As AI Risks Grow, Insurers Split on Covering the Damage

Insurers are split on AI risk: some build specialized agentic AI coverage, while major carriers quietly exclude it — leaving enterprises exposed without their knowledge.

Following a rash of data breaches this year, several insurance companies have begun offering proactive artificial intelligence-related policies to cover enterprises that might be targets of unprovoked attacks or the source of attacks from AI agents going rogue. Meanwhile, other carriers are intentionally side-stepping this emerging risk, leaving enterprises to figure out how to manage it.

Insuring an enterprise against attacks from rogue AI agents that attack the enterprise, or perhaps those created within the enterprise that breach the corporate environment and attack third parties, is uncommon coverage. Many enterprises mistakenly believe their cyber and liability insurance policies covers AI-related risks; it often does not.

As corporate insurance policies often renew at the end of the calendar year, CFOs, general and outside counsels, CISOs and other corporate executives tasked with insurance responsibilities should be reading their existing policies closely now to determine their current AI risks and identifying exclusions that might be in their policies. This is also a good time to meet with insurers who offer AI-specific policies to learn what coverages are available that their existing policy does not cover. Insurers are warning that increased use of AI and AI agents is not keeping pace with enterprises’ governance. Rogue AI incidents, like the recent Open AI attacks against Hugging Face and other servers, have only heightened insurers’ concerns.

In 2025, insurance coverage specifically for AI-related losses was in its infancy. Carriers often included minimal coverage in generic Errors and Omissions (E&O) policies, Directors and Officers (D&O) liability insurance, or simply in the liability policy, but many of those policies are inadequate to address AI’s actual risks.

Today, several specialty insurance firms have coverage for AI-related incidents, either as endorsements, language included in technology E&O policies, or as standalone policies. Among the insurance companies and specialty providers that sell purpose-built policies, affirmative endorsements, and specialized coverage targeting AI risks are Armilla, Coalition, Corgi Insurance, Cowbell, Munich Re, and Beazley.

However, several large carriers are restricting or excluding AI-related risks and autonomous machine behavior from commercial general liability policies, adopting the Verisk/ISO exclusion endorsements. The exclusions address gaps in policies that were written prior to generative AI becoming ubiquitous within enterprises, according to insurance industry trade publication Insurance Business (IB). The ISO endorsement removes coverage for bodily injury, property damage, and personal and advertising injury arising from generative AI. Chubb, Travelers, Berkshire Hathaway, AIG and W.R. Berkey are among those adopting this endorsement, according to IB .

How to Qualify for AI-Specific Insurance

So how can companies protect themselves from possible losses from potential risks from rogue AI agents? Here’s what you can do today that can reduce risk and improve your ability to qualify for AI-specific insurance:

• Review your existing cyber and corporate liability insurance to determine exactly what AI-related losses are covered and what your security exposures are.

• Analyze your network infrastructure to determine if you have sufficient guardrails along with specific policies and procedures for addressing AI agent attacks, both incoming and outgoing.

• Have your general or outside counsel review third-party contracts to ensure your supply chain is protecting you from potential AI threats.

• Require your supply chain partners to demand their supply chain partners are protected; enterprises need protections multiple levels back down the supply chain

• Have your engineering team determine the different design patterns and architectural principles your vendors are using to build their AI applications. Not all AI development is compatible and responds to security software the same way so treating incompatible architectural principles the same could leave security gaps.

• Ensure your AI applications have the minimum system rights and credentials required to do their jobs.

• Treat Agentic AI as you would service accounts or endpoint detection and response systems. They’re not “set them and forget them.” They need to be monitored and maintained.

• AI is not a panacea for every problem a company might face. It is a tool with specific use cases and configurations. If you use it as a catch-all for whatever ails your network, you will be compromised. Only use AI for specific tasks for which you have written rules, expectations, and results and then ensure the AI applications are meeting those specific goals.

What Coverage Looks Like in Non-Cyber Policies

Coverage for AI-based risks sometimes fall outside the purview of cyber insurance coverage. Because of AI’s ubiquity in the enterprise, coverages for its potential failures likely will appear in other specialties as well.

For example, AI is used by a Human Resources department extensively at enterprises as hiring tool, says Andrew Correll, head of underwriting for Armilla, a Lloyd’s coverholder writing policies for the London syndicate. Coverage for AI tools that hallucinate or display a bias that triggers an insurable event might well be included in the enterprise’s liability coverage or in coverage specific to use cases that are separate from a dedicated cyber insurance policy, he adds.

AI coverage addresses more than just a corporate computer being attacked and completely disabled, notes Craig Linton, AI and Emerging Risk Strategy Lead at Beazley. In some cases, a system only needs to be purged of unwanted data brought in by an AI agent. Taking systems offline for that purpose could interrupt business operations but is different than a common malware attack that forces the system to go offline or fail, a covered event. Linton noted Beazley offers dedicated policies for defenses against the attack and endorsements that he calls “AI voluntary shutdown coverage.”

In order for enterprises to qualify for AI-related coverage, underwriters “look at the body of controls holistically,” Correll says.

“Human review is obviously a component of that,” he says. “But we also look for what kind of guardrails and rules are in place.”

Linton notes the Beazley application for AI coverage includes dozens of questions focusing on roughly 15 security controls. While most of the security controls are essential for cyber insurance coverage ­— multifactor authentication, backup and recovery, training and network protection — the carrier also includes enquires about operational technology security, mergers and acquisitions, and Payment Card Industry (PCI) security.

He cautions the team buying AI insurance – often the general or outside counsel, Chief Financial Officer and senior executives – that employees might well be using unsupervised AI on their corporate and personal devices. Like similar shadow IT challenges companies faced in years past, employees will turn to shadow AI they can obtain easily and inexpensively if the tools are not provided by their employer and secured by the IT team. With AI, he says, this can introduce significant risks.

One challenge several sources mentioned was addressing the common problem on generative AI Large Language Models (LLMs) having hallucinations and displaying bias. For Corgi Insurance, coverage for hallucinated, inaccurate, or biased model outputs may fall under the Technology E&O policy/ Generic Tech E&O policies written before generative AI technologies were widespread could be silent or ambiguous about how they treat model outputs. The company recommends looking for explicit AI-output language and reviewing algorithmic-bias exclusions carefully.When selecting an AI-centric policy, the proverbial devil is in the details, cautions Jack Kudale, co-founder and CEO of Cowbell. Does the policy wording address a non-malicious system failure? Does it address an unauthorized disclosure without any external intrusion? Does that fall within a cyber coverage? Does it fall in a technology errors and omission, or does it in a completely different risk altogether? Questions like these will determine if the policy or rider will address the threat the enterprise is trying to insure against or if there is a possible exclusion, such as the Verisk/ISO exclusion endorsements and similar limitations employed by the top tier insurers. If an exclusion is found in an existing policy during a corporate review, the enterprise then can purchase specialty coverage to mitigate that risk.

Protecting your enterprise from potential rogue AI agents and other AI risks requires that enterprises proactively ensure that three risk areas are protected: Infrastructure, data pipelines and your supply chain, Kudale says.

Protecting the infrastructure includes ensuring you have no misconfigured servers, over-permissioned identities and no exposed public endpoints. Safeguarding the data pipelines includes ensuring the storage architecture is secured from breaches, compromises and poor decision-making, he adds. Finally, organizations need to secure their supply chain well beyond their direct vendors. Threats can come from secondary, tertiary or further back in the supply chain.

“It’s one thing we worry about the most,” Kudale says. “We don’t worry about hallucination and bias as much as others. We worry about supply chain more .”

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Originally published on Dark Reading