C5i: Who can build with AI, and who can lead it
Client: C5i · Sector: AI & Analytics · Engagement: Enterprise AI Capability Transformation
C5i's leadership wanted more than completion rates. They wanted to know, person by person, who can build with AI, who can lead its adoption, and who needs support. Ambilio built that view into the program from day one.
A baseline before any learning
Every participant completed a role-based readiness assessment before the first session: applied multiple-choice questions plus scenarios drawn from real delivery situations. Results were scored by capability category, not as one headline number, so gaps showed where they actually sat.
Five AI adoption archetypes
Each person was mapped to one of five archetypes:
- Builder: builds AI solutions others rely on.
- Multiplier: spreads AI practice across the team.
- Adopter: uses AI consistently in their own work.
- Observer: knows AI, applies it occasionally.
- Resister: avoids AI or works around it.
Placement used a composite of category-wise performance, not the headline score. Two people with the same score can land in different archetypes, and that difference is the one that matters for staffing. C5i received a per-person report and a written methodology showing how every placement was derived.
Measured all the way through
Ambilio's LMS ran the full journey: pre-readings, assessments and daily progress reports to C5i while the program was live, not after it closed.
Certification required clearing every tollgate: pre-readings, in-session participation, the capstone build, the capstone presentation and a final assessment with fresh questions. Capstones were scored per person, criterion by criterion, so a strong team could not carry a weak member. Certificates are co-signed by C5i's CHRO and Ambilio.
Entry and exit, side by side
The archetype mapping was applied again to the final assessment. C5i now holds an entry and an exit position for every participant: who moved, how far, and in which capability categories.
That gives leadership a basis for real decisions: who to staff on AI-led client work, who to make an adoption champion, and where the next round of capability building should focus.
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