AI in Swiss claims: what works at scale
Building AI is the easy part. Deploying it at scale is the real work. We interviewed senior data, AI and IT leaders at the largest Swiss health and life insurers to find out what separates pilots that scale from the PoC graveyard.
of AI pilots reach enterprise scale.
of AI project effort goes into integration with core systems.
In partnership with the Swiss Insurtech Hub
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4 pages: governance models, barriers to scale, claims results and what comes next.
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Download the PDFFour pages built for claims and IT leaders
Real answers from the people running AI at the largest Swiss health and life insurers, compared side by side.
Executive summary & methodology
Five key findings and how the study was run.
Governance, ROI & barriers
Three governance models, how business cases are planned, and the four barriers that stall pilots.
Claims impact & outlook
Results in document intake, invoice checks and claims assistants, and the move to agentic AI.
From pilot to production
How to skip the PoC graveyard with a 4-week Proof of Value on your own data.
Same questions, every insurer
30-minute structured interviews with 5+ senior data, AI and IT leaders. Every interview followed the same three blocks, so answers can be compared.
Strategy
How insurers choose AI use cases, govern them and decide what gets funded.
Processes & challenges
What it takes to move a pilot into production, and where it gets stuck.
Results & outlook
Measured impact in claims today, and where AI goes next.
Executive summary
Swiss health and life insurers are no longer asking whether to use AI; they are asking how to make it pay off at scale. Our interviews with leaders from the largest Swiss H&L insurers give a clear and consistent message: building AI is the easy part. Deploying it at scale is the real work.
Governance comes first. The leading insurers keep the "PoC graveyard" small by filtering use cases early, with central approval, strategic project portfolios and lighthouse pilots that must prove their value before rollout.
Integration is the main barrier. Most of the effort goes into connecting AI to legacy core systems and processes, not into building models.
People are the bottleneck. The same scarce IT and data teams build pilots, run solutions in production and maintain them.
What the Swiss market told us
of AI project effort goes into integration with core systems.
of AI pilots reach enterprise scale.
claims efficiency gain, reached ahead of target.
intent recognition on invoices with specialized models, up from ~72%.
Ready to move from pilot to production?
Qantev is the Claims Intelligence Platform for health and life insurers, trusted by insurers and TPAs including AXA, Bupa, Generali and Global Excel.
contact@qantev.com
