Copilots People Actually Use

Most AI pilots fizzle because they live outside the job. If you want adoption, put the assistant in the flow of work, give it guardrails, and measure real outcomes.

Pick narrow, painful tasks. 
Think: composing prior-auth packets, summarizing a client call, drafting a support reply with context. Tasks that are frequent, boring, and easy to verify.

Make risk visible. 
Classify the data, define what’s allowed, and log everything. Add human-in-the-loop where stakes are high. Compliance will meet you halfway if you bring proof.

Embed, don’t bolt on. 
The copilot belongs inside the tool people already use—EHR, CRM, code editor, helpdesk. Context improves quality and saves clicks.

Teach the model the job. Few-short examples, short rubrics, and checklists raise quality fast. Keep a feedback loop so the assistant gets better at your domain.

Measure what matters. 
Hours returned, resolution time, error rate, customer outcomes. If the numbers don’t move, adjust the use case or turn it off.

Don’t skip change management. 
Champions, short how-to clips, and office hours beat long manuals every time. Do this and your “AI strategy” becomes something people quietly rely on every day.