Insurers Search for Answers to Rein in Rogue AI
As incidents of rogue AI agents causing harm increase, the cybersecurity insurance industry is grappling with how to assess and insure against the growing risks. Cyber insurance traditionally focuses on breaches and downtime, but the emergence of autonomous AI agents capable of independent, potentially malicious actions is creating a significant liability gap. Insurers are struggling to determine who is responsible when these agents go rogue – whether it’s the deploying organization or the AI model providers themselves – and are facing challenges in underwriting policies for companies heavily reliant on AI services. The rapid pace of AI development and deployment means that existing insurance frameworks are ill-equipped to handle the evolving threat landscape.
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As incidents of unintended harm caused by rogue AI agents mount, CISOs and insurance firms are figuring out how to handle the fallout.
Maria Long, chief underwriting officer for cybersecurity insurance services firm Resilience, noted that rogue AI agents causing inadvertent compromises could result in significant losses to insurers in the future. This incident showed that the future wasn't that far off. For Hugging Face, the incident would almost certainly be covered by cyber-liability insurance as a classic security breach. However, if AI agents routinely escape containment, insurers have to consider that the volume of policy claims could grow.
Moving Beyond Breaches and Downtime
Currently, much of cyber insurance focuses on breaches and downtime, and that remains the focus of most insurers, says Resilience’s Long. As companies rely more heavily on AI services, and an AI service goes down due to an error or malicious action, this could lead to claims for losses. “If you’re now six months, one year, two years deep into your AI build-out, and really making this a routine part of your day-to-day [operations], what happens if that service is down and you can’t use it? Does that cause an interruption to the business? Does that result in a monetary loss to the organization?”
Liability Remains a Question
The problem with AI agents, however, is their persistence in pursuing their goals, and a single bad decision by an AI agent could trigger a worm-like outbreak of attacks, says Jack Nelson, CISO and deputy general counsel at Ivanti, an endpoint-security management provider. “I suspect your insurance carriers are having a hard time underwriting things like this because they just don't know how to [gauge liability] because of how fast these incidents could balloon,” he says. The issue could extend to criminal liability as well. The Trump administration’s Executive Order 14409, published in June, prioritizes the investigation and prosecution of AI-enabled attacks in which anyone “utilizes AI to illegally access or damage a computer without authorization.” Considering that attacks by rogue AI agents are not easily discernible from malicious AI attacks — Hugging Face initially just knew it was being attacked — rogue AI agents could result in prosecutions, a problem, considering that AI agents’ goal-oriented behavior makes them hard to control.
Overall, incidents of AI system failures and safety issues have taken off in 2026. The four preceding years saw a few dozen incidents (34 to 36) reported per year, but so far in 2026, there have already been 43, according to the MIT AI Risk Initiative. As companies accelerate their adoption of AI and increasingly automate some tasks with AI agents, cybersecurity has become a major concern, but one that often takes a back seat to efforts to gain productivity and business advantage from the new technology.
Moving Beyond Breaches and Downtime
Overall, as with much of the innovation around AI systems, everything is up in the air at the moment and could change in six months, says Ivanti’s Nelson. Given the deep pockets of the foundational AI model firms, however, and the past history of the ‘shared responsibility’ model for cloud services, much of the responsibility will likely land on the organization that deploys agents, he says. “Liability has yet to be determined — whether it’s totally going to sit with the person that unleashed the agent, or is it going to sit with the actual model creators that created a model that could do that,” he says. “I suspect the former is more likely, because [the operator has] so much input in terms of harnesses, skills, how you’re training the agent.”