Adoption.Engineered.

We train every team that touches the AI — branch, operations, marketing, executive — and own the curve until adoption is sustained.

How we deliver
Result

Adoption is what makes the AI work.

6×
Greater AI ROI when paired with structured change management
87%
Sustained AI adoption at 12 months across engagements
30 days
From kickoff to first measured behavior change
100%
Investment-back guarantee on every adoption engagement
CUcomputer

Built for credit unions.

Microsoft Co-PilotAzure PartnerNCUA-alignedOSFI-aligned

Every CUcomputer engagement runs on the Prosci ADKAR model — the same change-management framework used by the country's largest banks and credit unions. Adapted for AI adoption inside credit-union operations.

ADKAR methodology Role-based curricula M&A AI Agent 30/60/90-day reinforcement Adoption dashboards Investment-back guarantee

Branch and ops teams understand why the AI is being adopted.

Awareness

Engineered buy-in, every role, day one.

Desire

Live training on your data, in your terminology, per role.

Knowledge

Manager dashboards, check-ins, reinforcement clinics, first year.

Reinforcement
The framework

The Prosci ADKAR model.

Five outcomes every person must reach for a change to succeed. The same framework used by the largest US and Canadian credit unions for any technology rollout — and the one we run every CUcomputer engagement on.

  1. AAwarenessOf the need for change
  2. DDesireTo participate and support the change
  3. KKnowledgeOn how to change
  4. AAbilityTo implement required skills and behaviors
  5. RReinforcementTo sustain the change
The human factor

Top challenges of enterprise AI adoption.

For AI adoption to succeed, employees have to feel prepared, supported, and confident using AI in their daily work. Most organizations underestimate the human factors — uncertainty, trust, alignment — that ultimately decide whether the AI sticks.

Lack of training in AI tools
38%
Difficulties in system integration and AI tool functionality
16%
Unclear AI strategies and lack of leadership direction
15%
Concerns over AI data and information quality
13%
010203040
Source: Prosci, Artificial Intelligence Adoption Across the Enterprise.
The research

Effective change management. Measurably better outcomes.

Prosci's longitudinal benchmarking study of change initiatives across thousands of organizations. Projects with excellent change management deliver better project, schedule, and budget outcomes by a wide margin.

7×
More likely to achieve project objectives
4.6×
More likely to stay on or ahead of schedule
1.4×
More likely to stay on or under budget
Source: Prosci, Best Practices in Change Management benchmarking study.
Who we train

Every team that touches the AI. In their language.

Generic AI training fails inside credit unions. We run separate curricula for each role, on your live data, in your terminology.

Branch

Tellers and member-services reps learn the AI on the same screens they use today.

Operations

Ops leads learn to read the signals, route work, and tune the rules.

Marketing

Marketing learns to act on the segments the AI surfaces — without the data team.

Executive

Executives get adoption dashboards, ROI reads, and quarterly review templates.

FAQ

FAQ

What is ADKAR and why do you use it?
ADKAR is the change-management model from Prosci: Awareness, Desire, Knowledge, Ability, Reinforcement. It's the framework used by the largest banks and credit unions for any technology rollout. We use it because the research is clear — AI projects with structured change management deliver up to 6× the ROI of projects without it.
Do we have to use your AI products to engage you for change management?
No. We run change-management engagements for AI investments your credit union has already made — Copilot, an in-house model, a vendor platform — even if no CUcomputer product is in the picture. The methodology is the same.
What does the investment-back guarantee actually cover?
Each engagement has a measurable success metric agreed in writing at kickoff — typically a usage threshold, a workflow-time reduction, or a CSAT delta. If we don't hit that metric within 90 days of training completion, your investment is returned. No hourly billing, no expense recovery — full return.
How does the M&A AI Agent fit in?
Credit-union mergers are an unstructured-data nightmare — board minutes, member files, vendor contracts, policy docs, all in different formats. The M&A AI Agent ingests every source on both sides of the merger, unifies it into one queryable record, and surfaces the duplicates, conflicts, and gaps your integration team needs to resolve. We deploy it as part of M&A-specific engagements.
Do you train remote teams, or do you need to be on-site?
Both. Most engagements run as a hybrid: one on-site kickoff per cohort, then remote reinforcement clinics. For branch staff with mixed schedules, we record live sessions and offer make-up cohorts at off-hours.
How fast can a typical engagement start?
Two to three weeks from signed agreement to first live training session. The discovery phase runs in parallel with intake interviews; by week three, your first cohort is in the room.
Get started

Make the AI work. Make it stick.

30 minutes with the adoption lead who would run your engagement. We'll scope the cohorts, the success metric, and the guarantee on the call.

ADKAR methodology 30/60/90-day reinforcement Investment-back guarantee