Webinar: AI Inside Your Power BI Semantic Model

Most AI tools work next to your BI stack, not inside it. They don’t know your measures, don’t understand your definitions, and have no idea how your model is structured. The output looks useful, until it doesn’t. This might sound familiar:

• AI writes DAX, but you don’t trust it because it has no idea what your model actually means.
• Your semantic model is well-built, but explaining, maintaining and expanding it costs more time than it should.
• Business wants direct answers, not a new report. But getting there still requires manual translation every single time.
• You see AI demos that look impressive, but you can’t tell what is enterprise-ready and what isn’t.
• You want to explore this, but not without knowing where the security and compliance boundaries are.

AI tools are built to be generic. They work with whatever you paste into a prompt, with no knowledge of your measures, your naming conventions or the business rules baked into your model. That is not a prompt problem. It is an architecture problem. As long as AI sits outside your BI stack, it will keep producing output that looks plausible but drifts from what your model actually says.

What is emerging now is fundamentally different. Large language models like Claude can connect directly to Power BI semantic models via MCP servers, by reading the model itself rather than copying or exporting data:

• Schemas, measures, metadata and definitions are read directly from your model.
• AI reasons within the same logic as your BI team, based on your naming conventions and business rules.
• Nothing leaves your environment. The model stays the source of truth.
• From standalone prompts to an architecture layer
• Business questions answered in natural language, based on live model context.

No hype, just mature choices

AI is not always trustworthy, and we agree with you on that. Not everything needs to be connected, and not everything should be. Governance, security and manageability stay central. This is an architecture question, not an AI experiment. In 25 minutes you walk away with a technically grounded, realistic view of what this means for your Power BI setup.

What you can expect from this session

• What MCP is and how it lets AI read and reason within your semantic model.
• Where this delivers real value today: model authoring, DAX generation, documentation and natural language Q&A.
• How security, compliance and governance work when AI connects to your BI environment, and where the boundaries are.
• What is not ready yet and why knowing that matters before you start.

Who is this for?

For BI developers, analytics engineers and advanced Power BI users who feel responsible for the reliability of their environment. You are curious about AI, but skeptical of hype. Semantic models in your organization are growing in complexity, business questions keep coming faster, and you need to stay in control of what you build.

Practical details

• Date: 7 May 2026
• Time: 10:00 – 10:25
• Location: Online
• Language: Dutch
• Cost: Free