Mouneer Odeh, VP, Chief Data and AI Officer, Cedars-Sinai, is positioning the organization to harness fast-maturing AI while keeping clinical workflow, governance, and scale at the center of decision-making. In a wide-ranging discussion, he traced his path from advanced analytics to enterprise AI, outlined the role of platform vendors versus best-of-breed tools and internal builds, and described how non-IT staff are being trained to co-create agents grounded in Cedars-Sinai policies.
This interview was conducted as part of our recently published
Special Report on AI
Framing data and AI as a single continuum, Odeh said the mission is to accelerate research and discovery, improve patient care, and drive operational efficiency through “data-driven intelligence.” He argued that data quality is the critical differentiator between helpful and hazardous systems, adding, “the difference between AI that behaves like a really good graduate student or a fantastic assistant, and AI that behaves like your drunk friend is quality of the data.” He also emphasized tight linkages with clinical informatics, research leadership, applications, infrastructure, and security so that models can be deployed reliably inside real workflows.
Within the C-suite, Odeh partners closely with the chief health informatics officer and the chief health AI research officer, while maintaining deep ties to applications, technology, and security leaders. He said that collaboration matters because AI is increasingly delivered through applications and agentic interfaces. In his view, bridging operations and technology—while anchoring everything in governance—keeps initiatives focused on adoption and measurable outcomes.
Platform, Best-of-Breed, and In-House: Finding the Mix
At Cedars-Sinai, the AI portfolio breaks roughly into thirds across internal development, platform-delivered capabilities (notably in the EHR), and best-of-breed solutions. Odeh said platform vendors are racing to embed agentic capabilities where clinicians already work, which can compress time to value. He pointed to the EHR’s evolving strategy and observed, “You could almost say that they’re reinventing themselves from a software company to an AI company.” He added that Cedars-Sinai expects platform share to grow as vendor offerings mature, but only where they meet clinical and operational requirements at scale.
To avoid lock-in, Odeh drew a clear line between simplification and dependency. He stressed that Cedars-Sinai will continue to pursue innovative point solutions and internal builds where they offer distinctive value, workflow fit, or earlier availability than platforms can provide. In his words, “I don’t think we’ll ever be all in on just going with the platform play.” He said that whatever the source—platform, best-of-breed, or internal—the output must flow into clinician workflows so that it “feels” native; otherwise, good models will go unused.
From Projects to Products: Governing at Scale
Across deployments, Odeh said implementation now determines impact. He pointed to the shift from one-and-done project management toward product management that sustains engagement, measures use, and iterates based on observed behavior. He argued that customer-relationship skills inside IT are becoming as important as technical depth: without trust and responsiveness, organizations lose momentum, and opportunities to expand successful pilots stall.
He described governance as a practical enabler; multidisciplinary bodies decide who sees what, what actions are expected, how results are interpreted, and when a model is “publish-ready.” He added that informaticists are essential to this work, translating between clinical reality and technical integration so models land in the right place, with the right users,
