanisms is essential for safe operations. Traditional Zero Trust Network Access (ZTNA) strategies need to evolve to incorporate identity delegation and protocol awareness. Implementing an MCP-aware ZTNA can centralize access control, preserve user attribution, and enforce least-privilege access for AI-driven workflows. This adaptation is crucial for enterprises aiming to leverage autonomous digital workers while maintaining security. Organizations must configure their frameworks to ensure user identities are propagated effectively and minimize risk, enabling a robust security posture suited for the era of Agentic AI.
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