Does Business Insurance Cover Mistakes Made by an AI Tool or AI Agent?

Detailed Explanation

A business that has used AI tools or automation for a while without an incident can reasonably assume its existing insurance would respond if something did go wrong — an AI agent sends a wrong invoice, a chatbot gives a customer bad advice that leads to a loss, an automated decision turns out to be discriminatory or incorrect. As of 2026, that assumption is increasingly unsafe.

The core issue is that most general liability, directors and officers, and traditional errors and omissions policies were written well before AI-driven automation became common, and were never designed with this risk in mind. Rather than leaving it ambiguous (what the industry calls "silent AI" coverage — AI risk that's neither explicitly included nor excluded), a growing number of major carriers have moved to add explicit AI exclusions to these policy types, closing the ambiguity in the insurer's favor. The practical effect is that a business relying on a standard general liability or traditional E&O policy may find a claim caused by an AI tool's error falls outside coverage entirely, even if a very similar claim caused by human error would have been covered.

Where affirmative coverage for AI-related mistakes actually exists, it's typically one of a few specific places:

• A technology errors and omissions (tech E&O) policy — designed around professional and product failures, including software and systems that don't perform as promised, and currently the line most likely to respond to an AI-caused financial loss.
• A cyber policy with AI coverage explicitly written in — not every cyber policy includes this by default; it depends on the specific carrier and policy language.
• A dedicated AI-liability endorsement or rider — a growing but still-developing product category, added on top of an existing policy rather than assumed to be included.

None of these are universal or standardized across carriers, and terms are changing quickly as insurers respond to real claims experience. The only way to know what a specific business is actually covered for is to ask the broker or insurer directly, in writing, and get a specific answer about AI-related exposure — not to infer coverage from a policy's general language.

What to Ask Your Broker or Insurer

• Does our current general liability, D&O, or E&O policy contain an AI exclusion? Ask for the specific exclusion language, not just a yes/no — some exclusions are broader than others, and some apply only to certain types of AI use (e.g., generative AI specifically) rather than automation generally.
• Would a claim caused by an AI agent's autonomous action be treated differently from a claim caused by a human using an AI tool as an assistant? Some emerging exclusions distinguish between AI as a decision-support tool and AI acting with more autonomy — a distinction worth understanding for how your business actually uses these tools.
• Is there an affirmative AI-coverage option available — an endorsement, a technology E&O policy, or a cyber policy extension — and what would it cost? Treat the answer as time-sensitive and specific to your carrier; get it in writing and revisit it at each renewal rather than assuming last year's answer still holds.
• Does our current governance (an employee AI usage policy, vendor DPA review, human review steps) affect underwriting or claims outcomes? Some insurers factor documented AI governance into pricing or claims handling the same way they do general security controls.

Things to Consider

• This is a fast-moving area — treat any specific coverage detail as time-sensitive. Insurers are actively revising policy language and introducing new AI-specific products; a coverage gap confirmed at last year's renewal may have changed by this year's, in either direction.
• A confirmed coverage gap is a reason to close it deliberately, not just note it. If your broker confirms your current policies exclude AI-related claims, treat sourcing an endorsement or a technology E&O policy as an active decision, not something to revisit only after a loss occurs.
• This complements vendor-side risk management, but it's a different layer. Evaluating an AI vendor's data processing agreement and having an employee AI usage policy manage the risk of something going wrong; this page is about what happens financially if it does anyway.
• Documentation strengthens both governance and any eventual claim. A written AI usage policy, a record of vendor vetting, and evidence of human review steps around consequential AI-assisted decisions all support a claim if one is ever needed, on top of being good practice regardless.

Common Mistakes

• Assuming an existing general liability or E&O policy automatically covers AI-related mistakes because it covered ordinary human error before. As of 2026, this is exactly the assumption a growing number of policies no longer support — confirm it explicitly rather than inferring it from past coverage.
• Treating "we have cyber insurance" as equivalent to "we're covered for AI mistakes." Cyber policies are built around data breaches and security incidents; AI-related coverage is a separate question that depends on the specific policy's language, not something a cyber policy automatically includes.
• Waiting until after an incident to ask what's covered. Confirming coverage — and closing a gap with an endorsement or additional policy if needed — only works before a loss occurs; asking after the fact means finding out the hard way.
• Assuming the answer from one insurer, one policy type, or one country applies universally. Coverage details vary by carrier, policy wording, and insurance market — get a specific answer for your actual policies rather than relying on a general industry pattern.