Executive Summary
Credit unions do not need to have every answer before they begin using AI, but they do need a clear way to use it safely. This guide starts from the reality that employees and vendors are already bringing AI into daily work, often faster than policies and governance can keep up.
The report gives credit union leaders a practical path forward, from approved tools and data rules to staff training, vendor questions, use cases, measurement, and escalation. The message is not to slow AI down, but to make it usable in a way that fits the credit union model, with a focus on member trust, consistent human review, and steady progress over scattered experimentation.
Credit Union Implications
- Bring AI use into the open so staff have a safe, approved way to experiment.
- Protect member data first, especially in lending, compliance, BSA/AML, audit, and board work.
- Start with low-risk, useful tasks before moving into higher-risk use cases.
- Ask vendors where AI is already embedded and how it handles credit union data.
- Treat AI readiness as a leadership, culture, and governance issue, not just a technology project.
Filene’s Center for Design for Digital is generously funded by:
