AI-driven test automation is revolutionizing the software testing industry by using artificial intelligence to automate the development and execution of tests, which enhances performance, accuracy, quality, and reduces time-to-market and costs. However, it raises significant ethical concerns such as bias, privacy, transparency, accountability, and the impact on human testers. This technology requires careful consideration of ethical standards and best practices, including ensuring diverse and unbiased data, maintaining transparency, securing privacy, and involving human oversight to mitigate potential biases and negative outcomes. Real-world examples, like biased AI recruitment tools, highlight the risks of unchecked AI systems. To address these challenges, it is crucial to establish ethical guidelines, conduct regular audits, and provide training on ethical issues. Implementing these practices helps ensure AI-driven test automation is used responsibly, benefiting society while adhering to fundamental ethical principles.