A working simulation of how I'd run the rollout of an AI HR assistant: defining what "good" looks like (adoption, self-service resolution, satisfaction), tracking a phased launch, and automating the status reporting that used to eat hours of my week.
HR fielded the same repetitive questions — PTO balances, benefits enrollment, payroll dates, leave policy — through a shared inbox and ticket queue. HR generalists spent hours each week answering questions that didn't need a human, and employees often waited a day or more for a simple policy answer.
Scoped a phased rollout of HuBo, an AI assistant trained on HR policy docs and connected to the HRIS for personalized answers. Set adoption and self-service targets with department leads, instrumented usage and conversation outcomes into a single live dashboard, and added automated alerts so an escalation spike or satisfaction dip surfaces immediately instead of at the next sync.
Adoption, self-service performance, and satisfaction — synthetic data, updated through the current week.
These targets drive the KPI status colors, the target lines on the charts, and the alert rules below — edit them and everything recalculates live.
Phased milestones across the 12-week rollout. The dark marker shows the current week.
Once a department is fully onboarded, tracking shifts from "are people adopting this" to "is this working and saving time." These are early signals from Engineering — live since week 3, the only department with enough runway to show steady-state signal yet. Company-wide tracking of these KPIs begins at the "Full Adoption" milestone in week 12.
Two lightweight automations replace manual status tracking: live threshold alerts, and a one-click weekly digest.