Interoperability Is the Foundation That AI Depends On
Artificial intelligence is quickly becoming one of healthcare’s highest strategic priorities. From improving clinical decision making to streamlining operations and identifying opportunities for better patient outcomes, organizations are investing heavily in AI technologies. But there’s an important reality that’s often overlooked: AI is only as valuable as the data that powers it.
According to the HIMSS 2026 AI Landscape Report, 71% of healthcare organizations are already using AI, nearly half have integrated AI into care delivery and operations, and three out of four organizations plan to expand AI to advance patient-centered care.
Yet despite this rapid adoption:
- 84% say high-quality data is critical for successful AI adoption.
- Only 47% are confident their data is accurate.
- Only 21% believe their data is fully leveraged for clinical and operational decision making.
- 44% are actively implementing interoperability standards to support digital transformation.
Healthcare organizations recognize AI’s potential, but many are still building on fragmented, disconnected data. Interoperability across the healthcare ecosystem has the potential to close this gap by hydrating AI models with complete, consistent, and reliable data.
AI Applications in Healthcare Require Contextualized Data
Healthcare data exists across countless systems, organizations, and workflows. Without a trusted, standardized foundation, AI models struggle to deliver reliable, actionable insights. Successful AI requires data that is accurate, current, standardized, secure, and interoperable. This foundation enables AI models to produce reliable, actionable insights and makes interoperability a strategic business capability rather than simply a regulatory requirement.
HealthSynq™ for AI: Built on Trusted Interoperability
HealthSynq™ for AI combines clinical and administrative data using HL7® FHIR® standards into a semantic data layer that can be used for intelligent applications, analytics, and decision support. By reducing time and resources spent preparing and reconciling data, Opala customers can rapidly deploy AI tools in production at scale.
Turning Data into Actionable Insights
HealthSynq™ for AI enables organizations to put their data to work. One example is Opala’s Conversational Analytics capability, which allows users to interact with their healthcare data using natural language. Instead of relying solely on static dashboards or requesting custom reports from IT, users can ask questions about their own data and receive immediate, context-aware answers.
Questions such as:
- How are admissions trending over time?
- Which facilities are experiencing the fastest growth?
- What diagnoses are driving increased utilization?
- How do trends compare across lines of business?
Because their data resides within the HealthSynq™ platform, Opala customers can explore current clinical and operational data with confidence, knowing the information is standardized, scalable, and built on trusted interoperability. For health plans, this means decision makers can move beyond predefined reports to quickly investigate emerging trends, answer operational questions, and uncover insights that support care management, utilization management, and strategic planning, without waiting for new dashboards or report development.
Conversational Analytics demonstrates how interoperable data becomes significantly more valuable when paired with AI, transforming healthcare data from a static reporting asset into an interactive decision-support capability.
Beyond Analytics
The true opportunity extends well beyond reporting. When healthcare organizations establish a trusted interoperability data foundation, AI can support:
- Operational decision-making
- Care management
- Population health initiatives
- Utilization management
- Quality improvement
- Executive reporting
- Clinical insights
Instead of asking whether AI belongs in healthcare, organizations can begin asking where AI can deliver the greatest value.
Building the Foundation for What’s Next
Healthcare’s AI journey isn’t limited by innovation, it is limited by data readiness. Organizations that invest in interoperability today will be better positioned to take advantage of tomorrow’s AI capabilities.
At Opala, we believe interoperability is more than connecting systems. It creates the trusted data foundation that allows healthcare organizations to confidently adopt AI, accelerate innovation, and unlock new value from their data.
With HealthSynq™ for AI, organizations turn trusted healthcare data into actionable insights and administrative efficiencies at scale.
