Autonomous testing with Jira and BearQ
Atlassian introduces BearQ, an AI agent for Jira that autonomously tests code by integrating directly into workflows, reducing defects and manual handoffs.
Teams often struggle with brittle test suites and generic AI tools that fail to align with delivery plans, leading to blind spots and late-stage defects. BearQ addresses this by acting as an assignable AI teammate within Jira, exploring user journeys and generating adaptive test coverage based on work items. Once code is ready, teams can assign BearQ to a Jira ticket or @mention it in Rovo Chat to initiate testing, parsing acceptance criteria and technical requirements to create test cases and document reproduction steps.
BearQ eliminates the need for manual context gathering by turning Jira work items into living test context, reducing handoffs between product, engineering, and QA. It autonomously explores applications in real time, discovering untested user paths and edge cases that static scripts miss, while dynamically adapting tests as application behavior changes. This allows teams to catch regressions early and validate results faster, shifting from days to minutes in the testing cycle.
The agent acts as an autonomous teammate, validating across applications while teams set guardrails and retain oversight. When BearQ identifies issues like regressions or UX problems, it creates Jira issues with reproduction steps and evidence, reducing triage time and enabling QA to focus on higher-risk tasks.
BearQ for Jira is now available on the Atlassian Marketplace, allowing teams to connect it to their Jira workspace and integrate testing directly into their delivery workflows. The tool aims to unify testing and development by embedding quality assurance into the agent-orchestrated workflow.