Updated 2026-02-25
Decision Quality Scorecard for AI-Enabled Teams
A scorecard to evaluate whether AI-assisted decisions are actually improving leadership outcomes.
LeadershipMeasurementDecision 8 min For Leadership teams, operations leads, PMO
What You Will Get
- Measure decision quality beyond speed metrics
- Detect drift in judgment and execution consistency
- Build a repeatable leadership review standard
Why a separate scorecard
Output volume is not decision quality. Teams need a structured way to track whether AI improves judgment and business impact.
Core dimensions
- Clarity: was the decision question defined precisely?
- Evidence quality: were assumptions and data confidence explicit?
- Risk handling: were major downside scenarios addressed?
- Execution quality: were ownership and deadlines clear?
- Outcome alignment: did results match the intended objective?
Scoring approach
- Score each dimension 1-5.
- Flag any dimension below 3 for corrective action.
- Review trends monthly, not in isolation.
Leadership practice
Pair this scorecard with weekly review meetings and override logs to calibrate both AI use and human judgment quality.