When these AI automation tools are tactically used by the team then proper fixes can be suggested for errors and huge amounts of data can be accurately handled. The rate of errors that are introduced are also gradually reduced.

Following are a few advantages of implementing AI in automation testing:

1. Solving errors: When the AI platform tests the software product or application then whenever there are bugs being identified, it immediately alerts the tester about the specific bugs or errors. There are specific ai automation tools that can be leveraged to identify bugs

2. Quality is improved: Not only is the testing process made faster and more efficient by the strategic use of AI platform, but, also the quality is improved by processing huge amounts of data at a time. This in turn helps in identifying anomalies and similar error trends.

3. Automation testing is carried out more productively: The overall scope and depth of tests can be increased by the tactical use of AI in test automation and also it in turn results in the overall improvement of software quality. Automated software testing can look into internal program states, repositories, locator values and data sets in order to ascertain whether the software is behaving as expected or not.
Right set of tests can be used through the tactical use of AI in automation testing activities. Testing efforts are optimized and test coverage is enhanced through the use of AI automation tools.