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Worksheet
Is Your Data AI-Ready? Five Honest Questions
AI is only as good as the data underneath it. Point a clever model at messy, scattered data and you get confident, wrong answers — faster. Before you invest in AI, score your data honestly against these five questions. Give each a 0 (no), 1 (sort of), or 2 (yes).
- Can you find it? Is the data this workflow needs in a known place, or scattered across inboxes, spreadsheets, and someone’s laptop? If you can’t find it, AI can’t either.
- Can you trust it? Is it accurate and current, or full of duplicates, blanks, and “we fix that by hand” exceptions? AI will treat the mess as truth.
- Does someone own it? Is there a clear person responsible for keeping this data clean and correct — or does everyone assume someone else does?
- Is it consistent? Does “customer,” “date,” or “status” mean the same thing everywhere it appears? Inconsistent definitions quietly break every automation built on top.
- Is access controlled? Do you know who can see and change it, and could you review what an AI tool did with it? If not, that’s the first thing to fix — before, not after.
What your score means
| Total (out of 10) | Where you stand |
|---|---|
| 0–3 | Not yet. Fix the data foundation first. AI now would amplify the mess. This is the highest-value work you can do. |
| 4–7 | Getting there. Pick the one weakest answer above and fix it. You’re close enough that a focused cleanup unlocks real options. |
| 8–10 | Ready. A specific, well-scoped AI use case is worth exploring — start small, keep a human in the loop, and measure it. |
Our whole approach is built on this order: clarity before automation, automation before AI. If this worksheet stung a little, that’s useful — it means you just found the work that actually moves the needle.
Want to know which of these matters most for your operation? The free Self-Check points you at your biggest blocker in about seven minutes.