The biggest barrier to adopting agentic analytics is the lack of sufficient context. Many organizations invest in advanced AI tools but find that their agents lack the context needed to reason reliably — including semantic definitions, metadata about how data was created and processed, and broader business context. 

As a result, teams spend significant time preparing data and building context before AI systems can deliver reliable insights. A strong data foundation is a critical part of that context, but it's not the whole picture.

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