Insurance Faces Growing Gap in AI-Related Coverage
Traditional insurance policies are leaving organizations exposed to a growing class of liabilities created by artificial intelligence deployment, according to research from Gallagher Re. The firm's whitepaper, "Smart Systems, Blind Spots: Rethinking Insurance for the AI Era," found that current coverage structures do not adequately address risks from generative AI and LLM systems embedded in customer interactions and core business processes.
Courts and regulators are treating AI failures as the responsibility of the organization deploying the technology, not the vendor. This legal reality creates a mismatch with existing insurance contracts, which typically favor vendors.
Fragmented Coverage Leaves Gaps
A problem caused by a customer-facing chatbot might trigger a liability claim under one policy. An AI-assisted cyber attack would fall under cyber insurance. Other potential triggers include errors and omissions policies, product liability, or commercial general liability coverage.
But AI systems create distinct liabilities that fall outside standard policies. Algorithmic failures, model degradation, discrimination, and intellectual property infringement generally do not receive coverage designed to address them. The research shows that AI as an attack vector triggers cyber coverage, but AI as a liability source-such as hallucinations or bias-does not.
Gallagher Re said this fragmentation leaves significant gaps. "Coverage, governance and contractual protections must evolve," the firm wrote. "Enterprises need explicit protection for AI-driven liability, supported by stronger governance and smarter program design."
Litigation Already Material
The risks are not theoretical. Litigation patterns show AI-related harm is legally validated and financially material, with the problem expanding. Organizations deploying AI are increasingly aware of these exposures.
Insurance Industry Responds in Two Ways
Specialized insurers are developing standalone products to address exposures that traditional policies do not cover. Established carriers are introducing enhanced endorsements that adapt existing frameworks. Both approaches are necessary to close the gaps.
The industry must clarify AI coverage boundaries in existing policy lines and explicitly state each insurer's appetite for AI risk. The question now is whether the insurance market can adapt quickly enough to address these emerging liabilities.
Organizations seeking to understand AI for insurance professionals can explore how the industry is responding to these coverage challenges.
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