Our methodology

The ADKAR model. Applied to your credit union.

We use the Prosci ADKAR model — the most-cited individual-change framework in the change-management industry — to guide every CUcomputer engagement. Five stages, mapped to credit-union AI adoption.

ADKAR® is a registered trademark of Prosci, Inc. We use the model with attribution; the credit-union-specific application below is ours.

The model

Five stages. In sequence.

ADKAR is sequential. Skip a stage and the change doesn't stick. We measure each one for every credit-union team we train.

A
Awareness
of the need for change
D
Desire
to support the change
K
Knowledge
of how to change
A
Ability
to demonstrate new skills
R
Reinforcement
to make it stick
A
Stage 01
Awareness

Awareness of the need for AI in your credit union

Before any training begins, every team — branch, operations, marketing, executive — needs a shared understanding of *why* the AI exists. We run kickoff sessions tailored to each audience, framed in their language: ROI for executives, member experience for branch staff, throughput for operations.

Outcome

Every team knows the why before the how.

D
Stage 02
Desire

Desire to engage with the AI Agents

Resistance kills adoption. We surface the fears (job loss, replacement, unfamiliar technology) early and address them directly. Each team sees how the AI removes the work they hate — manual data entry, repetitive transcription, late-night escalations — so they want it, not just tolerate it.

Outcome

Your team chooses to use the AI.

K
Stage 03
Knowledge

Knowledge of how to operate it

Role-specific training, not a generic walkthrough. Tellers learn how AI Transcription surfaces member context. Marketing learns the brand-voice approval flow. Operations learns the AI Signals dashboard. Executive learns the ROI view. Every team gets what they need — nothing more.

Outcome

Each role knows their workflow cold.

A
Stage 04
Ability

Ability to use it on real work

Hands-on, shoulder-to-shoulder with a CUcomputer engineer. Real member calls, real campaigns, real data — under live supervision. We don't leave until every team has demonstrated the skill in production, not in a sandbox.

Outcome

Your team operates the AI on real workflows.

R
Stage 05
Reinforcement

Reinforcement to make it stick after we leave

Adoption fades without reinforcement. We schedule monthly check-ins at no cost for the first year. ROI dashboards stay live. New team members get the same training. M&A AI Agents continue to handle unstructured data as your CU grows or merges.

Outcome

AI use becomes the default, not the exception.

Next step

Adoption is measurable.

Every CUcomputer engagement is scored against ADKAR at each stage. You always know where your team stands — and we don't move forward until each stage is clear.