ENTERPRISE TEST MANAGEMENT AS A RISK CONTROL SYSTEM
The latest qTest Manager release cycle focuses on AI-assisted test design, stronger Jira security, MCP-driven automation, and tighter governance controls.
For CIOs, CTOs, QA Directors, and DevSecOps leaders, this release affects:
- How quickly requirements become executable test cases
- How securely Jira and qTest exchange traceability data
- How safely AI and support access interact with production test assets
- How reliably test evidence supports audit and release decisions
Test management is now part of enterprise risk management and SDLC governance.
AI CHAT AND AGENTIC TEST CREATION FOR SCALABLE COVERAGE
qTest AI Chat with Agentic Test Creation analyzes requirements, linked artifacts, and attachments to propose structured test cases directly inside the platform.
Business value:
- Standardized test design patterns across large portfolios
- Faster build-out of regression suites for high-risk releases
- Clear linkage between requirements, generated tests, and review history
Operational impact:
- Test designers shift from writing from scratch to reviewing and refining
- Teams generate edge cases, negative paths, and integration scenarios during backlog refinement
- Faster alignment between product, QA, and engineering
For enterprises managing thousands of Jira stories per quarter, AI-driven test generation supports consistent coverage and reduces interpretation gaps.
CUSTOM TEST STEP FIELDS FOR RISK AND DATA TRACEABILITY
qTest now allows up to five custom fields per test step.