After-Hours at the General Practice
What pet owners call about when the clinic is closed, and how AI handles the conversation.
This report aggregates 6 months of AI-handled after-hours call data from a panel of general practice veterinary clinics on PupPilot. The data covers call categories, resolution outcomes, and call efficiency.
Read the research
This report stays the case it describes. For a benchmark, PupPilot Research measured after-hours demand on a panel of clinics in 2026: one call in five (20.5%) reached the after-hours assistant (routing-based, which also takes lunch-hour and unanswered daytime calls), 8.8% of calls to full-line clinics arrived after 6 p.m. or at the weekend (clock-based), and among calls with a stated urgency, 13.8% after hours were emergencies, against 3.9% during business hours. Based on a panel of veterinary clinics on PupPilot — more than 100,000 inbound calls and hundreds of thousands of minutes of conversation between March and September 2026.
After-hours veterinary calls: what comes in beyond the usual working day?
The After-Hours Call Mix
What do pet owners actually call about when the clinic is closed? General FAQ dominates at nearly half of all calls, but emergency and urgent calls make up a meaningful share that requires careful handling.
| Call Category | Share of Calls |
|---|---|
| General FAQ | 42% |
| Scheduling | 25% |
| Pet Emergency / Urgent | 13% |
| Pet Illness / Injury | 5% |
| Prescriptions | 3.5% |
| New Client Registration | 3% |
| Medical Paperwork | 2.7% |
| Billing | 2.5% |
The top three categories alone account for 80% of all after-hours calls. This concentration means clinics can address the vast majority of caller needs with focused AI training in just a few domains.
What Gets Resolved vs. What Needs Staff
Not every call can be fully resolved by AI, and that is by design. The system triages what it can and prepares clean handoffs for everything else.
The goal is not to replace staff judgment, especially for emergencies, but to make sure every caller gets an immediate, useful response and that staff see a clean summary when they arrive in the morning.
Call Efficiency
AI-handled calls are fast. The average after-hours call lasts approximately one minute, with wide variation depending on the complexity of the call type.
| Call Category | Avg. Duration |
|---|---|
| General FAQ | ~55 sec |
| Scheduling | ~45 sec |
| Pet Emergency / Urgent | ~1.5 min |
| Pet Illness / Injury | ~2.5 min |
FAQ calls resolve in under a minute because the answers are straightforward. Illness and injury calls take longer because the AI asks follow-up questions to build a complete summary for staff. Emergency calls are deliberately kept concise: identify the situation and route to an emergency facility.
What This Means for General Practice Clinics
Most after-hours calls are simple
Two-thirds of calls are FAQ or scheduling. These are high-volume, low-complexity interactions that AI handles well without staff involvement, freeing up the morning for clinical work instead of callbacks.
Emergency routing is viable but not a replacement
Nearly half of urgent requests are routed to ER by AI, but the other half need human review. The value is in immediate response and routing, not in replacing clinical judgment.
Callers talk to the AI
On PupPilot Research's 2026 panel of clinics, 98.9% of business-hours callers spoke to the assistant rather than hanging up without a word — engagement, measured, not a satisfaction score. Read the research.
Speed matters, but completeness matters more
The fastest calls are not always the best. Illness and injury calls take 2.5 minutes because the AI collects detailed information. That extra time produces better staff summaries and ultimately better patient outcomes.
Methodology
This report is based on aggregated, anonymized data from general practice veterinary clinics using PupPilot for after-hours call handling over a 6-month period ending Q4 2025. Call categorization is performed by the AI in real time and validated through periodic human review. Resolution status is determined by whether the caller's primary intent was addressed without requiring staff follow-up. All data is presented in aggregate; no individual clinic or caller data is identifiable.