As the software industry faces mounting demands for speed, reliability, and efficiency, quality assurance professionals are meeting the moment with a more measured, pragmatic approach.
At least, that is the view of Amanda Sundara, general manager at TestRail, who said QA teams around the world are evolving—technically and professionally—by adapting to complexity with realism and renewed focus.
“While headlines champion AI-led testing revolutions, this year’s response reflects a shift toward maturity and realism,” Sundara explained.
“It’s a story of professional development through expanding responsibilities and skillsets, allowing teams to test with greater efficiency, accuracy, and confidence.”
Her remarks accompany the release of TestRail’s fourth annual Software Testing and Quality Report, a global study based on thousands of survey responses from QA professionals.
The 2025 edition explores how teams are navigating automation, tooling, and process transformation—while remaining firmly grounded in the human-driven aspects of quality assurance.
Sundara noted that although artificial intelligence continues to generate excitement, its role in testing is still evolving.
“Despite fears that AI may one day replace human testers, we’ve found it’s actually most effective at freeing up time for them to sharpen core capabilities and focus on critical tasks,” she explained.
This year’s report saw its largest participation from enterprise-level professionals to date, with most respondents working at mid-to-large-sized organisations in roles such as QA/Test Engineer, Analyst, and Lead.
The findings are organised into three core areas: QA processes and benchmarks, tools and technologies, and team responsibilities and challenges. New questions were also added to reflect growing interest in areas like AI, compliance and security, and QA’s evolving job market.
“While headlines champion AI-led testing revolutions, this year’s response reflects a shift toward maturity and realism.”
– Amanda Sundara
According to the report, the adoption of AI in QA remains fragmented and largely exploratory. While more than half of teams report using ChatGPT and nearly a quarter use GitHub Copilot, fewer than one-third have embedded AI directly into their core QA workflows.
Many cite integration difficulties and limited real-world impact as reasons for slow adoption.
Ambitions around automation continue to rise. Teams hope to automate 63% of their testing efforts by next year, up from the current average of 40%.
However, many still face hurdles such as test breakages, unreliable data, and gaps in skills – factors that often delay automation efforts and limit their scope.
Despite the growth of automation tools, manual testing remains essential. The majority of QA teams still perform functional, regression, end-to-end, and smoke testing manually. Rather than becoming obsolete, manual testing is evolving in parallel with automation, filling critical gaps that require human judgment and context.
There is also growing momentum behind shift-left testing. The report finds that 39% of QA teams are now being embedded earlier in the software development lifecycle. This early involvement correlates strongly with improved defect detection and higher satisfaction with overall quality processes.
Organisations with mature CI/CD pipelines are seeing clear results. Among teams that have invested heavily in continuous integration and delivery, 86% report faster software releases, and 71% report fewer defects making it into production. These outcomes highlight the benefits of aligning QA with broader DevOps practices.
However, many of the same structural barriers remain. Nearly half of all respondents say their teams are understaffed, and many still experience late-stage involvement in projects. End-to-end testing complexity and limited resourcing continue to constrain the ability of organisations to scale quality efforts effectively.
Looking ahead, Sundara emphasised the role of QA in balancing innovation with practical delivery.
“QA teams are intelligently aligning with organisational and customer demand to deliver higher-quality, cost-efficient software under tighter deadlines,” she concluded.
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