# Willis flags AI as governance, liability and insurability challenge > Source: > Published: 2026-05-28 12:06:18.034178+00:00 # Willis flags AI as governance, liability and insurability challenge According to **Willis**' latest Risk & Resilience Review, AI is being embedded across underwriting, claims, cyber defence and operational decision-making. The report states that more than **700 million** people now use leading AI systems every week and warns adoption is outpacing existing governance frameworks, creating new accountability, liability and insurability questions. Reporting by Markets Business Insider and reinsurance.news highlights that the insurance market is already diverging, with some carriers relying on traditional policy wording and so-called "silent AI" assumptions while others are introducing affirmative AI cover and stronger underwriting tied to governance controls. "For insurers, this is uncomfortable territory," the report says, adding that legal doctrine, regulation and operational oversight are all implicated. Industry observers will be watching how underwriting, policy language and regulatory clarity evolve. ### What happened According to **Willis**' Risk & Resilience Review, **AI** is now embedded across underwriting, claims, cyber defence, and operational decision-making. The report states more than **700 million** people use leading AI systems weekly and warns that adoption is outpacing existing governance frameworks. The report highlights emerging questions around accountability, liability and insurability and says exposure is building across multiple lines. The report states, "For insurers, this is uncomfortable territory. The industry is used to dealing with uncertainty, but typically with the benefit of history, data and precedent." ### Editorial analysis - technical context Companies embedding AI into operational workflows commonly rely on models and pipelines that are partly opaque to end users. This pattern increases the challenge of attributing root cause when model outputs contribute to errors, and it complicates forensic analysis needed for liability claims. Observed patterns in similar transitions show insurers and risk teams require stronger evidence of governance, testing and human-in-the-loop checkpoints before accepting model-driven decisioning as insurable processes. ### Context and significance Reporting by Markets Business Insider and reinsurance.news documents a market divergence where some insurers retain traditional policy wording and "silent AI" assumptions while others introduce affirmative AI coverage and add underwriting requirements tied to governance frameworks. Industry context: That divergence can produce coverage gaps and pricing mismatches as underwriters quantify exposures without long-run loss histories or established legal precedent. The report also situates cyber risk growth as a backdrop, citing global cybercrime costs rising from roughly **US$3 trillion** in 2015 to a projected **US$10.5 trillion** annually by 2025, which increases pressure on adaptive cyber defences that often use AI. ### What to watch For practitioners: monitor shifts in policy language toward affirmative AI endorsements and exclusions. For practitioners: track emerging regulatory guidance and litigation that will clarify liability allocation for model-driven decisions. For practitioners: watch market signals from major insurers and brokers on underwriting tests, governance milestones, and required controls before coverage is extended. ## Scoring Rationale This story matters to practitioners because it documents concrete insurance-market responses to AI adoption and quantifies exposure drivers affecting risk transfer and compliance. It is notable but not frontier-level technical news. Practice with real Health & Insurance data 90 SQL & Python problems · 15 industry datasets 250 free problems · No credit card [See all Health & Insurance problems](/problems/datasets/health)