PolicyProof for AI Agents
A standardised residual-risk input layer for insurers and MGAs writing professional-liability cover for firms that deploy AI agents.
insurer underwriters and MGAs launching AI-liability products
- Standardised risk inputs so policies can be priced consistently across carriers
- Portfolio-level risk aggregation across an insurer's entire agentic book
- Benchmarking of applicant risk vs anonymised peer set
- Loss-prevention recommendations that can be tied to premium discounts
Carriers are quietly declining AI-agent deployments because no shared residual-risk language exists between underwriter and buyer.
Strong live evidence: AIG, Great American, and WR Berkley have filed with regulators to restrict AI-agent liability, Willis research documents a structural shift from silent to explicit AI cover between 2025-2026, and Lloyd's syndicates have launched AI E&O products — confirming underwriters urgently need standardised inputs.Insurers face hidden AI liability as agent risks multiply ↗Insurers to Pull Back From AI Liability Coverage - Datamation ↗
Incumbents (AIG's AI Liability Policy 2024, Lloyd's syndicate 2002 AI E&O, Swiss Re AI Model Risk Endorsement 2025) are building internal carrier-specific products, and RICS has published a competing AI standard — but no vendor has emerged offering a compositional, agent-failure-path-to-residual-risk input layer sold across carriers.From Silent Coverage to Explicit Policies: How AI Risks Are ... - Archyde ↗Silent AI cover: the unforeseen risks for insurers ↗
B2B pricing for underwriter risk-scoring tools is well established (e.g., UnderwriteAI, Vertafore) but AI-agent-specific inputs are unpriced; carriers and MGAs are still in product-design mode and have not publicly disclosed willingness to pay for a third-party standard, and loss-history scarcity suppresses premiums.Beyond the hype: A strategic AI framework for MGA success - Vertafore ↗Insurance carriers quietly back away from covering AI outputs ↗
Highly structural: EU AI Act, RICS mandatory AI standard from March 2026, and accelerating enterprise agent deployment make residual-risk quantification a long-term regulatory and commercial need — though incumbents (NIST, ISO, carrier consortia) could absorb the standard-setting role.RICS Update: AI Standards and PI Insurance - Forte ↗Artificial intelligence and the impacts on professional indemnity insurance - WTW ↗
Non-trivial: requires deep actuarial and underwriting domain expertise, carrier/MGA sales cycles (12-24 months), integration with policy admin systems, and credibility to set a cross-carrier standard — the arXiv paper provides academic framing but no production traction yet.Beyond the hype: A strategic AI framework for MGA success - Vertafore ↗