Forum Discussion
How are teams automating Power BI development workflows using AI agents?
I am exploring how AI agents can help automate repetitive tasks in Power BI development and data workflows.
Some possible use cases:
- Automatically generating reports from business requirements
- Triggering data preparation workflows through APIs
- Validating datasets before publishing dashboards
- Detecting anomalies and suggesting improvements
- Automating documentation for datasets and reports
I am interested in learning how developers are currently combining Microsoft Fabric, Power BI APIs, notebooks, and AI agents.
What architecture patterns or best practices are you using for AI-driven BI automation?
1 Reply
v-abhinavmuCommunity Support
Hi codeautomation,
Thanks for reaching out to the Microsoft Fabric Community forum.
A practical approach is to use an AI/data agent for natural-language interaction and query generation, while using Fabric and Power BI APIs for controlled execution and deployment.
User requirement -> AI/data agent -> semantic model -> DAX/query generation -> validation -> deployment
• Prepare the semantic model for AI: Use Prep for AI to configure relevant tables, columns, and measures, along with verified answers and AI instructions.
• Validate and iterate: Test the agent using benchmark questions and expected answers, then refine the semantic model and agent instructions based on the results.
• Automate Fabric workflows: Fabric notebook APIs support notebook management, on-demand execution, monitoring, cancellation, and returning exitValue for orchestration.
• Automate Power BI operations: Power BI REST APIs can manage Power BI resources and trigger semantic model refreshes.
• Use CI/CD: Fabric supports Git integration, Fabric Items APIs, and deployment pipelines for automating development and deployment workflows, including testing before production.
This provides a documented way to combine AI/data-agent capabilities with Fabric and Power BI APIs, validation, and CI/CD rather than relying on the AI agent alone.
For more details, please refer to the below Official Microsoft documentation:
• Semantic model best practices for data agent - Microsoft Fabric | Microsoft Learn
• Manage and execute Fabric notebooks with public APIs - Microsoft Fabric | Microsoft Learn
• Power BI REST APIs for embedded analytics and automation - Power BI REST API | Microsoft Learn
• Datasets - Refresh Dataset - REST API (Power BI Power BI REST APIs) | Microsoft Learn
• CI/CD workflow options in Fabric - Microsoft Fabric | Microsoft Learn
• Adopting an iterative process for improving your data agent - Microsoft Fabric | Microsoft LearnI hope this helps. Please feel free to reach out if you have any further questions.
Thank you.