KPI benchmark
How much does AI reduce appointment no shows?
Across 5 public AI deployments, the median no show reduction is 30%. Relative reduction in missed appointments.
30%
Median no show reduction
5
Public deployments pooled
3 of the 5 values are claims by the organization itself, a regulator or an independent study; 2 come from the AI vendor. One value per organization; "up to" claims are listed but not pooled. Data as of 12 November 2026. Methodology
No show reduction by industry
| Industry | Median | Deployments |
|---|---|---|
| Healthcare | 30% | 5 |
No show reduction by use case
| Use case | Median | Deployments |
|---|---|---|
| AI agent for patient appointment scheduling, reminders and no show reduction | 30% | 5 |
How to measure it
Missed appointments divided by booked appointments, before and after or versus a control group, on the same clinics or services.
Across the library
Median 30% across 5 deployments, reported range 8% to 50.7%.
Higher is better. Unit: percent.
Reported values by use case
AI agent for patient appointment scheduling, reminders and no show reduction
- Emirates Health Services50.7% · organization claim
- Good Shepherd Rehabilitation Network32% · vendor claim
- UMC Utrecht30% · organization claim
- Erasmus MC14.3% · organization claim
- Reid Health8% · vendor claim
Use cases that should track no show reduction
Frequently asked questions
- How much does AI reduce appointment no shows?
- Across 5 public AI deployments, the median no show reduction is 30%. Relative reduction in missed appointments.
- How do you measure no show reduction?
- Missed appointments divided by booked appointments, before and after or versus a control group, on the same clinics or services.
- What no show reduction do organizations in healthcare report?
- A median of 30% across 5 deployments in healthcare. Other industries have fewer than 3 reported values so far.
- Where do these no show reduction numbers come from?
- From public AI deployments in the Blits.ai AI Use Case Library. Every value is quoted from a named source, each organization counts once, and "up to" claims are listed but left out of the median. Data as of 12 November 2026.