The “Safe Choice” Illusion: Rethinking Risk in AI-Powered Radiology Reporting

When radiology organizations evaluate their next reporting platform, established vendors can appear to be the safest option. But does familiarity actually reduce risk, or can it preserve technical limitations, fragmented workflows and barriers to innovation?

Join radiology leaders who have recently navigated reporting platform evaluations as they discuss how they assessed implementation readiness, ecosystem fit, radiologist experience, vendor support, architecture and long-term viability. 

Hear how they identified technical and operational requirements, pressure-tested vendor claims and evaluated the service and support models that can enable a platform to deliver in practice — not just on paper. Learn which assumptions they challenged and how they distinguished a familiar choice from the right choice.

Attendees will leave with a practical framework for evaluating AI-powered reporting solutions and asking more revealing questions of prospective technology partners.

Objectives:

• Identify the clinical, operational, technical and strategic criteria for an enterprise reporting-platform evaluation.
• Recognize hidden risks that may accompany an incumbent or seemingly “safe” technology decision.
• Apply questions used by peer organizations to assess implementation readiness, ecosystem fit, vendor support, innovation velocity and long-term platform viability.
• Distinguish AI claims from evidence of meaningful, sustainable workflow improvement.

Speakers: 

• Tessa S. Cook MD, PhD, Associate Professor and Vice Chair of Informatics, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania‍
• Charles Q. Li, MD, Neuroradiologist, Allegheny Health Network, Physician Informaticist, Digital Transformation Office, Allegheny Health Network, Associate Professor, Department of Radiologic Sciences, Drexel University College of Medicine‍
• Lisa Soltz, Vice President, Implementations, Rad AI‍
• Rishi Seth, MD, Chief Medical Information Officer, Rad AI (Moderator)

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