QA Automation Performance Benchmarks
This page presents normalized benchmarks comparing autonomous agentic QA automation with AI-assisted and script-based testing approaches. Results focus on execution speed, maintenance effort, and cost efficiency for web and mobile applications.
Benchmark Methodology
To ensure objective comparison, the following methodology was applied during internal benchmarking:
- Tests executed on representative web and mobile applications with standard UI patterns.
- Comparable functional and regression coverage maintained across all automation tools.
- Execution performed in a clean, CI-like cloud environment with equivalent resource allocation.
- Results normalized on a 100-point scale for multi-attribute clarity.
Test Execution Speed
Execution speed affects developer feedback cycles and CI/CD throughput. Autonomous agentic systems optimize execution paths by minimizing unnecessary waits and intelligently batching requests.
Test Execution Speed
Normalized illustrative benchmarks. Based on internal testing and publicly available information. Results may vary by application.
Test Maintenance Effort
Manual maintenance increases long-term QA cost and slows teams. Agentic AI eliminates manual selector updates and script refactoring through continuous UI and API discovery.
Maintenance Effort
Normalized illustrative benchmarks. Based on internal testing and publicly available information. Results may vary by application.
Cost Efficiency Over Time
Infrastructure usage and human effort determine real QA cost. By reducing both execution time and manual maintenance, agentic automation provides significant efficiency gains as test suites scale.
Cost Over Time
Normalized illustrative benchmarks. Based on internal testing and publicly available information. Results may vary by application.
Key Observations
Total Autonomy
Autonomous execution reduces manual intervention by over 90% compared to traditional frameworks.
Resilience
Self-healing logic minimizes test breakage during UI refactors and API schema changes.
Resource Optimization
Optimized execution runs lower infrastructure usage, resulting in direct SaaS cost savings.
Disclaimer: Benchmarks are illustrative and based on internal testing and publicly available information. Actual results may vary by application, environment, and usage patterns.