What happens when the technology everyone is rushing to adopt becomes too unpredictable for the very industry built on managing risk? According to new reporting from the Financial Times, we may be about to find out.
Several major U.S. insurers including Great American, Chubb, and W. R. Berkley have asked regulators for approval to exclude broad, AI-related liabilities from corporate insurance policies. One underwriter told the FT that the output of modern AI models remains “too much of a black box” to reliably insure.
AIG, which was also mentioned in the FT report, later clarified to TechCrunch that it “was not specifically seeking to use these exclusions and has no plans to implement them at this time.”
The hesitation comes after a series of high-profile AI failures that carried serious financial consequences. Google’s AI Overview wrongly claimed earlier this year that a solar company had legal troubles, sparking a 110 million dollar defamation lawsuit. Air Canada was forced to honor a discount fabricated by its own customer-service chatbot. And in another incident, fraudsters used an AI-generated deepfake of a senior executive to steal 25 million dollars from the global engineering firm Arup during what appeared to be a legitimate video call.
But what truly worries insurers isn’t a single colossal payout. It’s the prospect of systemic losses. If a widely used AI model makes a faulty decision or generates misleading information, thousands of businesses could be affected simultaneously. As one Aon executive explained, insurers can absorb a 400 million dollar loss from one company. What they can’t withstand is a scenario where an autonomous AI error triggers 10,000 claims overnight.
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