The data foundations checklist we use on every engagement

Before we agree to scope an AI initiative with a client, we walk through the same short checklist. None of it is glamorous. All of it decides whether the project lands or quietly evaporates.

The checklist

• Is there a single owner for the data this initiative depends on?
• Do we know where it lives, who updates it, and how often?
• Are the definitions for the key terms agreed across teams, in writing?
• Can we trace a number on a dashboard back to its source without guessing?
• Is access governed by role, not by who happened to ask first?
• Do we have a place to put new datasets that isn't someone's laptop?

If more than two answers are "sort of", we don't start with AI. We start with the foundations - and we say so out loud.