What is the difference between RAG and agent memory?

RAG retrieves documents at query time to answer a question from a knowledge base. Agent memory persists facts and context across sessions, so the agent remembers what happened last week without re-reading a document.

Do enterprises need a knowledge graph to build good agent data?

Not always. A knowledge graph helps when an agent needs to reason across many linked entities, but many enterprises get most of the value from clean structured data plus well-chunked documents before a graph is needed.

Which of the three agent data pillars should a company build first?

Start with structured data if agents will answer factual questions from your systems of record, since it is usually the fastest win and the most governed data you already have.

How much enterprise data is actually usable by agents today?

As much as 90% of enterprise data is unstructured (IDC, via Box), which means most of it needs cleaning, chunking, and metadata work before an agent can use it reliably.

Is agent-ready data different from analytics-ready data?

Yes. Analytics-ready data tolerates occasional errors because a human reviews the dashboard. Agent-ready data needs continuous quality and governance because the agent acts on it without that human check.

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Technology2026-09-08EN

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Ellen Minh Nguyen

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