Summary
Throughout this module, you learned how to administer and develop a governance strategy for Power Platform AI features. You explored how Zava's admin team faced challenges such as uncoordinated AI adoption across marketing and store operations, with no consistent governance around data residency. This module equipped you to address those challenges with a comprehensive AI governance framework.
You learned to establish responsible AI principles with content moderation levels and human oversight requirements mapped to governance zones. You configured data residency controls that keep regulated data within required boundaries while enabling AI features for less sensitive workloads. You governed which knowledge sources and AI capabilities are available to makers through environment settings and DLP policy integration. And you administered AI Builder models, prompts, and semantic search with appropriate credit allocation and feature controls.
This layer of AI-specific governance controls sits on top of your environment topology and data policies to complete the "Maintain oversight and prevent agent sprawl" journey. With environments, data policies, and AI governance in place, you have a foundation that enables responsible AI innovation while maintaining the oversight your organization requires.