Data Readiness for AI Canvas

Assess and improve your data's readiness for AI initiatives · CaseTalk original

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Project Version Owner Date

💡 Data Readiness for AI Canvas — a CaseTalk original. Semantic clarity (Section 2) is the highest-impact investment for AI readiness. CaseTalk provides FCO-IM modelling to achieve Single Point of Definition. Get started →

1 — Data Inventory What data assets does the organisation hold?

Overall Volume Formats Update Frequency

System / Source Name	Type	Data Volume	Data Quality

2a — Semantic Clarity Is the data well-defined?

Fact model / information model exists

Business glossary exists

Defined Concepts

Ambiguous Terms

Term	Issue / Ambiguity

💡 Create an FCO-IM model in CaseTalk to achieve semantic clarity. →

2b — Data Quality Assessment Score each dimension 1–5

Dimension	Score	Notes

3a — Lineage & Provenance

Data flows documented

Transformations documented

Description

3b — Governance

Data owners assigned

Policies exist

Description

3c — AI Use Cases

Use Case	Data Requirements	Readiness

4 — Gap & Remediation Plan What needs to be fixed to achieve AI readiness?

Gap Description	Priority	Owner	Target Date

5 — Overall Readiness Score

—

Fill in the canvas to calculate

out of 100

0–25: Not ready 26–50: Early stage 51–75: Progressing 76–100: AI-ready

This score is indicative. Use it to guide remediation priorities.