The false wait for perfection
Some companies postpone AI until a large data platform is complete. Others move forward without understanding what their data means. Both extremes create delay or risk.
A minimum viable foundation
For each use case we define sources, minimum quality, owners, frequency and traceability. Governance is designed around value, not as an abstract program.
- Shared metric definitions.
- Controlled and traceable access.
- Quality rules tied to usage.
- A business owner for each critical data element.
Practical decision
Build the data foundation the first use case needs and leave an architecture ready to grow. This creates value without creating unmanageable debt.