AI & ML in testing -- how relevant are these?

Before understanding the relevance of artificial intelligence in quality assurance and testing, it is important to understand the difference between AI and ML. Machine Learning is a subclass of AI, while AI is any software code that makes the computer do smart things, also taking over some tasks from humans that are repetitive and menial. Machine Learning, on the other hand, consists of deep learning techniques that help these robots learn to get smart. The bots learn from human interactions and, in the process, get smart to replace human beings and carry out specified tasks. For example, robots in RPA automation are usually assigned to back-office tasks in industries like healthcare, banking, etc., that need to be done consistently over time with minimal human intervention. Or, some tasks are high-volume, such as claim processing in the insurance industry, or are time-consuming have AI-ML-powered robots handling the work.