Healthcare AI is only as trustworthy as the data behind it.
In this episode of The Beat's AI at HLTH series, host Sandy Vance talks with Steve Fanning and Max Drown of Infor about why interoperability, data quality, and governance are essential to successful AI adoption.
They explore how Infor Cloverleaf helps organizations modernize HL7 integrations, adopt FHIR, and connect clinical and operational data. Steve also shares a real-world example of how inaccurate patient information can undermine an AI initiative.
The takeaway: Before healthcare organizations scale AI, they need to make sure their data is connected, accurate, and secure.
In this episode, they talk about:
- Why healthcare AI initiatives struggle when underlying data isn't accurate or secure
- How interoperability creates the foundation for trustworthy AI
- Why health systems should think beyond traditional point-to-point HL7 interfaces
- How FHIR can support more structured, accessible, and usable healthcare data
- How Infor Cloverleaf supports integration modernization and data normalization
- Why connecting clinical, financial, supply chain and operational data matters
- What a real-world data duplication problem reveals about AI readiness
- How CIOs can modernize existing infrastructure without compromising governance
- Why successful AI should transform workflows, not simply automate inefficient processes
A Little About Max and Steve:
Max Drown is Director of Product Management at Infor, specializing in Cloverleaf and healthcare interoperability. With extensive experience developing and implementing integration solutions for hospitals and healthcare providers, he focuses on modernizing HL7 interfaces, supporting FHIR adoption, and improving data readiness for AI.
Steve Fanning leads healthcare industry strategy at Infor, where he has spent more than a decade helping healthcare organizations modernize enterprise systems and prepare for emerging technologies. His work focuses on connecting clinical and operational data, improving interoperability and helping health systems build a foundation for responsible AI adoption.
