Building computer vision models from scratch is costly and resource-intensive. The emergence of foundation models for vision — large-scale AI models trained on extensive data sets — is shifting computer vision toward more adaptable and scalable solutions. These models can perform tasks like image classification, object detection, and image captioning with minimal additional training. This report guides technology practitioners on what the benefits of AI foundation models for vision are, how to overcome the associated challenges, and how to leverage these models systematically.