As businesses move from AI tools that assist employees to autonomous agents capable of making decisions and taking actions, the cyber insurance industry is confronting a new category of uncertainty. AI agents can potentially access systems, identify vulnerabilities and execute tasks with limited human intervention, making it harder to determine whether an incident should be treated as a cyberattack, technology failure or operational mistake.
Traditional cyber policies generally focus on events such as unauthorised access, ransomware, data breaches and system disruption. Autonomous agents complicate those definitions because an AI system may have legitimate access when it takes an unexpected action. Insurers including QBE, Beazley and MSIG are therefore examining how existing policies should respond when AI contributes to an incident, rather than simply treating AI as an entirely separate risk category.
The challenge extends beyond policy wording. Insurers have limited historical claims data to assess how frequently autonomous AI failures could occur or how costly they might become. There is also the possibility of systemic exposure if multiple businesses depend on the same AI model or technology provider. Specialised offerings are already emerging around AI-related risks such as model performance, hallucinations and intellectual property, signalling a broader expansion of the risk-transfer market.
For enterprises, the insurance conversation is beginning to overlap with AI governance. Access controls, human oversight, monitoring, testing and the ability to intervene when an agent behaves unexpectedly could become increasingly important when organisations assess their exposure and negotiate coverage. As AI agents take on more operational responsibility, the critical question for insurers may no longer be simply whether a system was attacked, but who carries the risk when an authorised AI system causes unintended damage.
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