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iFHP Report: Benchmarking AI in Health Insurance – Global Patterns and Practical Lessons
Understanding where AI is creating value and where constraints remain

Health insurers are experimenting with AI across many parts of their business, but progress is uneven.

This new iFHP benchmarking report looks at how AI is being used in practice, drawing on interviews and survey data from iFHP members across different regions. It explores where AI is already delivering value, where adoption remains cautious, and what is holding organisations back.

The findings show that operational and support functions tend to be furthest ahead, where use cases are clearer and risks are easier to manage. In pricing and risk, AI is most often used to support analysis rather than automate decisions. Member engagement remains an area of caution, shaped by trust, compliance and reputational concerns. Strategic and clinical applications appear only where data quality and governance are well established.

The report points to a clear next phase for insurers: moving beyond pilots and experimentation towards more dependable, scalable use of AI. Doing so will require strong governance, better data integration, continued human oversight and focused investment in skills.

About the report

The iFHP Benchmarking Report on AI in Health Insurance maps AI adoption across five areas: operations, pricing and risk, member engagement, strategy and clinical, and product and market innovation. It also explores the organisational, regulatory and cultural factors that influence progress. This report is intended for senior leaders, strategists and board members who want a clearer picture of how AI adoption is actually evolving across health insurance markets, and what responsible, effective use looks like in practice.

Key takeaways

• Operational AI is now relatively well established in many plans
• Pricing and risk teams use AI primarily to support, not replace, decision-making
• Member-facing use cases remain cautious due to trust and compliance concerns
• Strategic and clinical applications depend on stronger data and governance foundations
• Innovation is uneven and often driven through external partnerships

Download the executive summary below, or sign in to view the full report.

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