Beyond AI Models: Why Infrastructure Will Define the Next Decade of Radiology

AI is reshaping radiology, but not in the way most hospitals expect. While attention often centers on which AI model to choose, the more critical question is often overlooked: how will you manage AI across departments, vendors, and clinical workflows—now and in the future?

What makes this even more urgent is the fact that AI itself is changing. The field is shifting beyond traditional point solutions toward large language models, foundation models, and multimodal architectures. Each brings new promise, but also new complexity in how they are deployed, integrated, and governed.

This webinar uncovers the missing piece in many hospital strategies: infrastructure.
We’ll explain the difference between AI models, marketplaces, and infrastructure platforms, and why only one of them can support sustainable, system-wide impact.

Whether you're just beginning with AI or facing integration challenges, this session will help you reframe your approach.

Because the platform you choose today will define what AI can deliver tomorrow.

Why the next wave of AI models demands more from your infrastructure
Discover how narrow models, LLMs, foundation models, and research prototypes are converging—and what your systems need to support them all.

What separates marketplaces from true infrastructure platforms
Understand the trade-offs between access and integration, and learn what hospitals should demand across governance, routing, data standardization, and scalability.

The critical questions leaders must ask before scaling AI
From deployment logistics to vendor neutrality and performance monitoring, get a practical checklist for evaluating whether your AI plans are built to last.