Guardrails for Growth: AI Governance in Medical Imaging

As AI becomes a cornerstone of modern medical imaging, effective governance is no longer optional—it’s mission-critical. This session dives into the core elements of enterprise AI governance, including bias mitigation, safety oversight, and transparency across clinical workflows. Through real-world examples and expert insights, you’ll learn how to build and sustain a governance model that balances innovation with responsibility. 

Speakers will outline practical approaches to forming multidisciplinary oversight teams, crafting internal policies, and aligning with evolving regulatory and ethical standards. Whether you’re launching your first AI project or scaling across departments, you’ll gain actionable tools for managing AI safely and effectively in imaging environments.    

Objectives   

• Identify the foundational elements of an enterprise AI governance model tailored for medical imaging. 
• Differentiate between regulatory, institutional, and ethical responsibilities in the deployment of AI tools. 
• Implement practical strategies to oversee, evaluate, and adapt the use of AI in clinical imaging workflows. 

Resources     

• Effective Strategies for Post-Production Monitoring of AI Algorithms in Radiology
• Core Essentials Live: Troubleshooting Tips & Tricks

CE Credit     

The Society for Imaging Informatics in Medicine has approved this activity for 1.0 hours of SIIM IIP Credits towards certification and re-certification by the American Board of Imaging Informatics (ABII).