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"The 2026 QA Testing Benchmark Report"

Real production metrics from 1M+ runs on what breaks, what it costs, and what AI can fix.

Web agent benchmarks often imply AI is not ready for reliable, end-to-end automation. But production teams are already running meaningful workflows at scale, because real-world reliability is built from deterministic code, recovery logic, and maintenance over time.

In this report, Checksum analyzes 1M+ production automation runs to show what actually breaks and how often. The top failure drivers are selector changes (32%), flow changes (27%), environment instability (22%), and loading or timing issues (19%).

The report also offers insight into the economics of maintenance and the impact of AI-assisted repair. In the data, AI-maintained suites cut failure rates from 14.8 to 2.7 per 100 runs (an 82% reduction), and reduce human time per failure to about five minutes on average.

Offered Free by: Checksum.ai
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