Enterprise enablement case study

AI Academy

A layered learning strategy that moves from shared responsible-AI foundations to increasingly advanced and role-specific application.

As part of a three-person AI team, I helped design the academy pyramid. I owned the learning design and content for the foundational eLearning and served as subject-matter expert and learning-flow designer for the remaining training layers. Course developers created the finished visual learning experiences.

AI literacyLearning strategySubject-matter expertise

Problem

Organizations needed employees to understand AI, use it responsibly, and connect new capabilities to practical work rather than isolated tool demonstrations.

My role

I helped design the academy pyramid as part of a three-person AI team. I independently owned the learning design and content for the foundational eLearning, excluding course development. For the remaining training layers, I served as subject-matter expert and designed the learning flow.

What I produced

The foundational eLearning design and content, plus subject-matter direction and learning flows for instructor-led, advanced, and role-specific training. The three-person team jointly conducted the initial focus groups that informed the vertical training.

Evidence/result

The shipped client programs created a scalable path from baseline AI literacy to advanced and function-specific application. The viewable draft ethics module is one sample from the foundational eLearning I designed.

A layered learning strategy

Broad foundations. Focused application.

The audience becomes more targeted as learning becomes more advanced and specific to the work.

Collaboration

Own the work. Build it together.

The academy required shared architecture, individual ownership, and close handoffs. I collaborated with the AI team on the pyramid and focus groups, owned the foundational eLearning design and content, shaped the other learning flows as an SME, and partnered with developers who built the finished experiences.

Learning in the work

Start with friction, not features

The three-person AI team began the vertical-training design with focus groups. Those conversations surfaced function-specific friction points and where AI could help, keeping the learning connected to workflow, judgment, and business value.

View the evidence

A sample from the foundation.

The draft AI ethics module shows how the academy introduced responsible use as part of baseline AI fluency.