AI agent risks increase insurers’ hidden liability

More than 90% of insurers’ exposure to AI agents may be sitting inside conventional policies never designed for the technology, according to a new industry report. The finding comes from Underwriting the Agent Economy, a study by the Artificial Intelligence Underwriting Company (AIUC). Researchers from Anthropic and OpenAI were among its co-authors, alongside experts from insurers, brokers, universities and research groups.

AIUC is a San Francisco-based firm that certifies and insures AI agents. The study found that exposure was concentrated in cyber, directors and officers, commercial general liability, and technology errors and omissions policies. This “silent” cover refers to risks that are neither expressly included nor excluded. Carriers may face liability for losses they never priced or anticipated.

Willis research found the professional liability market shifted structurally between January 2025 and January 2026. Providers moved from silent AI assumptions to either explicit affirmative warranties or absolute exclusions. Gallagher 2026 survey data found that one in five insurance professionals reported their customers had already experienced losses linked to AI risk.

Disputes over liability are already forming

According to the study, AI agents differ from chatbots in one material respect: they carry out tasks rather than generate responses. These tools can operate software, access company data and move funds with limited human oversight. Failures could trigger claims across professional negligence, data breach, fraud, discrimination and cyber lines.

The growing reliance on autonomous systems in business operations means that even carefully worded policies may be tested in ways that courts have not yet addressed.

The gap between technological capability and insurance language could widen as AI agents become more independent.

Disputes over which policy responds when an AI agent causes harm are likely to become more common, and the outcome may depend on details that neither side fully anticipated.

Real cases are already testing those boundaries. British engineering firm Arup lost HK$200 million (approximately US$25 million) in 2024 after criminals used deepfake video calls to impersonate senior executives.

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An employee in Hong Kong was persuaded to transfer funds to accounts the fraudsters controlled. A claim from such an incident could span crime, cyber, and social-engineering cover.

Insurers and policyholders would likely dispute whether the transfer was voluntary or fraudulent.

In North America, US solar installer Wolf River Electric has sued Google for at least US$110 million in damages. The lawsuit alleges Google’s AI Overviews feature published false claims about the company’s business practices. In Canada, a tribunal ordered Air Canada to pay compensation to a passenger misled by its chatbot. It found the airline was responsible for information on its own website.

Risk scenario and market response

The study warned that a severe AI event could produce around US$100 billion in direct losses. Wider economic costs could reach into the trillions if insurers withdrew cover and businesses reduced AI adoption. The agency stated the figure is a risk scenario, not a forecast.

Kevin Kalinich, head of intangible assets at Aon and a co-author of the report, said AI could produce “aggregated, systemic, correlated” losses. The co-authors compared the risk to the terrorism insurance market after September 11. More than US$40 billion in insured losses then prompted carriers to restrict cover until government backstops were introduced.

Some industry figures have questioned whether the warnings are overstated. Critics note that AIUC has a commercial interest in the growth of specialist AI cover. It acknowledged that criticism but found that existing policy wording was already generating uncertainty for both sides.

Some carriers have begun adding exclusions for generative AI, which could reduce hidden exposure while leaving policyholders with less protection.

The study called for dedicated AI cover, common technical standards and clearer policy language, warning that without those changes, major AI losses are likely to produce disputes over risks that insurers did not know they had accepted.