Systems | Development | Analytics | API | Testing

Xray is transitioning into a Forge App, Atlassian's modern cloud development platform, using Forge Remote to strengthen security, align with Atlassian's long-term roadmap, and support future innovation. If you're wondering what the Xray Forge migration means, the short answer is simple: your testing workflows stay exactly the same. The changes happen behind the scenes, improving the platform that powers Xray while maintaining the features, scalability, and performance your team relies on.

AI is becoming part of every stage of the testing lifecycle. Teams are using it to analyze requirements, design test cases, generate automation scripts, and accelerate execution activities that previously required significant manual effort. Within Xray, AI already helps transform Jira requirements into actionable test cases with AI Test Case Generation.

AI is becoming part of every stage of the testing lifecycle. Teams are using it to analyze requirements, design test cases, generate automation scripts, and accelerate execution activities that previously required significant manual effort. Within Xray, AI already helps transform Jira requirements into actionable test cases with AI Test Case Generation.

Test execution is one of the most time-sensitive stages of software delivery. Teams are expected to validate functionality, ensure stability, and support release decisions within increasingly shorter development cycles. Even with strong automation in place, there is rarely enough time to execute every Test before a release. This makes prioritization a critical part of the QA process.

For organizations developing regulated products, risk management and testing are closely connected. Every identified risk must be assessed, mitigated, verified, and documented to support compliance requirements and release decisions. Yet these activities often happen in separate systems. Risk assessments may live in dedicated risk management tools or spreadsheets, and testing is usually managed elsewhere.

With the release of Xray Cloud 15.0.0, Xray expands its latest AI capabilities with the introduction of AI Test Prioritization, joining two recently released features: Xray's Rovo Test Plan Summarizer and AI-generated Manual Scripts for Test Case Designer, introduced in Xray Cloud 14.0.0. Testing is rarely just about executing test cases. Teams need to understand where risk exists, how testing is progressing, and whether a release is ready to move forward.

Understanding the health of a Test Plan isn't always as straightforward as it sounds. A Test Plan may contain hundreds of Tests, multiple Test Executions, linked requirements, and defects spread across different areas of a project. The information teams need is usually there, but finding answers often means navigating through several screens, reviewing reports, and manually connecting the dots. Questions such as How much testing has been completed?, Are there any coverage gaps?

At Assurity Consulting, our experts are deeply experienced in leveraging a variety of industry-leading Test Management tools, with Xray for Jira being a prominent example in our toolkit. Our commitment, however, extends beyond proficiency in a single platform. Our core approach is fundamentally tool-agnostic, meaning we prioritize the client’s unique context, goals, and technological ecosystem over allegiance to any specific vendor or solution.

Xray has won the Atlassian Marketplace Partner of the Year 2026: Software Collection Apps, recognizing its continued contribution to the Atlassian Marketplace and its role in supporting software teams with native test management inside Jira. The award was announced in Anaheim during Atlassian Team ’26, as part of the Atlassian Marketplace Partner Awards celebrations recognizing outstanding partners across the Atlassian ecosystem.

The first-ever Sembi Software Quality Pulse Report is based on nearly 4,000 responses from QA engineers, developers, security professionals, and engineering leaders worldwide. The findings paint a picture of an industry in motion—and a QA function that increasingly relies on tighter integration, thoughtful AI adoption, and better-connected workflows to keep up. Here's a look at some of the data that matters most for agile QA teams working inside Jira-native environments. TL;DR.