What is Data Annotation, and why is it important for AI and machine learning?

Data annotation is the process of labeling or tagging data—such as images, text, audio, and video—so that machine learning models can understand and learn from it. For example, images can be labeled to identify objects, while text can be categorized according to sentiment or intent. High-quality annotation helps improve the accuracy and reliability of AI models. Businesses that need large volumes of accurately labeled datasets can use professional Data Annotation Services to streamline the process and maintain consistent labeling standards.