Data quality is a property of the data. Evidence fitness is a relationship between the data, the question, and the cost of being wrong. Stewardship has mastered the first. As AI systems move from displaying data to recommending action, organizations need the second.
AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Identify, evaluate, and prioritize AI opportunities for your business
Use these 5 dimensions to spot areas in your business that AI might improve. For background info on each dimension, click here.
Manual, rule-based, repetitive tasks
You already collect data, but don't use it well
Friction, lack of personalization, delays
Improve coordination, visibility, or forecasting
Automating content creation and knowledge work
Scoring Guide:
| Score | Description |
|---|---|
| 1 | Very low or unclear |
| 2 | Weak or limited |
| 3 | Moderate or partially in place |
| 4 | Strong and mostly ready |
| 5 | Very strong and fully aligned |
Strong opportunities score well across all 4 dimensions. Weakness in one doesn't mean 'no' — it means 'plan accordingly'.
Immediate implementation, low complexity, high readiness
Medium-term implementation, moderate complexity
Long-term vision, high complexity, strategic impact
This matrix plots your opportunities based on Impact (x-axis) and Feasibility (y-axis).
