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What "AI-ready" looks like in this area

• Every field a customer-facing process touches has a published definition.
• Same-named fields in different systems are either reconciled or explicitly labelled as different.
• A new analyst — or a new AI tool — can read the catalog and answer "what does this number mean" without scheduling a meeting.

What we typically find on Day 1

• Critical fields with no documented definition — "everyone just knows."
• Same-named columns that mean different things in different systems.
• Domain meanings that live in the heads of two or three long-tenured people.

What changes during a Business Transformation

• A published data catalog: every field, its definition, its lineage, its owner.
• AI tools query the catalog before reasoning over data; if a field has no definition, the AI surfaces the gap rather than guessing.
• The catalog becomes the artifact your team maintains — it is how the next analyst (human or AI) gets up to speed.

What stays the same

• Your data stays in your warehouses, databases, and systems of record.
• We do not migrate data to a new platform unless the existing one cannot support the work, which is rarely the case.
• What changes is documentation and access discipline, not the substrate underneath.

How this area connects to the rest

This is one of the seven areas an Enterprise Readiness review examines. The reference architecture that shows how all seven fit together is the agentic stack. The discipline that makes every engagement run the same loop is the repeatable process.