As Insurers Start Excluding AI Risk Instead of Pricing It, a New Book Asks If Insurance Law Can Adapt
On 1 April 2026, P&C Insurance Executive Intelligence reported that major U.S. commercial carriers — including WR Berkley and AIG — had begun adopting new ISO/Verisk exclusion endorsements (forms CG 40 47 and CG 35 08), effective from 1 January 2026, that strip generative-AI-related bodily injury, property damage, and advertising injury claims out of standard commercial general liability policies. The reporting cites a Testudo database tracking more than 700 U.S. generative-AI lawsuits filed between 2020 and 2025, with filings up 137% year-on-year in the most recent period, while the major AI vendors themselves — OpenAI, Anthropic, Google, and Microsoft — cap their own contractual liability at twelve months of fees, leaving enterprise deployers to absorb whatever risk remains. In short: rather than price AI risk, large parts of the insurance market are choosing to exclude it.
That retreat is exactly the symptom Dr Feng Wang's new book, AI and the Evolution of Insurance Law, sets out to diagnose. Wang tests the core doctrines insurers have relied on for a century — insurability, causation, disclosure, policy construction, liability — directly against what makes AI different: model opacity, automated decision-making, and systemic, correlated exposure across policyholders. The book's central question is not whether insurers should exclude AI risk, but whether existing doctrine can be adapted to underwrite it responsibly, and where it cannot, what regulatory or contractual innovation should take its place.
Three parts of the book speak directly to the exclusions now appearing in the market: a full chapter reassessing what counts as "knowledge" under the UK Insurance Act 2015 once an AI system, rather than a human underwriter, is doing the assessing — a framework insurers well beyond the UK already treat as a reference point; a chapter-length treatment of causation for AI-related losses, the exact question that makes AI claims hard to adjudicate under current policy wording; and a closing discussion of AI-specific liability insurance design, AI mutuals, and public-private partnership models as concrete alternatives to blanket exclusion.
For law, business, and insurance libraries, this is a title that will only grow more relevant as exclusion language like CG 40 47 becomes standard policy wording and clients start asking what, if anything, still covers their AI exposure — making it a timely acquisition for insurance law, technology regulation, and financial services law collections.
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Q&A
Why are insurers excluding AI-related risk instead of pricing it?
Reporting from April 2026 shows major carriers adopting new exclusion endorsements for generative-AI liability, citing a sharp rise in AI-related lawsuits and the limited liability caps AI vendors themselves accept — leaving insurers unwilling to absorb the residual exposure under existing doctrine.
Can current insurance law doctrine handle AI-related harms?
The book argues this is genuinely open. It tests insurability, causation, disclosure, and liability doctrine against AI-specific features like model opacity and automated decision-making, finding some doctrines adapt more easily than others.
How does AI affect the duty of disclosure in insurance contracts?
The book devotes a chapter to reassessing "knowledge" under the UK Insurance Act 2015 in an AI context, a question insurers and regulators outside the UK are also grappling with given English law's influence on international market practice.
What alternatives to exclusion does the book propose?
It discusses AI-specific liability insurance design, AI mutuals, and AI public-private partnership models as structural responses where traditional underwriting doctrine falls short.
Where can I buy AI and the Evolution of Insurance Law?
You can order this title directly from CLNZ Books with secure worldwide shipping, payment by credit card or PayPal, and institutional invoicing available on request.
