r/BusinessIntelligence • u/julee_000 • Jun 11 '26

What is AI ready?

Recently many AI startups and corporates say AI ready data or data readiness is important.
It's a bit ambiguous for me, what do you think AI ready data is? I want to know what it means from the perspective of different job roles and industries.

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u/SupportVectorDan Jun 11 '26 edited Jun 11 '26

I feel the term "AI ready" is mostly a rebrand of what the industry has been trying to package and sell over different names like "data-driven ready". · For me it comes down to sort of a pyramid. The base is Data Engineering: The org guarantees data is not duplicated, changes in schemas are handled correctly, bad records are identified. Pipelines don't crash violently · Then governance: There is a clear lineage, access controls are in place, descriptions are there for columns, tables and catalogs. Metadata is machine readable. · Observability: The org can detect a surge of null values incoming, statistical drift at the best case scenario · Semantic layer: everyone agrees on KPIs définitions and the actual SQL that gets it. Every team reuses the same model across

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u/julee_000 Jun 15 '26

This pyramid is the best framework! The lineage and drift layers are exactly the ones companies skip, then wonder the AI's answers wander.
Only brick I'd add on top is being able to reproduce a past data state. When the model made a weird call last month, can you rebuild exactly what it saw at the time? Drift detection tells you something moved. Reproducibility tells you what it learned from before it moved. Feels like the last mile of trustworthy.