The value of AI depends less on the model and more on the readiness of the data behind it. That includes governance, quality, traceability and a realistic operating model.
What readiness looks like
- Define the source of truth for each metric.
- Standardize how data is cleaned and validated.
- Document who owns each dataset and process.
- Track lineage so teams can trust the output.