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Artificial Intelligence in software automation testing to improve testing efficiency, and accuracy and to keep pace with the increasing complexity of software applications. AI can be used to automate various testing activities such as:

• Test Case Generation: AI algorithms can be used to generate test cases automatically based on requirements, code structure, and usage patterns. This helps in reducing the effort required for manual test case creation.

• Test Data Generation: AI can be used to generate test data that covers a wide range of scenarios, including edge cases and negative scenarios.

• ·Test Case Prioritization: AI algorithms can analyze the test results and prioritize the test cases that are most likely to uncover bugs. This helps in reducing the time required for regression testing.

AI can also be used in combination with other technologies such as Machine Learning and Natural Language Processing to provide a more comprehensive solution for software automation testing. However, it's important to note that AI is not a silver bullet for software testing and still requires human oversight and judgment.

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