the situation
Interest in GenAI was rising fast, but adoption was uneven and fragmented. Some teams were ready to build and wanted autonomy to create agents and solutions quickly. Others were still unsure what GenAI was, how to use it safely, or which tools were approved. At the same time, decentralized purchases of AI tools and training were creating governance gaps and elevating security and compliance risk. IT and Procurement needed new capabilities and controls, because AI changes both work processes and how vendors and AI-embedded products must be evaluated.
the IDEA
Scale adoption without scaling risk. Create one operating model that covers the full journey:
- baseline literacy for all employees (responsible use)
- deeper capability for users (prompting)
- hands-on paths for builders (agent development)
- and reinforcement through leaders, champions, IT, and Procurement.
the solution
A tiered GenAI adoption model designed to scale confidence, capability, and value across the enterprise—combining clear guardrails, approved tools, role-based learning, and a build pathway for AI development.
1. One baseline, shared by everyone:
A short, mandatory foundational microlearning that answers the real questions fast: What is GenAI? What can I do with it? What tools can I use at work? What’s off-limits? Built to reduce hesitation and prevent unsafe experimentation.
2. Role-based enablement paths:
Clear enablement journeys based on how people engage with GenAI:
- employees build safe habits
- power users build prompting and applied use
- builders develop agents and solutions with autonomy in strategic areas
- champions and leaders translate, reinforce, and remove friction locally
3. A practice engine to make adoption stick:
A Community of Practice built for behavior change, not content consumption: short learning bursts, guided challenges, reusable prompt patterns, and visible before/after examples. A Copilot-based prompt coach helps members improve prompting and get unstuck in the flow of work. Measurement focuses on participation, capability lift, and time-saved signals.
what i did
- Owned the people-side change strategy for enterprise GenAI adoption, integrating comms, enablement, and reinforcement into a single change plan.
- Led stakeholder mapping and audience segmentation, defining change impacts, WIIFM, desired behaviors, and adoption paths for employees, power users, builders, champions, leaders, IT, and procurement.
- Built the engagement plan by audience, including message architecture, CTAs, practice prompts, and reinforcement loops.
- Developed the baseline microlearning and an AI FAQ, covering approved tools, prohibited uses, and responsible-use principles.
- Designed the power-user adoption engine: a Community of Practice with curated foundations, applied practice, peer learning, and a Copilot-based prompt coaching concept to accelerate capability lift.
- Helped shape the builder enablement pathway, enabling cohort-based learning so teams could develop agents/solutions with autonomy while staying aligned to standards, approvals, and safe build practices.
- Established the change network layer (champions + people leaders), including role clarity, onboarding materials, and engagement cadence to localize messaging, remove friction, and reinforce adoption.
- Built the IT training strategy based on process impacts from AI-embedded tools, defining the steps required from the team.
- Built the sustainment approach, including adoption communications, social proof (showcases/testimonials), recognition concepts, and adoption measurement signals focused on participation, capability lift, and value indicators.
why it mattered
GenAI adoption isn’t just a communications problem—it’s a capability and risk problem. Without a clear path, people either don’t use it (low confidence) or use it anyway (shadow tools, inconsistent practices, avoidable compliance risk). This plan put the right scaffolding in place: baseline responsible-use literacy for everyone, deeper pathways for power users and builders, and role-based reinforcement (leaders, IT, Procurement) so GenAI could scale safely and create value.
The rollout is ongoing, so success is being monitored through the following metrics:
- Capability uptake: learning-path completions and number of people trained
- Adoption velocity: number of GenAI solutions in production; percent of business units actively using GenAI
- Governance adherence: percent of GenAI initiatives following required guardrails
- Experience signal: NPS / satisfaction with tools and enablement
- Value realization: soft and hard benefits; value-to-cost ratio for GenAI solutions
- Reuse at scale: number of replicable GenAI solutions (so learnings don’t stay trapped in one team)
Early signals from the first pilot builder cohort (Copilot Studio):
- 44 participants
- 4.81 / 5 satisfaction
- +40 additional participants queued for upcoming cohorts
Cinthia Blanchard 
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