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meta_description: "A practical checklist for evaluating whether your data warehouse has the definitions, relationships, policies, and lineage AI systems need before generating trusted SQL." slug: "evaluate-data-warehouse-ai-generated-sql" category: "Technical articles" author: "Arisyn" --- # How to Evaluate Whether Your Data Warehouse Is Ready for AI-Generated SQL AI can generate SQL quickly. That is no longer the hard part. The harder question is whether the SQL is grounded

The biggest challenge isn't giving AI access to more information. It's helping AI know which information to trust

Enterprise AI doesn't fail because of compute—it fails because of data ambiguity. Learn why trusted business definitions, data relationships, and clear context are essential for reliable AI.

Most enterprise AI projects don't fail because of the model—they fail because the underlying data architecture wasn't designed for AI. As AI agents become the primary consumers of enterprise data, trusted data foundations are becoming the key to reliable AI.

Discover why enterprise AI needs a shared understanding of business metrics. Learn how trusted metric definitions improve AI analytics, governance, and decision-making.