Ensuring data quality involves several steps: collecting relevant and diverse datasets, cleaning data to remove inconsistencies and noise, and annotating data to make it usable for training AI models. High-quality data is crucial for training accurate and reliable AI models. Techniques like data augmentation can also enhance the dataset.