Data Governance Enabled AI
Trusted AI reporting with Steward-in-the-Loop from the Data Cookbook
AI builds reports in seconds. Can you trust them?
Many AI reporting tools now offer the ability to turn plain-language questions into finished reports right away. But the AI doesn’t know how your organization defines “active employee” or how your team agreed to calculate “customer retention rate.” Without that context it guesses, and you end up with reports that look authoritative but use definitions nobody approved. Data Governance Enabled AI means your AI tools start from the definitions your people have approved, and anything new the AI creates goes to the stewards accountable for your data.
Steward-in-the-Loop:
Governance that runs in both directions
1. Approved definitions go in.
Before building a report, the AI pulls approved glossary definitions, calculations, and usage guidance from the Data Cookbook. Your AI reporting tool is instructed to cite them in every report, labeling each as a steward-approved definition or as an AI assumption waiting for steward review.
2. Reports and assumptions loop back to the data catalog.
Details of the finished report are posted back to the Data Cookbook’s report catalog. If the AI had to assume anything along the way, such as a new data definition, a source mapping, or a calculation, those assumptions come back too. They arrive as new glossary terms with technical definitions, linked to the report.
3. Stewards validate.
Data stewards review the report and the new terms, then approve or edit them.
4. The glossary gets stronger. Approved terms are sent back to the AI tool through the MCP server as updated definitions. The next report starts from better information. Each report that gets validated makes the AI more accurate about your data, and your stewards decide what counts as the truth.
AI Guardrails and Stewardship
What is the Data Cookbook MCP server?
MCP (Model Context Protocol) is an open standard, widely supported across major AI platforms, that gives AI tools one consistent, secure way to connect to other systems without a custom integration for each one. The Data Cookbook MCP server tells your AI-based tools what the data catalog can do and how to use it.
Why the Data Cookbook’s MCP server matters for your AI governance
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Bi-directional: AI tools don’t just read your glossary. They also submit reports, assumptions, and new terms for steward review.
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Open standard: Your approved definitions aren’t locked to a single reporting vendor, so they stay in place as your AI tools change.
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Ready to configure: IData’s guidance and documentation walk you through connecting your AI tools without custom development.