Testlio blog

Engineering teams now move faster than ever. In 2025, they build smarter, ship quicker, and rely heavily on AI tools and continuous delivery pipelines. 

AI failures rarely look like crashes. More often, they appear as confident but incorrect answers, subtle bias, or culturally inappropriate responses.

Did you know the global digital health market is on track to surpass $660 billion by the end of 2025? That’s no surprise, considering how healthcare apps have become indispensable in our daily lives. 

We are thrilled to share that Testlio has been awarded the ISO/IEC 27001 certification for our information security management system. 

Testing AI-powered applications is one of the top priorities for teams deploying machine learning systems at scale. As AI becomes embedded in everyday tools, its behavior becomes harder to control.

This article serves as a step-by-step guide for creating a test automation strategy. It will help you answer why, when, and how to perform automated testing, so you can not only implement it but also overcome its challenges. 

AI doesn’t just fail with bugs. It fails in silence, in bias, and in behavior. That’s why traditional QA won’t cut it anymore.

As software systems get increasingly complex every day, the challenges of effective testing also escalate. Software testing involves handling large datasets, complex workflows, and shorter release cycles. 

Finding a bug is one thing, but documenting it is just as important, if not more so.