The process of getting AI models approved by the FDA is complex and requires careful attention to data quality, security, and regulatory compliance, especially in healthcare applications like medical imaging. The FDA has been increasingly approving AI and machine learning algorithms, with a significant rise since 2019, primarily in radiology due to the abundance of image-based data. While many AI tools used in healthcare do not require FDA approval, those that do must adhere to rigorous standards, including FDA-compliant datasets, expert data annotation, and robust audit trails. The FDA has modernized its processes through its Digital Health Center of Excellence to handle the growing number of submissions, although only a fraction of AI tools in healthcare currently undergo FDA review. Under the 21st Century Cures Act, some AI tools are exempt from approval if they meet specific criteria, allowing healthcare providers to independently verify recommendations without relying solely on the AI output. The article highlights the importance of understanding whether FDA approval is necessary for specific AI healthcare models, which can save significant time and resources.