AI Readiness Assessment: 5 Questions

For a typical dataset, is there a clear description of what it holds and an agreed meaning for its key business terms?

These are understood by the teams closest to the data, not available universally Documented and maintained by hand, prone to drift from the live data Captured automatically in the catalog and kept current Kept current and served to AI tools the moment they query

Before an AI agent acts on a dataset, can it establish where the data came from, who owns it, and whether it is sensitive (such as PII)?

Not directly — this is established by the people who manage the data In part — it is documented, but separate from how data is accessed Yes — lineage, ownership, and sensitivity are tracked automatically Yes — and access rules are enforced automatically the moment data is queried

Given several similar datasets, can an AI agent tell the trusted, widely used one from a stale or duplicate copy?

Not yet — they look equivalent unless someone familiar weighs in With guidance — the right one is known, but has to be pointed out Yes — usage and trust signals are tracked automatically for each asset Yes — and those signals are surfaced so the agent selects the right one itself

If a pipeline fails or data goes stale, how quickly does that surface — before it reaches something downstream?

It surfaces once someone downstream notices something abnormal It can be caught by reviewing dashboards or run logs It is flagged automatically by monitoring and alerts It is detected continuously and tied to the exact affected asset

As AI agents begin running queries at scale, can you see which queries are slow or expensive, at the level of an individual asset?

Not yet — cost and performance are visible as an overall total After the fact — the detail can be worked out manually when needed Yes — speed and cost are tracked automatically across queries Yes — monitored continuously, for each asset and each query

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Your AI readiness

Catalog

Operational

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AI Readiness Assessment Report

Key strengths

Improvement opportunities

Recommended next steps

Find out how AI-readyyour data is

Where should we send your results?

Your AI readiness

Catalog

Operational

Key strengths

Improvement opportunities

Recommended next steps

Now that you know what needs to be done, see how Prizm can help you cover that gaps in just a few weeks.

Find out how AI-ready
your data is

Now that you know what needs to be done,
see how Prizm can help you cover that gaps in just a few weeks.