The high prevalence of thyroid nodules combined with the generally indolent growth of thyroid cancer present a challenge for optimal patient care. Risk classification models based on US features have been created by multiple professional societies, including the American College of Radiology (ACR), which published the Thyroid Imaging Reporting and Data System (TI-RADS) in 2017. ACR TI-RADS uses a standardized lexicon for assessment of thyroid nodules to generate a numeric scoring of features, designate categories of relative probability of benignity or malignancy, and provide management recommendations, with the aim of reducing unnecessary biopsies and excessive surveillance. Adopting ACR TI-RADS may require practice-level changes involving image acquisition and workflow, interpretation, and reporting. Significant resources should be devoted to educating sonographers and radiologists to accurately recognize features that contribute to the scoring of a nodule. Following a system that uses approved terminology generates reproducible and relevant reports while providing clarity of language and preventing misinterpretation. Comprehensive documentation facilitates quality improvement efforts. It also creates opportunities for outcome data and other performance metrics to be integrated with research. The authors review ACR TI-RADS, describe challenges and potential solutions related to its implementation based on their experiences, and highlight possible future directions in its evolution. ©RSNA, 2019 See discussion on this article by Hoang.