Strategy & Insights

New Snowflake Research Reveals How Healthcare Leaders Are Rapidly Adopting Agentic AI and Prioritizing Interoperability

A doctor and a nurse reviewing brain scans.

It’s a pivotal time for healthcare and public health organizations. Budgets and margins are shrinking, mandates — both government and internal — are broadening in scope to meet current challenges, and reimbursement rates are changing or in flux. Executives and line of business decision-makers across these industries are struggling with complex problems where data, technology and interoperability play a critical role in helping them tackle them head-on.  

Snowflake and Hakkoda partner to provide actionable AI intelligence

To get the latest insights on how these organizations are evolving their interoperability and AI strategy to meet today’s challenges, Snowflake and Hakkoda, an IBM Company, partnered to survey decision-makers across these sectors to provide actionable intelligence and learnings for leaders and stakeholders, as well as illuminate trends, shift perceptions and spark conversations, providing the material for thoughtful conversations. 

In total, 183 senior healthcare executives and managers across providers, payers, health systems, nonprofit health organizations and public health agencies were polled via an online survey managed by Fierce Healthcare. Their job titles ranged from CEO and director to program manager and partner, and all respondents resided in the United States.

Today, we released the findings from our research in our The Future of AI + Interoperability Report. It’s the second of its kind, following our 2023 survey about the state of interoperability in healthcare.  

A few highlights* from the report:

  • 85% of healthcare and public health agency leaders report that improving data sharing and interoperability is a higher priority today than it was two years ago, as organizations scale AI and strive to achieve operational efficiency and value-based care goals. 

  • The research findings also shine a light on the rapid pace of agentic and AI technology adoption across a variety of use cases, depending on the organization type. 

  • 77% of organizations have already invested or plan to invest in generative or agentic AI technologies, prioritizing high-impact use cases such as administrative workflow automation, clinical documentation and revenue cycle operations.

Get the full report findings now.

Healthcare and public health leaders expect measurable AI ROI

Additionally, the report highlights that healthcare and public health leaders expect measurable ROI from their AI investments. It’s clear that these industries are maturing in their AI adoption, moving from experimentation and pilots to operationalizing it at scale. As a result, decision-makers are placing greater emphasis on measurable productivity, efficiency and cost savings gains.

​​“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.”

“AI is moving rapidly into mission-critical healthcare workflows,” said Chris Puuri, Global Head of Healthcare and Life Sciences, Hakkoda, an IBM Company. “Organizations that address fragmentation and build interoperable data foundations will be the ones that translate AI investment into measurable efficiency, financial resilience and improved patient outcomes.”

Closing the AI-interoperability gap

The signals from the report are strong: the age of enterprisewide AI in healthcare and public health agencies is upon us and interoperability has never been more important. The findings also clearly demonstrate the critical challenge ahead for these two industries: closing the gap between the vision for AI and the current interoperability challenges to make this vision a reality. 

Get the report now.

*Note: Figures have been rounded for ease of presentation.

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