Use Cases of Artificial Intelligence in Software Testing

2 min readJun 12, 2022


Software testing, in simple words, is the process of finding errors in the developed product. It checks whether the real outcomes can match expected results, as well as aids in the identification of defects, missing requirements, or gaps. Artificial Intelligence is being used in software testing to automate the process and deliver quality results for ensuring a superior customer experience.

Here are some use cases of AI in Software testing –

  • Visual Validation — Visual bugs can be identified by pattern recognition and image recognition mechanisms of AI. Machine Learning based tools can even detect minor anomalies.
  • Improved Accuracy — In the case of manual testing there might be room for mistakes due to repetitive work, negligence fatigue, etc. But AI helps in removing these human- prone mistakes and produces more effective results.
  • Better Test Coverage — AI widens the scope of testing. It can check data, index and internal programs efficiently. All major and minor aspects of a program can be analyzed in the process of automatic testing effectively.
  • Reduces cost and time — Manually, software testing takes a lot of time and energy. Automating this process gives results much more quickly. The software just needs to be repeated whenever there is a new code or a change in the previous code. This also reduces the cost of hiring software testers.

· Automated API Generation — AI tools can be used to help take the complexity out of API testing by converting manual tests into automated API tests. This will provide quicker test results and help to speed up the feedback loop and catch issues faster.

· Automatically Writing Test Cases — AI tools can now be used to automatically write test cases; they crawl and collect enough data that is then useful in training ML models.





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