Guide
The 90-Day AI Readiness Plan for Community Banks
Dec. 14, 2025 · Prepared by Terrence A. Thomas
Many community banks want to move faster with AI, but get stuck between competing priorities, unclear governance, and uncertainty about what “regulator-safe” progress looks like. A 90-day plan works when it emphasizes readiness and controls — not just pilots.
What “AI readiness” really means
- Use-case clarity: a short list of high-value decisions that can be improved, measured, and governed.
- Data readiness: lineage, quality, privacy, and documented assumptions.
- Security and access: least-privilege access, audit logging, and clear boundaries.
- Model governance: validation, monitoring, documentation, and accountable owners.
- Change enablement: adoption plans that don’t rely on “hope and training.”
The fastest path to meaningful AI progress is a readiness sprint: define scope, harden data and governance, and ship one measurable win — without creating audit debt.
What banks can do in the next 90 days:
Confirm the first use case, define success metrics, assign owners (business + IT + risk), and document what the model can and cannot do. Establish data sources, access boundaries, and an initial “audit pack” outline.
Build a clean data map (lineage + definitions), define permissible use, set privacy constraints, and design controls for overrides, exceptions, and monitoring thresholds. Align policy rules with any AI recommendations.
Establish validation routines (back-tests, stability checks, stress scenarios), implement drift monitoring, and confirm documentation standards. Ensure stakeholders can explain outcomes at both portfolio and individual-decision levels.
Launch one controlled capability, track performance and adoption, and complete a “first-audit” walkthrough internally. Confirm your playbook is repeatable before scaling to the next use case.