Is Your Data Ready for AI? A Short Checklist
AI is only as good as the information behind it. Check yours in ten questions.
AirBrain Team 6 min read
| # | Question | If "no," try this |
|---|---|---|
| 1 | Do you know where the data for this workflow lives? | Map the sources: systems, folders, inboxes |
| 2 | Is there one source of truth? | Pick one system as the reference |
| 3 | Is it reasonably accurate? | Spot-check 50 records and note error patterns |
| 4 | Are duplicates under control? | Add matching rules and clean-up |
| 5 | Is it up to date? | Set owners and review dates |
| 6 | Is it structured enough? (consistent fields, naming) | Standardise the key fields |
| 7 | Can you access it programmatically? (API, export) | Ask IT about connectors or exports |
| 8 | Do you have examples of good outcomes? | Collect 20 to 30 well-handled cases |
| 9 | Are permissions clear? (who may see what) | Document access rules before connecting AI |
| 10 | Do you know the privacy rules that apply? | Check with your legal or compliance contact |
How to read your results
- Mostly yes: You're ready to pilot.
- A few no's: Fix those in parallel with a pilot.
- Many no's: Start with Data & AI Engineering. It will pay off for every AI project after.
Don't boil the ocean
You don't need to fix all company data. Choose the one workflow, find the data it needs, and make that good first.
A note on documents
Have a workflow in mind?
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