Securing Copilot with Zero Trust Principles

As organizations rapidly adopt AI-powered assistants like Copilot, securing sensitive organizational data becomes a top priority. Implementing a Zero Trust framework ensures that your AI tools only access the data they are supposed to, keeping your intellectual property safe. This course teaches you how to design, configure, and maintain a secure environment for Copilot deployments using modern security methodologies. You will transition from understanding basic security concepts to enforcing strict access controls and monitoring AI interactions. What you'll learn: * Understand the foundational pillars of the Zero Trust security model and how they apply to generative AI. * Configure identity and access management policies to ensure least-privilege access for AI tools. * Implement data classification and sensitivity labels to protect confidential information from unauthorized retrieval. * Analyze data flow and permissions within your collaborative workspace to prevent accidental data exposure. * Monitor and audit AI interactions to detect anomalous behavior and potential security threats. * Apply modern data loss prevention strategies tailored for AI assistant environments. The course begins with foundational security definitions and key terminology before guiding you through practical strategies for permission management, data labeling, and continuous monitoring. You will read real-world scenarios and complete written exercises designed to test your understanding of secure AI deployment. This course is designed for IT administrators, security beginners, and business technology leads who want to secure their AI tools. No prior security experience is required. Start learning today to build a secure, AI-powered workplace with confidence.