Quality Engineering
Ship Faster. Keep Quality First
Apply AI to optimise QA workflows, increase coverage and deliver sooner without compromise to quality.
Quality Engineering Roadmap
Roadmap to optimise quality engineering with AI—focused on scale, speed and consistency.
| Phase | Focus | Description | Status |
|---|---|---|---|
| Phase 1 | AI-Powered Test Data | Automate test data generation using structured AI understanding of requirements and data sources. | Complete |
| Phase 2 | AI Scenario Generation | Transform requirements and acceptance criteria into Gherkin scenarios. | Complete |
| Phase 3 | Cognitive Test Design | Introduce AI agents that design tests based on product goals, not just input-output validation. | Research |
| Phase 4 | Continuous Quality Intelligence | Enable predictive analytics that detect quality risks early across CI/CD pipelines. | Future |
| Phase 5 | Autonomous QA Ecosystem | Build self-learning quality assistants that evolve testing strategies from real user behavior. | Vision |