AI in radiology: from insights to impact – key takeaways for health systems
- By Philips
- March 10 2026
- Duration 42: 42
Join our on-demand webinar featuring Philips experts and guest panelists as they explore how AI can reduce costs, accelerate diagnosis, streamline workflows and enhance image quality – ultimately helping to strengthen trust and confidence among care teams and patients.
At-a-glance:
- A look at how radiology teams can justify, integrate and scale AI – covering financial value, workflow redesign and trust-building across the enterprise.
- Philips experts and healthcare leaders share candid insights, use cases and lessons learned from implementing AI in diagnostic imaging today.
- Learn why governance, end‑to‑end workflow reinvention and cross‑department collaboration are critical to reducing costs, speeding diagnosis and improving confidence in care.
How should health systems implement AI in imaging? For AI adoption to be successful, it requires significant collaboration between key stakeholders to come together with a desire to streamline processes, mitigate change, enhance clinical conversations and transform point of care across the entire organization.
We welcome you to listen to our Philips experts, Heather Chait, AI Ecosystem Lead; Sonia Tripathi, Head of Marketing, Precision Diagnosis; and Wilson To, Head of Strategy, Informatics, alongside our customers which includes Dr. Jeffrey Miller, Chief of Radiology at Phoenix Children’s Hospital, and Nickki Hardin, Healthcare Director at Huron Consulting Group.
The promise of AI lies in its ability to intelligently and rapidly consolidate information for faster diagnoses across imaging systems, adding more clarity for pathology and giving clinicians a comprehensive view of patient data so they can provide the right care.
Dr. Heather Chait
AI Ecosystem Lead
Philips
We’re not thinking of AI in terms of point solutions anymore. We’re thinking about how that piece of AI impacts the overall enterprise. As Wilson To says, "Radiologists don't want another AI model bolted onto an existing workflow – you’re just adding more work. The end-to-end reinvention of workflow is what {our} customers are now asking for."
Learn more in our white paper
Be sure to learn more and read our white paper, "The state of AI in diagnostic imaging: readiness, resources and risk tolerance," where you will hear from other radiology administrators across large and small hospital, as well as our experts give practical steps to implement AI into your organization.
Featuring
Dr. Heather Chait
AI Clinical Ecosystem Lead
Philips, United States
Sonia Tripathi
Head of Marketing, Precision Diagnosis
Philips, United States
Wilson To
Head of Strategy Enterprise Informatics
Philips, United States
The state of AI in diagnostic imaging: readiness, resources and risk tolerance
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Disclaimer
The opinions and clinical experiences presented herein are specific to the featured topics and are not linked to any specific patient and are for information purposes only. The medical experience(s) derived from these topics may not be predictive of all patients. Individual results may vary depending on a variety of patient-specific attributes and related factors. Nothing in this article is intended to provide specific medical advice or to take the place of written law or regulations.