Shree Periakaruppan of ACR explains how trust, AI governance, and data platforms are helping radiology teams improve speed, accuracy, and care.
In a field where AI is already becoming part of daily clinical work, Shree Periakaruppan, Head of Data Engineering and Analytics at American College of Radiology, brings a practical and grounded view of what makes transformation successful. As Head of Data Engineering & Analytics at the American College of Radiology (ACR), Shree focuses on what matters first: trusted data platforms, strong governance, clear workflows, and real outcomes not just technical performance.
In her conversation on The Executive Outlook, Shree explains why the biggest challenge in AI is often trust, not technology. She shares how radiology has advanced because of strong data standards, why governance and continuous monitoring are critical, and why AI value should always tie back to patient care, efficiency, cost, or satisfaction. She also highlights the red flags leaders should watch for, from unclear ROI to poor workflow integration.
For Shree, successful AI in radiology is not about replacing people or chasing hype. It is about reducing friction, supporting radiologists, improving care faster, and building systems that scale with clarity, purpose, and trust.
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