4 Key Steps to Optimize Power BI Copilot Accuracy with Your Data Model

Great article One point I'd add is that Power BI Copilot is only as effective as the semantic model behind it. Beyond clean data, organizations should focus on descriptive table and measure names, well-defined relationships, business-friendly metadata, and consistent naming conventions. These improvements help Copilot better understand user intent and generate more reliable insights. Microsoft has also introduced AI-focused data preparation features, such as verified answers and AI instructions, to further improve response quality and reduce ambiguity. Investing time in model governance and ongoing data quality checks can significantly enhance Copilot's accuracy as business data evolves. At Damco, we've also observed that a well-structured semantic model consistently delivers more meaningful and trustworthy AI-driven analytics than relying on clean data alone.