Data Before AI: Getting Your Foundation Right
Why most AI initiatives stall — and why the answer is almost always data. A practical framework for assessing your organisation's data readiness.
Show Notes
Most AI projects don’t fail because of bad algorithms. They fail because the data wasn’t ready.
Key Points
- The data maturity curve — where most organisations actually sit vs. where they think they sit
- The 10-question readiness checklist — a quick self-assessment for any leadership team
- Quick wins — three things you can do this quarter to improve data readiness without a massive investment
Links Mentioned
- Blog post: “The Data Readiness Checklist Every Executive Needs”
- DAMA-DMBOK Data Management Framework
Timestamps
- 00:00 — Introduction
- 03:00 — Why data readiness matters more than AI tools
- 10:30 — The 10-question checklist walkthrough
- 20:00 — Three quick wins for this quarter
- 26:00 — Wrap-up