"Is anyone actually using the AI tools we pay for?" Every team lead gets asked that, usually by finance, usually at the worst time. Usage tracking answers with numbers. - Per-person usage: aggregates hide the story. You want to see who runs 200 queries a week and which tool nobody opened since March. - Cost attribution: usage translated into dollars per team per tool per month. That is the number that justifies renewals or kills them. - Adoption analytics: which teams finished onboarding and which need help. Training and tracking belong together. - Privacy: be transparent about what is tracked. Teams that trust the data use it; teams that feel watched game it. Our database tracks AI tools by profession with real pricing tiers, and PrivateLLM deploy sets up a private LLM on AWS for $50 plus usage for teams that want usage data on their own infrastructure.