Snowflake Research Reveals 85% of Healthcare Leaders View Interoperability as Foundational to Scaling AI

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Findings underscore a turning point in AI adoption in healthcare, where achieving measurable efficiency and cost savings with AI depends on breaking down data silos across fragmented systems

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MENLO PARK, Calif. — Snowflake (NYSE: SNOW), the AI Data Cloud company, in collaboration with Hakkoda, an IBM company, today released new research revealing that as healthcare organizations and public health agencies scale AI beyond pilot programs, improving interoperability is becoming foundational to broader AI deployment. With 77% of organizations investing in generative or agentic AI, 85% of leaders report that improving interoperability — the ability to securely share and use data across clinical, administrative, and financial systems — has become a higher priority over the past two years as they work to scale AI.

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​​“Across healthcare, AI is moving into operational environments and leaders are holding it to a higher standard,” said Jesse Cugliotta, Global Head of Healthcare and Life Sciences, Snowflake. “Organizations want measurable efficiency gains, workforce relief, and better patient outcomes. That only happens when clinical, financial, and operational data can move securely and seamlessly across systems. Interoperability is no longer a compliance checkbox — it’s the engine that makes scalable AI possible.”

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AI Investment Expands Across Core Healthcare Workflows

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AI investment is accelerating across healthcare organizations, with 77% of respondents reporting they have already invested or plan to invest in generative or agentic AI technologies. Organizations are prioritizing high-impact use cases such as administrative workflow automation (60%), clinical documentation and scribing (50%), and revenue cycle operations, including billing and prior authorization (47%).

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These priorities reflect the mounting pressure on healthcare organizations to reduce administrative burdens and support clinicians, enabling more time for direct patient care. By automating these workflows, organizations aim to increase revenue cycle efficiency amid persistent workforce constraints and reimbursement complexity. As a result, AI investment is shifting toward practical applications shaped by internal priorities.

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Interoperability Becomes Critical as AI Scales

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As AI initiatives expand, 85% of healthcare leaders report that improving data sharing and interoperability has become a higher priority compared to two years ago. Operational efficiency and decision making (74%), improving the patient experience (71%), and helping drive value-based care (64%) were cited as the primary drivers behind increased focus on interoperability.

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This shift reflects a broader change in how healthcare organizations view interoperability — not only as a compliance requirement but as a strategic enabler of scalable AI initiatives. Compared to Snowflake’s 2023 survey, where improving patient care and coordination ranked as the top driver, operational efficiency and decision-making now lead as primary motivators for interoperability. While internal data sharing is already widespread at 82%, leaders acknowledge that connecting systems across departments and partners will be critical to expanding AI across the organization.

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Leaders Expect Measurable Returns

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Healthcare organizations increasingly expect AI investments to deliver quantifiable results. Fifty-two percent of respondents anticipate time savings between 10% and 50%, while 42% expect moderate cost savings as AI initiatives mature.

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These findings reflect a shift toward evaluating AI through a more operational lens, with leaders placing greater emphasis on measurable productivity and efficiency gains. Respondents also cite mature data governance as an important contributor to AI effectiveness, underscoring the role of trusted, connected data in supporting scalable AI.

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“AI is rapidly becoming embedded in mission-critical healthcare workflows,” said Chris Puuri, Global Head of Healthcare and Life Sciences at Hakkoda, an IBM Company. “The organizations that will see returns are the ones tackling data fragmentation head-on and building interoperable foundations. That’s what turns AI investment into measurable efficiency, financial strength, and better patient outcomes.”

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Methodology

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The 2026 Future of AI + Interoperability in Healthcare Report is based on responses from 183 US senior healthcare leaders across providers, payers, health systems, non-profit health organizations and public health agencies. The online survey was conducted in collaboration with Hakkoda, an IBM Company, between October 8, 2025 and January 12, 2026. Figures in this release have been rounded for ease of presentation.