Building AI-Powered Features Around Power BI Embedded Analytics

Hi codeautomation​ ,

Thank you for reaching out to fabric community.

Use Power BI/Fabric as the governed semantic layer with an AI service such as Azure OpenAI providing the reasoning layer. The AI can interpret the user's question, create the appropriate DAX query and have the backend execute it against the Power BI semantic model through supported Power BI APIs.

With Power BI Embedded, keep the AI and Power BI API integration in the application backend instead of exposing credentials in the browser. The backend can authenticate the user, identify the relevant semantic model and permissions, provide the AI service with the necessary metadata, validate the generated query, run it and return the results as a natural-language insight.

For security, do not grant the AI unrestricted direct access to production databases. Apply Microsoft Entra ID, Power BI permissions and RLS/OLS where applicable to ensure the AI can access only the data the user is authorized to view. In Fabric-native conversational scenarios, Fabric Data Agent is another option for querying Power BI semantic models while maintaining the platform's security model.

Thanks!!