AutoML tools significantly speed up model development by automating time-consuming tasks like data preprocessing, feature selection, model selection, and hyperparameter tuning. These tools reduce the need for extensive manual intervention, allowing data professionals to focus more on insights and decision-making. By streamlining the workflow, AutoML enables faster prototyping and testing of various algorithms, making it easier to find optimal models for a given problem. This not only improves efficiency but also ensures consistent performance across different datasets. If you want to explore these concepts further, consider enrolling in a Machine learning course.