The best image annotation tools offer features such as reducing manual labeling time, improving label accuracy and consistency, supporting diverse data types, and offering collaboration, QA, and integration with the ML pipeline. For large-scale enterprise teams working with complex datasets, especially those involving medical imagery, video, or multimodal inputs, Encord stands out in 2025 due to its comprehensive annotation platform, support for multimodal annotation, and production-level MLOps integration. Other top tools include V7, which offers fast AI-assisted annotation with an intuitive user interface, CVAT, a top open-source image annotation tool designed for technical teams, Labelbox, which combines data labeling, model integration, and analytics under one roof, Roboflow, popular among developers and ML researchers, and Lightly, which focuses on optimizing training datasets. When choosing the best tool, consider factors such as data modalities supported, automation and AI assistance, security and compliance, custom workflows and QA, model evaluation integration, API access and toolchain fit, and project size and domain.