As healthcare rapidly adopts AI, concerns around accuracy, safety, and trust have become impossible to ignore, especially in patient-facing applications. In this context, conversations around clinically governed data, transparency, and AI accountability are critical to ensuring technology enhances care without introducing risk. In this exclusive discussion, Gagan Sethi, CEO, Ebix Technologies, shared with Dr. Asawari Savant, from Elets News Network (ENN), on how platforms like EbixONE are addressing these challenges while enabling scalable, safe AI adoption in healthcare. Edited excerpts 

How clinically governed data can reduce AI hallucinations and improve patient safety across healthcare?

Clinically governed data is the fastest, most practical way to reduce hallucinations in healthcare AI because it changes what the model is allowed to “know.” Clinically governed data enforces medical editorial standards, structured taxonomy, version control, and clear sourcing. It also enables citation-first responses, which means the AI can show where the answer came from. That combination directly improves patient safety because it makes outputs more verifiable.

How EbixONE enables organisations to train AI models on verified, clinician-approved medical content?

EbixONE, Ebix AI initiative, enables organizations to build and train healthcare AI on verified content by giving them licensed access to trusted medical knowledge foundations through enterprise delivery models. That includes ADAM’s clinically reviewed medical content and medical illustrations, and Oakstone’s clinician education and CME aligned materials where appropriate. In simple terms, it lets healthcare organizations use the AI models they prefer, while ensuring the knowledge layer behind those models is clinically vetted and consistently maintained. This is done through MCP serves that clients can directly access or Ebix APIs they can use to get data either for training or for real-time verification purposes. 

Role of EbixONE in creating transparency, traceability, and governance in healthcare AI workflows with integration of platform-like libraries like A.D.A.M. and Oakstone CME?

The role of EbixONE in transparency, traceability, and governance is to operationalize trust. EbixONE is designed as an umbrella program for how EBIX delivers AI across verticals with a common operating model, shared security and governance practices, and consistent delivery standards. In addition, with our other offering SMARE, Ebix adds monitoring and controls so organizations can track interactions, enforce safety policies, and maintain audit-ready records. This is what allows AI deployment in regulated environments.

What is the impact on hospitals and health systems seeking safer patient-facing AI solutions?

For hospitals and health systems, the immediate impact is confidence to deploy patient-facing and staff-facing AI without introducing unacceptable risk. Most hospitals are trying to build systems to improve navigation, patient education, discharge instructions, benefits guidance, and internal clinical operations. But they hesitate to provide much of the medical information through AI because hallucinations and lack of traceability can create legal and reputational exposure. EbixONE helps by giving them a clinically vetted knowledge layer and governance controls that compliance teams can review. It also supports multi-language needs, which matters for global health systems and diverse populations.

Why healthcare AI success increasingly depends on data provenance, validation, and oversight?

Healthcare AI success increasingly depends on provenance, validation, and oversight because healthcare cannot be a “best effort” AI response. The same AI behavior that is acceptable in consumer search or general productivity is not acceptable when decisions, guidance, or health outcomes are involved. If you cannot explain where information came from, whether it is current, and how it was validated, you cannot do AI adoption in serious healthcare settings. That is why provenance and governance are not optional. They are the core requirements for safety and regulatory readiness. Strong models will continue to evolve, but the differentiator will be whether the underlying knowledge can be defended and governed.

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What are the key factors driving Ebix Technologies’s growth in India and global markets, and what is your long-term vision and strategy for the company, particularly for expanding the EbixOne platform’s healthcare ecosystem and strengthening its digital health services and content for users?

First is the market shift toward digital-first insurance, healthcare, and enterprise platforms. Second is the demand for trusted data foundations as AI adoption accelerates. Third is our ability to operate globally with strong delivery capacity and deep B2B experience across multiple verticals. In healthcare specifically, our long-term vision is to expand the EbixONE healthcare ecosystem by making ADAM and Oakstone even easier to license and integrate into enterprise AI stacks, and by offering practical delivery models that fit how organizations build today. That includes connectors and APIs, MCP server based access for agent ecosystems, and governance controls through SMARE. Over time, we also see opportunities to deliver embeddable experiences powered by our vetted content, while keeping the enterprise governance and traceability standards intact. The strategy is simple for now – which is to help organizations move fast with AI, but do it with knowledge, transparent sourcing, and safety controls.

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Disclaimer: The views and opinions expressed in this article are solely those of the author and do not necessarily reflect the official policy or views of any organisation. The content is intended for informational and educational purposes only and should not be construed as medical advice.

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