Many reporting projects start at the visible layer: pick a tool, connect a spreadsheet, choose a few charts, and publish. That can create a useful prototype. It rarely creates a dependable operating system.
The six layers of a trusted hub
1. Decision layer
Who needs to decide what, how often, and what happens if the signal is late or wrong?
2. Source layer
Which system controls the truth? What is the grain, latest complete date, join path, and reconciliation?
3. Meaning layer
What exactly does each metric include and exclude? Who owns the definition and threshold?
4. Experience layer
What view lets the audience find the answer, exception, and next action without decoding the report?
5. Workflow layer
Who reviews the hub, which exceptions create work, how are corrections recorded, and when does the system escalate?
6. Governance layer
What access, approval, evidence, validation, failure handling, retention, and rollback make the system safe to rely on?
Where AI fits
AI can make the hub more useful by classifying issues, explaining variance, summarizing exceptions, preparing follow-up, and retrieving context. It should operate inside the system's definitions and authority—not replace them.