Governance in Microsoft 365 Copilot & Studio: Practical Policies, Guardrails, and Checklists for Secure, Responsible AI at Scale

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Bol Drawing from Microsoft’s latest governance models, enterprise case studies, and real-world best practices, it translates complex principles into clear, actionable steps to help organizations scale AI responsibly. This pocket guide is a concise, field-ready reference for IT leaders, administrators, and architects responsible for governing Microsoft 365 Copilot and Copilot Studio deployments. As AI evolves from simple assistants to autonomous digital colleagues, governance is no longer optional—it’s the backbone of secure, compliant, and value-driven adoption. Covering both platforms, this guide shows how to define effective policies, controls, and monitoring frameworks that protect organizational data while enabling innovation. Drawing from Microsoft’s latest governance models, enterprise case studies, and real-world best practices, it translates complex principles into clear, actionable steps to help organizations scale AI responsibly. What You Will Learn: Design and implement a governance framework for M365 Copilot and Copilot Studio Configure sensitivity labels, DLP policies, and lifecycle management to protect organizational data in AI workflows Apply environment strategy, role-based access control, and ALM to Copilot Studio agents Measure, monitor, and optimize AI agent performance, cost, and compliance Balance innovation with guardrails using models like Microsoft’s Zoned Governance

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Drawing from Microsoft’s latest governance models, enterprise case studies, and real-world best practices, it translates complex principles into clear, actionable steps to help organizations scale AI responsibly. This pocket guide is a concise, field-ready reference for IT leaders, administrators, and architects responsible for governing Microsoft 365 Copilot and Copilot Studio deployments. As AI evolves from simple assistants to autonomous digital colleagues, governance is no longer optional—it’s the backbone of secure, compliant, and value-driven adoption. Covering both platforms, this guide shows how to define effective policies, controls, and monitoring frameworks that protect organizational data while enabling innovation. Drawing from Microsoft’s latest governance models, enterprise case studies, and real-world best practices, it translates complex principles into clear, actionable steps to help organizations scale AI responsibly. What You Will Learn: Design and implement a governance framework for M365 Copilot and Copilot Studio Configure sensitivity labels, DLP policies, and lifecycle management to protect organizational data in AI workflows Apply environment strategy, role-based access control, and ALM to Copilot Studio agents Measure, monitor, and optimize AI agent performance, cost, and compliance Balance innovation with guardrails using models like Microsoft’s Zoned Governance

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Pagina's: 136, Editie: First, Paperback, Apress


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