What You Should Know:
- The Milestone: Snowflake and Hakkoda have released “The Future of AI + Interoperability in Healthcare” report, surveying 183 senior healthcare leaders. The central finding is that scaling AI beyond isolated pilot programs requires a massive upgrade in data sharing capabilities.
- The Adoption Curve: AI investment is accelerating rapidly, with 77% of healthcare organizations reporting they have already invested or plan to invest in generative or agentic AI technologies. Furthermore, 64.5% have either adopted, are experimenting with, or plan to implement agentic AI within the next 12 months.
- The Interoperability Pivot: Driven by the need for scalable AI, 84.7% of healthcare decision-makers rate interoperability as a higher priority today than it was one to two years ago. Operational efficiency is now the number one driver for this data sharing.
- The Core Use Cases: Rather than focusing purely on clinical diagnostics, organizations are pointing AI at the back office. The top agentic AI use cases are streamlining administrative workflows (59.56%), clinical documentation (49.73%), and revenue cycle operations like billing and prior authorizations (46.99%).
- The ROI Expectations: Leaders are increasingly evaluating AI through a strict operational lens. Over half of respondents (52.46%) anticipate time savings between 10% and 50%, and 41.53% expect moderate cost savings as their AI initiatives mature.
Targeting the Back Office
According to a new research report released by Snowflake and Hakkoda, which surveyed 183 US senior healthcare leaders, the industry has reached a critical inflection point. With 77% of organizations actively investing in AI, a staggering 84.7% of executives report that improving interoperability and data sharing is a higher priority today than it was just two years ago. While much of the media focuses on futuristic diagnostic algorithms, the actual buyers are focused on administrative survival.
The top three use cases for agentic AI identified in the survey are heavily operational:
- Streamlining administrative workflows (59.56%)
- Clinical documentation and scribing (49.73%)
- Billing, claims, and prior authorization processing (46.99%)
These priorities reflect the crushing pressure on hospital margins and the persistent workforce shortages crippling the industry. By automating the revenue cycle and back-office paperwork, health systems aim to relieve clinician burnout and accelerate cash flow.
The Path to Measurable ROI
The era of adopting AI simply for innovation’s sake is over; executives now demand hard returns. According to the research, 52.46% of respondents anticipate time savings between 10% and 50%, while 41.53% expect moderate cost savings as these tools mature.
However, the report warns that achieving these returns is inextricably linked to an organization’s data maturity. Departments utilizing modern, interoperable platforms that embed AI directly into existing workflows will see faster time-to-value than those relying on fragmented, manual processes.
“AI is moving rapidly into mission-critical healthcare workflows,” said Chris Puuri, Global Head of Healthcare and Life Sciences, Hakkoda. “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.”
Read the full research report, “The Future of AI + Interoperability in Healthcare Report.”
