What I do
The model is rarely the hard part. The real work is building enough trust to start, enough habit to change how people work, and enough measurable value to keep scaling.
AI Enablement & Adoption Framework
My work follows a practical path: assess and govern the foundation, help teams turn AI into daily behavior, then automate and scale the workflows that create measurable business value.
Can AI succeed safely here?
Before scaling AI, I help establish the trusted foundation: readiness, permissions, content quality, ownership, and the minimum viable governance needed to move without creating unnecessary risk.
Can people change how they work?
Adoption is a behavior-design problem. I build cohort-based enablement loops around named tasks, manager follow-up, habit formation, and the usage signals that show AI is becoming part of daily work.
What should we automate?
Once the foundation and habits are in place, I help teams identify high-impact workflows, build and deploy solutions, use agents and automations responsibly, measure ROI, and scale what works.
Trust, habit, and value reinforce each other through a continuous improvement flywheel: learn, improve, scale, repeat.
Platforms I work in
The work is platform-agnostic in principle, but in practice I go deep on the Microsoft, OpenAI and Anthropic stack, where most enterprise AI I've come across lands today.
Microsoft 365 and Copilot (Cowork and Chat). Agents and Copilot Studio, Power Platform with proper environment, Codex and Claude Code, strategy, governance, Azure AI, SharePoint Online, OneDrive, and Teams. On the automation side, Power Automate and Blue Prism at scale.
That depth is a starting point, not a fence. New platforms appear constantly in this space, and picking them up quickly is part of the job — I'm always glad to learn the tools a problem actually calls for.