In March 2023, my manager gave me a mandate: figure out AI. Not the hype—the actual tools. What works, what doesn't, and how our team could use them.

I'd been a ChatGPT paid user for 2+ years at that point. The difference between casual use and organizational deployment is massive. Personal experimentation is low-stakes. Organizational adoption requires methodology.

The approach:

■Landscape analysis: Vetted dozens of AI services for real-world applicability
■Knowledge infrastructure: Built 'AI Central' on our SharePoint as the definitive resource
■Practical toolkit: Curated the 'AI Toolbox' with tools for presentation design, data visualization, video generation
■Proof of concept: Produced avatar-led training videos demonstrating AI-powered meeting synthesis

The breakthrough wasn't the tools—it was the framework. AI adoption fails when it's treated as magic. It succeeds when it's treated as workflow architecture.

Key lessons:

■Start with pain points: Don't ask "what can AI do?" Ask "what takes too long?"
■Document everything: The AI Central hub became our institutional memory
■Show, don't tell: The avatar videos proved the concept faster than any deck
■Operationalize early: Move from prototype to production fast

By 2024, we were running fully AI-generated training campaigns. The 'Smarter Way to Work' MFA-OTP video used a complete AI chain: Gemini for scripts, Sora for visuals, ElevenLabs for narration. The ID Theft & Fraud videos validated the model as a reliable internal service.

The shift from experimental to operational took 18 months. The CI team went from AI-curious to AI-native. We're now the internal service bureau for advanced media production—capabilities rivaling external vendors at a fraction of cost and time.

The real win? We didn't just adopt AI. We built the adoption framework that others can replicate.