The Agent Advantage: Radiology Ops in the Era of Agentic AI

AI agents can reason across inputs, execute multi-step tasks and coordinate across clinical systems — not as point solutions, but as end-to-end operators with defined guardrails and structured human escalation paths. The result is a different operational model: workflows that run without manual handoffs, staff focused on exceptions rather than routine coordination and administrative overhead reduced at scale. 

That overhead is most acute in radiology, where departments spend over 25% of their operating budget on administrative work running alongside the scan, from requisition intake and scheduling coordination to inbound call management, patient and provider communications, and prior imaging retrieval. Most of it is still managed manually. 

In this session, Rishi Nayyar, Co-Founder and CEO of PocketHealth, walks through the technology enabling AI agents in radiology: document intelligence, system automation playbooks, and multi-channel communication agents. He’ll cover how agents are orchestrated into reliable end-to-end processes, and what it takes to make them trustworthy in a clinical environment where both patient safety and operational performance are on the line. 

Objectives

• Describe how agentic AI differs from traditional software and why that distinction matters for radiology operations. 
• Discuss how document intelligence, system automation, and multi-channel communication agents work together to run end-to-end radiology workflows, and what the operational outcomes look like in practice. 
• Explore what responsible deployment looks like: the accuracy standards, failure handling, and governance controls that keep agents under human oversight. 

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).