Guides

Research for the People Who Buy and Place AI Coverage

Each guide answers one question a risk manager, general counsel or broker asks about AI liability, with the cases, regulations and policy language behind the answer.

BuyingHow Underwriters Assess AI Risk, and How to Prepare an AI Liability ApplicationUnderwriters price AI liability on three things: how much harm the company's AI could do to people and their finances, how well the company governs and monitors it, and its claims history. Preparing an inventory of AI systems, a written governance policy and evidence of testing before applying gives the underwriter what it needs and can improve terms.12 min · October 5th 2026

Fundamentals

FundamentalsWhy Companies Using AI Need AI Liability InsuranceAI liability insurance is written to pay for defending and resolving claims that arise from a company's use of AI, such as a customer harmed by wrong output, an applicant screened out by a biased tool or an investor misled about the company's AI. Companies need it because their D&O, EPL, E&O and cyber policies were written before these exposures existed, and insurers have begun adding AI exclusions to them.12 min · October 5th 2026

Coverage

CoverageSilent AI and the New AI Exclusions in D&O, E&O, EPL and CGL PoliciesSilent AI is the uncertainty that arises when an insurance policy neither covers nor excludes losses caused by artificial intelligence. Insurers are now resolving it with AI exclusions, including ISO general liability endorsements effective January 2026 and at least one far broader exclusion in D&O and E&O forms, so each renewal should be read for new AI wording and affirmative cover bought where it is removed.11 min · October 5th 2026

CoverageAI Liability Insurance vs Cyber Insurance: What Each CoversCyber insurance is built to respond to security and privacy events, such as a breach, ransomware or a network outage. Many AI claims involve no security event at all, for instance a chatbot giving wrong advice or a hiring tool screening out older applicants, so they fall to liability policies such as E&O, EPL or D&O, which may themselves be silent on AI or exclude it.12 min · October 5th 2026

Risk

RiskAI in Hiring: Discrimination Claims, New Rules and EPL CoverageEmployers that use AI to screen, rank or evaluate people remain responsible for the discrimination those tools cause, and a federal court has allowed claims against the software vendor as well. Rules in New York City, Illinois, California and Colorado add notice, audit and record-keeping duties, and an EPL policy that is silent on AI or excludes it may not respond to these claims.12 min · October 5th 2026

RiskAI and the Board: Oversight Duties, AI-Washing and D&O ExposureDirectors and officers face AI claims in two ways: for overstating what the company's AI does, known as AI-washing, and for failing to oversee AI that later causes harm. Regulators have already brought AI-washing cases and shareholders have filed AI-related securities suits, so boards should document their AI oversight and check whether their D&O policy is silent on AI or excludes it.12 min · October 5th 2026

RiskWho Is Liable When AI Hallucinates? Cases, Exposure and InsuranceWhen AI output is wrong, the company that put the AI in front of customers or clients is usually the party held responsible, as a Canadian tribunal ruled against Air Canada in 2024 over its chatbot's advice. Professional liability (E&O) is the line most likely to respond to these claims, but many E&O wordings are silent on AI and some now exclude it.11 min · October 5th 2026

RiskAgentic AI Liability: Who Pays When an AI Agent Gets It WrongA company that lets an AI agent act for it is generally bound by what the agent does, in the same way it is bound by the automated systems it already deploys. The exposure grows with the agent's authority, from read-only research to sending messages, changing systems and moving money, which is why transaction limits, approval gates and audit logs matter to both liability and insurance.12 min · October 5th 2026

RiskPrompt Injection, Data Poisoning and Deepfake Fraud: Which Policy RespondsAI creates two kinds of cyber risk: attacks on a company's AI, such as prompt injection and data poisoning, and attacks that use AI, such as deepfake impersonation. Which policy responds depends on the loss: cyber for breaches and data loss, crime or social engineering cover for stolen funds, and E&O or D&O when customers or investors claim the company's AI failed them.12 min · October 5th 2026

Regulation

RegulationThe AI Laws That Create Liability for US CompaniesThere is no comprehensive federal AI law in the US, but laws in Colorado, Texas, Illinois, New York, California and Utah, together with the EU AI Act, impose duties whose breach can lead to enforcement and lawsuits. Most are enforced by attorneys general and other regulators rather than by private plaintiffs, but their duties can also become the standard of care that private claims cite.13 min · October 5th 2026

Buying

BuyingBuying AI Liability Insurance: Questions to Ask Your Broker and InsurerBefore buying AI liability insurance, check how the policy defines AI, whether it responds to employment, discrimination, securities and regulatory claims, how limits and defense costs work, and who stands behind the policy. A broker should be able to answer each question from the policy wording rather than the marketing.12 min · October 5th 2026

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