QASource Blog

How AI Improves Automated Testing Services

From the early robotics of the 1950s to the advanced, algorithm-driven machine learning of today, AI has come a long way in a short amount of time. Though AI is still relatively young, QASource has found that AI's current and potential value to automated testing is massive. With the increasing complexity of applications, the lightning-fast speed of the software development lifecycle, and the highly competitive time to market across industries, engineers will take all the help they can get, whether it be from machines or other humans.

So, why exactly is AI beneficial to automated testing services? Put simply, it allows the machine to learn and understand environments, perform “intelligent” actions, and improve itself automatically.

1

Written by QA Experts

QASource Blog, for executives and engineers, shares QA strategies, methodologies, and new ideas to inform and help effectively deliver quality products, websites, and applications.

Authors

Our bloggers are the test management experts at QASource. They are executives, QA managers, team leads, and testing practitioners. Their combined experience exceeds 100 years and they know how to optimize QA efforts in a variety of industries, domains, tools, and technologies.

Popular Posts