Global reinsurer SCOR has released a report detailing the growing integration of generative artificial intelligence (GenAI) in life and health insurance. Drawing on the company’s internal experience and a recent industry survey, the report identified key opportunities as well as persistent challenges.
According to a February 2026 Gallagher survey cited in the report, 80% of life and health insurers have already deployed GenAI solutions in at least one core function, signaling that the technology has moved well beyond the experimental stage.
The SCOR report identified four primary use cases gaining traction across the industry: AI-powered customer engagement tools, automated summarization of unstructured data, augmented underwriting and claims support, and advanced data analytics. Among these, streamlining document-intensive underwriting and claims processes emerged as SCOR’s highest priority, with the review of medical records often requiring several hours to several days of staff time per case.
SCOR said its proprietary AI Assistant tool, first introduced to internal users in 2023, has since expanded to more than 100 underwriting and claims professionals across major global markets and now processes more than one million pages of documents each month.
Despite that growth, the report highlighted four significant challenges that insurers should expect. Early pilots of the AI Assistant produced results that ran counter to expectations: case management times initially increased rather than decreased, as employees spent additional time verifying AI-generated outputs against source documents. The report noted that returns on investment may take time to materialize and warned that organizations risk abandoning AI initiatives prematurely if early gains fail to meet expectations.
Fragmented digital infrastructure also emerged as a major obstacle. According to the report, legacy systems often trap data in incompatible databases, hindering the seamless flow of information needed to achieve AI’s full efficiency potential.
Regulatory compliance represented another challenge. The report cited frameworks such as the EU AI Act, GDPR, and HIPAA as imposing strict requirements related to explainability, data protection, and non-discrimination. SCOR said these obligations can cause organizations to delay scaling AI initiatives.
The regulatory concern appears well-founded. Separate research from MoneyGeek found that nearly one in three health insurers do not test their AI models for racial bias, according to the NAIC.
The report was authored by Pierre Gilloury, head of L&H Transformation; Antoine Ly, head of AI Foundations and Data Science; and Roberto Castellini, head of L&H Data Science, with Kevin Heera of SCOR Digital Solutions contributing to the publication.
