The Clinical Data Gap: Why Healthcare AI Stalls at Proof-of-Concept

​A Data Foundations for Healthcare AI session, in partnership with Perform by AI

​Healthcare AI pilots in the GCC rarely fail because the models don't work but because the data underneath them was never ready to support them. Siloed EHRs, inconsistent clinical coding, and patient records scattered across systems that were never built to talk to each other.

​This session breaks down exactly where healthcare organisations get stuck between a promising proof-of-concept and a system clinicians can actually trust and use.

​You'll leave with:

• ​A clear picture of the clinical interoperability barriers unique to GCC healthcare systems

• ​A practical way to assess whether your data environment is actually ready for AI before you invest further

• ​What separates a healthcare data readiness assessment from a standard enterprise one, and why that distinction matters

​Who should attend: Healthcare CIOs, CMIOs, digital health leads, and anyone responsible for AI initiatives that keep stalling before they reach patients.

​This is the first in a three-part series on building the data foundations healthcare AI actually needs.