Hitachi Vantara / Zetaris Why is Ai Failing to Deliver Clinical and Operational Value
Harness the power of AI to improve patient outcomes, streamline operations, and ensure trust in every decision.
Despite massive investment, many healthcare organizations are struggling to turn AI into measurable clinical and operational impact. Models risk explainability, data quality remains inconsistent, and AI often fails to integrate into real-world care workflows.
Join a small group of healthcare and technology leaders for a virtual, peer-led roundtable exploring what's holding healthcare AI back - and what's required to make it trustworthy, scalable and clinically meaningful.
Focus Areas:
Data Fragmentation: With over 80% of healthcare data unstructured, how are organizations making it usable and governable for AI?
Security vs Data Quality: 54% of IT leaders prioritize security over data quality - how do you achieve both without sacrificing model accuracy or trust?
Infrastructure at Scale: Data volumes are expected to grow 122% by 2026 - are current systems ready to support AI?
Trust in AI Outputs: Only 33% of leaders trust AI accuracy - what's missing, and how do we close the gap?
Key Questions We'll Explore:
- Are your AI models explainable, auditable and trusted by clinicians?
- How do you ensure clinical-grade data quality when most healthcare data is unstructured?
- What does it take to embed AI into patient care workflows rather than keeping it siloed?
Join a candid, peer-level discussion - free from sales pitches - to learn how healthcare leaders are improving data quality, trust and real-world AI impact in clinical settings.
Request your spot
Participation is by registration only, to ensure a senior, peer-level conversation.