Credit Union AI Adoption Scorecard
“Answer honestly — this is your snapshot. No right or wrong, only where you stand today.”
15 questions across 5 pillars. Select the option that best describes your credit union right now. You'll receive a scored maturity level for each pillar and an overall readiness rating.
Strategy
Executive alignment, roadmaps, and outcome mapping
We have a documented AI strategy tied to our mission and board-approved objectives.
AI initiatives are mapped to measurable member outcomes — not just cost savings.
We have a named executive accountable for AI strategy and a 3-year roadmap.
Governance
Ethics policies, auditability, and bias controls
We have a formal AI ethics policy reviewed by our board.
Our AI decisions are auditable — we can explain to any member how an AI decision was made.
We conduct regular bias audits on AI models that affect lending or member access.
People
Training, co-design involvement, and change management
Our staff has received meaningful AI literacy training in the past 12 months.
Frontline staff helped co-design our AI workflows — not just receive them.
Leadership actively addresses staff fear and uncertainty about AI replacing their roles.
Data
Data unification, consent, and incident response
We have a unified member data view across core, lending, and digital channels.
Member data consent and AI usage transparency is clearly communicated.
We have a data incident response plan for AI-related breaches or bias events.
Scale
Enterprise deployment, metrics, and execution velocity
AI is deployed enterprise-wide — not just in one or two pilot departments.
We report AI performance metrics to our board on a regular cadence.
We have a clear 90-day execution sprint planned or underway for AI expansion.