Introducing HealthSynq™ for AI: Creating Successful AI Initiatives in the Real World with Complete Data and Mature Governance
Why AI-Ready Data Matters Now
Healthcare organizations today are not short on data. In fact, the opposite is true. Between regulatory APIs, payer-provider exchanges, clinical records, claims data, and operational systems, health plans now have access to more information than ever before. Yet despite this explosion of data, many organizations still struggle to translate it into meaningful insights or scalable AI initiatives. And the stakes are rising.
According to Gartner®, “Through 2026, organizations that don’t enable and support their AI use cases through an AI-ready data practice will see over 60% of AI projects fail to deliver on business SLAs and be abandoned.”
Healthcare organizations are increasingly investing in AI and advanced analytics, but many initiatives stall before they can deliver meaningful value. The reason is simple: most healthcare data isn’t ready for AI.
Payers and providers are struggling to move AI initiatives from pilot to production due to several persistent challenges:
- Incomplete or fragmented datasets that limit capability and value
- Lack of data provenance and sensitive data handling, increasing risk exposure
- Significant ongoing effort required to maintain context across data sources
- Evolving AI governance expectations that make trust a moving target
Raw FHIR data alone is not enough. Claims-only or clinical-only records provide incomplete views of the patient journey. Even when regulatory interoperability APIs are live, the downstream work required to standardize, link, validate, and govern that data can create a major bottleneck.
And when AI encounters unclear or inconsistent data, it doesn’t simply degrade gracefully, it either halts or produces unreliable outputs and hallucinations. In high-stakes healthcare environments, that risk is unacceptable.
At Opala, we’ve seen our customers get tremendous value from harnessing healthcare data interoperability but have a vision to extend its impact even further – to power smarter decisions, predictive insights, and more connected payer-provider collaboration.
That’s why we’re excited to introduce HealthSynq™ for AI. This is a new capability within the Opala HealthSynq™ platform that builds on the longitudinal data foundation our customers trust today, with features that are purpose-built to address the challenges AI applications face in the real world.
HealthSynq™ for AI closes the gap between data exchange and AI execution. It converts data availability into data capability so that you can push past pilots and have confidence deploying your AI in the real-world.
What HealthSynq™ for AI Does
Healthcare data typically arrives in many formats and from many systems. Claims data, clinical records, operational information, and regulatory API responses all carry valuable insights, but they rarely align without significant transformation.
Opala HealthSynq™ has addressed this challenge for payers for years by creating a unified, longitudinal view of patient data across payer and provider systems.
This includes validating data quality at ingestion, preserving governance and provenance across the data lifecycle, and ensuring consistent normalization across trading partners. Sensitive data, including PHI, is managed with strict controls, supporting privacy, security, and appropriate use within any application.
HealthSynq™ for AI builds on this foundation by enriching and activating that data for intelligent use. It introduces enriched context within standards-based, healthcare specific models that AI understands best, embedded governance and transparency aligned to emerging frameworks from industry organizations like CHAI, and advanced data preparation capabilities designed specifically to support AI and analytics at scale. Then when it comes to leveraging HealthSynq’s AI-ready data in your AI tools, pipelines and experiences, Opala makes sure integration is easy, seamless and secure.
The result is trusted, AI-ready data that healthcare organizations can confidently use to power advanced insights and automation.
Data Engineered for the Next Era of Healthcare
As healthcare continues to embrace interoperability, the next challenge is ensuring that data flowing across systems can power intelligence.
HealthSynq™ for AI represents the next step in that journey.
Reach out to learn how your organization can activate the full potential of its healthcare data, and move AI initiatives from concept to real-world impact.
Gartner: A Journey Guide to Deliver AI Success Through AI-Ready Data, 11 July 2025, Ehtisham Zaidi, Roxane Edjlali
