Writing
Notes on AI employees
64 pieces for operators on one-process builds and the parts that still need a person. RSS
· Use cases
AI employee for onboarding
Onboarding is a checklist with a finish line. The employee chases tasks, files the docs, and flags the stuck ones. A person still grants access and signs the money. Measure people who actually start.
· Use cases
First-pass CV screening that stays honest
A first pass pulls facts against a written role. It does not hire. It does not invent a skill. Keep the criteria public to the team, the person on the gate, and a log you can replay.
· Use cases
After-hours support without a night shift
Nights need a queue, not a theatre. Close the repeats. Book or take a message. Wake a person when the protocol says so. The morning team should inherit state, not a pile of chats.
· Use cases
AI employee for appointment booking
Booking is offering a slot that exists, writing it down, and telling the truth when it does not. Escalate clinical and money questions. Measure no-shows and ghost bookings, not chat volume.
· Use cases
AI employee for document review
Document review is extract, flag gaps, and leave the weird cases. That loop cut review work by about half at SmartComply. The model was not the hero. The person on the miss was.
· Use cases
AI employee for internal operations
Internal ops is the copy-paste between two tools. Automate that first. Keep a person on money, access, and anything that changes a customer record. Measure cycle time, not “automation adoption”.
· Use cases
AI voice employee for inbound calls
Inbound voice is pick up, ask the right questions, and book the slot or route the call. A person still takes money, medical, and anger. Measure booked work and repeat-yourself rate.
· Use cases
AI employee for marketing ops
Marketing ops is a calendar, a brief, and a first draft. The employee researches, drafts, and keeps the week from going quiet. A person still owns claims, legal, and the publish button.
· Use cases
AI employee for recruiting
Recruiting AI is a first pass, not a hire. Keep a person on the decision. Write the criteria down. Treat NYC LL144 and the EU AI Act as reasons to go slower, not as footnotes.
· Use cases
AI employee for sales follow-up
Follow-up is lookup, a first note, and a flag for the leads worth a call. Do not let the employee discount or close. Measure replies that turn into meetings, not open rates.
· Use cases
AI employee for customer support
Support is a queue with a job description. Give the employee the repeats, a state handoff, and a 10–15% escalation target. Leave refunds and medical advice alone on day one.