Why AI Projects Fail Without Trusted Data Foundations

We’ve been seeing a common pattern across AI projects lately:the issue usually isn’t the model — it’s the quality and structure of the data underneath it.

If the data lacks consistency, lineage, context, or trust, AI tends to amplify those problems rather than solve them.

We recently put together a piece exploring why data quality is becoming a core AI readiness issue in modern lakehouse environments, including where approaches like Data Vault can help create a more reliable foundation for AI.

Interested to hear if this aligns with what others are seeing.

https://ignition-data.com/resources/data-intelligence-series/your-ai-is-only-as-trustworthy-as-your-data-a-practical-framework-for-data-quality-in-the-modern-lakehouse

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