Chuck Podesta, CIO, Renown Health, is steering his organization toward an interoperability model that leans on AI “orchestration” rather than large, centralized data repositories—while pairing that shift with tougher data governance and a stronger resilience posture. The three-hospital system in Reno, Nev., which includes an 800-bed regional facility, a community hospital, a children’s hospital and a health plan, is also preparing an AI Innovation Center to accelerate workforce productivity and evaluate clinical tools.

From his vantage point, Podesta sees steady movement but not sufficient progress in connecting health data across vendors and care settings. “We’re still very far behind where we need to be, although with some of the new technologies, especially around AI, there is hope now,” he said, noting that federal rules and vendor advances—such as single-pane patient access features—are nudging the market forward.

He argues that patients’ expectations are setting the bar: they want longitudinal records that travel with them across states and providers. Against that backdrop, he views current cross-system exchange as incomplete and often brittle, even when organizations share the same core EHR. The imperative, he said, is to deliver a unified experience without forcing clinicians or consumers to assemble it themselves.

From Data Lakes to Orchestration AI

Within data strategy, Podesta describes two schools of thought. One approach consolidates information from EHR, ERP and ancillary systems into governed platforms such as data warehouses or cloud analytic environments. That method, he said, can yield trustworthy operational dashboards and support research, but it is expensive and slow to adapt.



He is increasingly focused on a second path: leaving data in place and using intelligent agents to retrieve it on demand. “Orchestration AI leaves the data where it is and uses AI to fetch it, which can be faster and cheaper—as long as governance is sound,” he said. In this model, standards and APIs still matter, but the emphasis shifts to secure access, provenance and auditability at the source, rather than repeated copying into new stores.

Governance, Talent and the Citizen Layer

At Renown, Podesta plans to launch an AI Innovation Center to review EHR-embedded capabilities, enforce data and AI governance, and promote enterprise productivity tools to the full workforce. The near-term goal, he said, is to reclaim time by automating repetitive administrative tasks across departments.

He wants employees closest to the work to help lead that change. “Look at all the mundane tasks you do and figure out how to automate those—not to replace you, but so you can do the work that only you can do,” he said. Early internal analysis showed surprisingly broad, grassroots experimentation with generative tools; thousands of staff interactions with public systems prompted Renown to pursue enterprise licensing and guardrails to protect sensitive information while channeling energy into sanctioned uses.

Podesta also points to “evangelists” already on the payroll—clinicians, analysts and operators who write effective prompts, build lightweight workflows and teach peers. By convening these practitioners inside a formal program, he expects faster diffusion of practical use cases without heavy reliance on consultants or large bespoke builds.

Resilience, Outages and Multi-Cloud Plans

As AI and ambient documentation embed deeper into everyday care, Podesta emphasizes that resilience must advance in step. He expects the industry’s security posture to tilt from detection-and-response toward proven recovery capabilities that keep clinical and business systems available under duress. Recent hyperscale interruptions underscored for him the operational risk of single-cloud concentration and the need to design for failover—between clouds and between cloud and on-premises resources.