This article discusses the enhancement of software testing methods through the use of Artificial Intelligence (AI). It highlights the limitations of traditional manual and automated testing approaches and explores how AI technologies—such as machine learning, neural networks, and natural language processing—can improve efficiency, accuracy, and adaptability in the testing process. The study emphasizes the potential of AI-driven systems to automate test generation, predict defects, and analyze test results intelligently, thereby reducing human effort and improving software quality assurance.

Artificial Intelligence, Software Testing, Machine Learning, Test Automation, Neural Networks, Defect Prediction, Quality Assurance.

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