Test automation using Artificial Intelligence has become a buzz of phrase; with even large enterprises such as Google, Amazon talking about Artificial intelligence getting into their mainstream platforms. Despite the existence of Artificial intelligence for over a decade, we are seeing this buzz word used a lot nowadays, with numerous applications and platforms leveraging AI and ML elements. AI-based recommendation engines with the auto-correction features and Google search - suggestions based on recent searches were made classic examples about the usage of AI. The AI is already available, but making it available even for the Software Testing community as AI-powered/ enabled Automation tools & Platforms is crucial.

With the help of machine learning or pattern recognition technology, artificial intelligence is now more profitable than ever when it comes to testing and test automation. These innovative technologies allow the machine to primarily learn and better predict what is going to happen and then apply it to new data.

How Does This Benefit the Testing Community?

It would support the development of a pattern training that would help to ensure greater self-learning by computers, therefore, help free up the employees for other pursuits. By fostering machine learning and artificial intelligence, testers can allow computers to make predictions based on correlations between data points and then apply these predictions to new data to improve overall prediction accuracy.

As agile and DevOps become critical for software development, testers must advance beyond manual testing and traditional automation strategies towards AI/ML-based testing to enhance software quality and support self-healing test automation.