The adoption of artificial intelligence (AI) in radiology is accelerating, offering powerful solutions to address the growing volume and efficiency challenges faced by radiologists. While AI demonstrates significant value in automating repetitive tasks and streamlining workflows, concerns around accuracy and medicolegal liability remain barriers to widespread trust and adoption. To bridge this gap, the American College of Radiology (ACR) has pioneered governance frameworks and registries that promote safe, clinically effective AI integration. Central to this effort is Assess-AI, the first national registry for monitoring AI algorithm performance using real-world clinical data. Leveraging large language models (LLMs), Assess-AI extracts structured insights from radiology reports to generate “surrogate ground truth” for continuous performance benchmarking and national comparisons. This presentation explores the governance strategies, safeguards, and scalable monitoring methods that ensure AI adoption remains clinically relevant, safe, and trusted—empowering radiologists to focus on high-impact decision-making while advancing patient-centered care. 

Speaker: Shree Periakaruppan, Head of Data Strategy, Data Engineering, Analytics and BI, American College of Radiology

Shree Periakaruppan is a change agent and data-driven leader with 25+ years of experience transforming organizations through strategy, analytics, and AI. As Head of Data at the American College of Radiology (ACR), she established and scaled the enterprise data function, positioning data as a strategic asset. She spearheaded the implementation of ACR’s Data Lake and created BEACON (Backbone for Enterprise Analytics, Curation, Orchestration, and Normalization), a modern platform powering ACR’s data products. Shree also advanced large language model use for extracting structured findings from unstructured reports, enabling scalable AI validation. Her team pioneered metadata-based prompt management for Assess-AI, the first AI quality registry in radiology. Beyond technology, she demonstrated exceptional financial leadership, securing grants and partnerships to deliver zero-cost MVPs. A thought leader in governance, inclusion, and responsible AI, Shree has spoken at AWS ReInvent, Women in Data, and WLDA, and is a Carnegie Mellon Chief Data & AI Officer alum.