AI Enablement & Education·2022–Present Client-confidential
Enterprise AI Enablement
AI that non-technical teams can actually own.
My role
Builder & instructor
Outcome
Non-technical users went from wary of an AI tool to owning an AI-powered workflow.
01
The problem
- A powerful AI capability is worthless if the people it's meant for won't or can't use it. Enterprise AI projects fail far more often at adoption than at modeling.
- The intended users were non-technical. They didn't need to understand transformers; they needed to trust the tool, understand its limits, and fit it into how they already worked.
02
The approach
- I built the AI-powered application inside Snowflake so it lived where the data and the users already were — no new platform to learn.
- Just as importantly, I designed the enablement around it: onboarding materials, hands-on training, and internal notebooks that translated the AI concepts into plain workflows.
- I framed the AI in terms of what it's good at and where it needs a human — building appropriate trust rather than hype.
03
The outcome
- Non-technical users adopted the tool as part of their real work, not as a demo.
- The same enablement approach — blogs, tutorials, notebooks — raised baseline AI/ML fluency across the wider organization.
Technologies
SnowflakeCortex / LLMsStreamlitPythonTechnical Enablement