Back in 2023, only 15% of businesses had adopted AI-augmented software testing tools. By 2027, that number is expected to leap to 80%. The reason behind this rapid adoption is clear. The complexity of modern software and products is skyrocketing, and with it, the risks associated with quality assurance (QA). These risks, whether it’s a compliance oversight in healthcare, a security flaw in financial systems, or a software bug that disrupts users, can cost more than money. They can erode trust and credibility.

Testing automation is becoming the go-to solution to mitigate these risks. This includes everything from regression testing to AI-driven anomaly detection. At its core, automation in QA refers to the use of software tools and scripts to execute repetitive test cases, identify defects, and validate functionality without manual intervention. Beyond saving time, automation ensures consistency, scales effortlessly, and catches problems early. It’s not just a technical upgrade; it’s a fundamental shift in how organizations approach software QA.

 …