How large are AI-built n8n workflows, and which fail validation?
52% of workflows created last week have at least 11 nodes and 19% have 31 or more. The larger the workflow, the less often it fails validation: 1.2% for 2–3 nodes versus 0.15% for 31–100.
- Last updated
- Oct 23, 2026
- Data window
- Oct 5–11, 2026
- Author
- Romuald Członkowski
- 2-3 nodes1.18%
- 4-10 nodes0.57%
- 11-30 nodes0.35%
- 31-100 nodes0.15%
- 101-300 nodes0.15%
The picture of AI producing only simple three-node automations does not hold. The validation result looks counter-intuitive at first: large workflows are built incrementally through many small updates, each of them checked (7 updates per create). Small workflows are often one-off drafts sent without a check.
History
One row per weekly issue. The table grows with every update.
| week | workflows | ≥11 | ≥31 | failed validation |
|---|---|---|---|---|
| 2026-W41 | 80,197 | 52% | 19% | 0.7% |
| 2026-W40 | 73,123 | 52% | 18% | 0.8% |
| 27 Sep 2026: telemetry source changed | ||||
| 2026-W37 | 118,918 | 55% | 21% | 1.0% |
| 2026-W36 | 98,043 | 49% | 19% | 1.8% |
| 2026-W35 | 98,122 | 55% | 21% | 1.0% |
On 27 September 2026 I moved n8n-mcp telemetry to new infrastructure. Versions older than 2.90.0 stopped reporting that day, so figures from before and after it come from different sets of installs. I don't compare one with the other.
Methodology · Data and charts may be reused with attribution (CC BY 4.0).