With recent trends in automated and digitized data acquisition, and deep learning algorithms, AI and ML applications are growing rapidly in fields that were initially to be solely managed by human expertise. By introducing AI and ML into automated testing tools, QA teams are able to address many of the conventional problems of automated software testing. According to a report by Digital Transformation Trends, 80% of businesses admitted that AI and ML improved their productivity, brand value, and ROI. And now, these two components have become an integral part of the software testing life cycle.
March 20, 2019Automation has given the quality assurance process a much-needed injection of speed. By taking responsibility for every aspect of the QA phase out of the hands of manual testers and turning it over to efficient computer test scripts, automation allows us to: Achieve Better Quality Release Faster Get More QA Coverage