Ambient AI scribes listen to a consultation and draft the clinical note. For many clinicians the appeal is obvious: less typing, more eye contact and fewer evenings spent finishing notes. The market has moved quickly, and practices are being approached by vendors almost weekly. That is exactly why a short, disciplined evaluation pays for itself.
1. Where is the data stored and processed?
Ask where audio and transcripts are processed and stored, whether any data leaves Australia, how long recordings are retained, and whether your data is used to train the vendor’s models. Get the answers in writing.
2. How is patient consent obtained and recorded?
Patients should know a scribe is in use and be able to decline. Decide how consent will be sought, how it is recorded, and what happens when a patient says no. Professional bodies, including the RACGP, have published guidance on this; read it before you start.
3. Who checks the note?
The clinician remains responsible for the record. Build review into the workflow and be alert to errors and omissions, particularly with medication names, numbers and negatives.
4. Does it integrate with your practice software?
A scribe that saves five minutes of typing but adds three minutes of copying and pasting is not a saving. Test it inside your real workflow.
5. What does it really cost?
Look past the per-clinician price to set-up, training, contract length and exit terms. Can you export your data if you leave?
6. How will you measure success?
Agree the measures before the pilot: documentation time per consult, after-hours charting, clinician satisfaction and patient feedback. Capture a baseline first.
7. Is this the right problem to solve first?
Sometimes the biggest time sink is not the note at all, but recalls, referrals or inbox management. A short diagnostic can tell you where AI, or simply a better process, would help most.
This article is general information, not legal, clinical or regulatory advice. Always check current guidance from your professional body and the relevant regulators before adopting AI tools.