Systems | Development | Analytics | API | Testing

Discover the most powerful updates in Katalon Studio 10.2 and TrueTest in this comprehensive product webinar. Join Lucio, Mai Le (Director of Product Management), and Philip Becker (Sr. Product Manager) as they walk you through Katalon’s newest capabilities, including enhanced AI-powered test generation, smarter StudioAssist context handling, improved security for global variables, and multi-environment data tracking. Learn how TrueTest helps QA teams close testing gaps and streamline automation with minimal manual effort.

Manual testing is still dominating software testing workflows in 2025 — but is it holding teams back? In this quick insight from Katalon’s State of Software Quality Report 2025, Senior Product Manager Mai highlights the surprising stat that over 80% of QA teams still rely heavily on manual testing, with 26% spending more than 75% of their time on it. While manual testing remains important, it can also become a bottleneck. Discover what’s driving this dependency and how modern practices and tools can accelerate efficiency.

Did you know that 77% of QA professionals are already using AI in their testing practices? In this year’s State of Software Quality Report 2025, Katalon asked QA teams about the role of AI in their workflows, and the results are eye-opening. This short video reveals one of the biggest takeaways: how widespread AI adoption has become in the quality space, and why it matters for the future of testing.

Did you know that 26% of QA teams still describe their testing processes as very informal or unstructured—with minimal automation? This stat from Katalon’s State of Software Quality Report 2025 underscores a major opportunity for growth in QA maturity. Relying primarily on manual testing not only limits efficiency but also affects the consistency and scalability of quality assurance efforts.

AI is transforming testing—but not without its challenges. According to the State of Software Quality Report 2025, 46% of testers cite the lack of skilled personnel or the steep learning curve as major barriers to adopting AI in software testing. In this insightful message, we highlight one of the most pressing issues in the QA space: while AI has immense potential to drive efficiency and quality, teams are struggling to fully capitalize on it due to limited expertise.