Data and technology
1 min read
Data foundations come before AI readiness
AI readiness begins with trusted data, explicit ownership, well-defined use cases, and an operating model that can turn insight into action.
Readiness is a business question
An organization is not ready for artificial intelligence simply because it owns modern tools. Readiness depends on whether priority decisions are clear, relevant data is accessible and trustworthy, and teams can adopt new ways of working.
Build the minimum viable foundation
The goal is not to perfect every dataset before creating value. Focus governance and quality controls on the data required by the highest-value use cases.
- Name accountable data owners
- Agree critical definitions and quality thresholds
- Secure access according to risk
- Measure adoption and realized value
Move from dashboards to decisions
Business intelligence creates value when it changes the speed or quality of a decision. Executive dashboards should therefore connect indicators to thresholds, owners, review routines, and clear actions.
