Our analytics team wanted to show how we're adopting AI tools, but faced a measurement problem: standard AI metrics focus on lines of code deployed to production which is not as meaningful for SQL pipelines and data work. We built a custom AI toolkit using IBM Bob and GitHub, and more importantly, created a tracking system that measured what actually matters for analytics teams. Six months later: 40-60% time savings, 50+ documented use cases, and a framework for measuring AI impact beyond code generation with the added bonus of sharing knowledge across the team as we all ramp and iterate our AI tool skills in real time.