GENERATIVE AI INSURANCE ERRORS & OMISSIONS
COVERAGE PART 01 · THE "AI ERROR" TRIGGER

GENERATIVE AI ERRORS & OMISSIONS INSURANCE

When your AI is confidently wrong — a fabricated figure, an invented fact, a bad answer — and a customer relies on it, the loss lands on your company. This is affirmative coverage for inaccurate, incomplete, and fabricated AI output.

ELIGIBILITY · $10M+ ANNUAL REVENUE · PREMIUMS FROM $15K
⚠ AI ERROR Futuristic AI auto-coding screen with a glowing neural network generating code in real time CONFIDENT OUTPUT IS NOT THE SAME AS CORRECT OUTPUT
WHAT THIS COVERS

THE PROBLEM WITH A MACHINE THAT IS NEVER UNSURE

A generative model does not say "I don't know." It produces a fluent, confident answer every time — even when that answer is wrong. The industry calls it a hallucination, or confabulation. To your customer, it just looks like your company gave them bad information.

A Generative AI Error claim arises when your system produces output that is inaccurate, incomplete, or entirely fabricated, a third party relies on it, and that reliance causes a financial loss. The output looked authoritative. That is exactly what makes it dangerous.

It does not matter whether the error came from a chatbot answering a customer, a model drafting a client deliverable, or AI-generated code shipped into production. If the work went out under your name and someone was harmed by the mistake, the exposure is yours — and this is the coverage built to respond to it.

customer_support_assistant
> customer: can I still get the discounted rate if I apply after my trip?
> ai_assistant: Yes — you can submit your request for up to 90 days after travel and still receive the discount.
Policy actually requires approval before travel. The answer was fluent, instant, and wrong — and a customer relied on it.
THIS IS NOT HYPOTHETICAL

AI ERRORS ARE ALREADY PRODUCING REAL LIABILITY

Two of the most-cited AI cases to date are both, at their core, errors-and-omissions stories: a system gave confident, wrong information, and a court held the humans behind it responsible.

2024 · CIVIL RESOLUTION TRIBUNAL

THE CHATBOT THAT INVENTED A POLICY

An airline's support chatbot told a grieving passenger he could claim a bereavement fare after his trip. The published policy said the opposite. The tribunal found negligent misrepresentation and held the airline liable — flatly rejecting the argument that the chatbot was somehow a separate party responsible for its own words.

The business owns what its AI tells customers.
2023 · U.S. FEDERAL COURT

THE CITATIONS THAT NEVER EXISTED

Attorneys submitted a court brief built on case citations a generative model had fabricated. The authorities were not real. The court imposed sanctions — a now-standard cautionary tale about putting unverified AI output into work product that others rely on.

"The AI generated it" is not a defense.
INTERACTIVE · ERROR-TO-CLAIM PATHWAY

HOW A SINGLE WRONG ANSWER BECOMES A CLAIM

An AI error rarely looks like a disaster at the moment it happens. Walk the five steps from a fluent mistake to a liability claim — and see where affirmative coverage steps in.

WHY YOU CAN'T ASSUME E&O RESPONDS

THE FORMS WERE NOT WRITTEN FOR THIS

Professional liability was built around human professional negligence. A confident machine fabrication sits in a gap many forms never anticipated — and the market has started closing that gap by excluding AI, not covering it.

ISO CG 40 47 / CG 40 48

STANDARD-FORM EXCLUSIONS

Effective January 1, 2026, new ISO general liability endorsements let carriers carve generative AI out of standard commercial policies entirely — text, images, audio, video, and code.

PROFESSIONAL LIABILITY

E&O IS NOT IMMUNE

Some carriers have moved to exclude AI-related claims from professional liability as well. Whether your specific E&O still answers "yes" depends on the carrier, the wording, and your renewal date.

SILENT vs AFFIRMATIVE

BUILT TO RESPOND ON PURPOSE

A standalone Generative AI Error policy is written to cover this exposure affirmatively — defense costs and damages from a reliance-based AI mistake — rather than leaving it to silent or excluded language.

INTERACTIVE · TAP TO REVEAL

FOUR THINGS BUSINESSES ASSUME ABOUT AI ERRORS

Each card is a common assumption we hear. Tap to turn it over.

ASSUMPTION

"Our E&O already covers anything our staff produces."

TAP TO FLIP ↻
THE REALITY

Most E&O forms predate generative AI, and some carriers now exclude AI claims outright. Coverage for an AI error is increasingly something you confirm, not assume.

ASSUMPTION

"If the AI got it wrong, that's the vendor's problem."

TAP TO FLIP ↻
THE REALITY

Courts have placed responsibility on the business that deployed the tool, not the model's maker. The output went out under your name, so the claim comes to you.

ASSUMPTION

"Someone skims the output, so we're covered."

TAP TO FLIP ↻
THE REALITY

A quick glance does not catch a fluent fabrication, and it does not create coverage. Human review lowers frequency and helps underwriting — it does not replace the policy.

ASSUMPTION

"This only matters for actual AI companies."

TAP TO FLIP ↻
THE REALITY

Any established business that lets AI touch customer-facing work carries the error exposure — marketing, support, advisory, software, operations. You do not have to build AI to be liable for it.

FROM YOUR INTERNAL AUDIT

WHERE AI ERRORS ACTUALLY HIDE

Start by asking where AI output reaches a customer. Most error exposure is sitting in routine, everyday workflows your team may not even flag as "AI."

CUSTOMER-FACING ANSWERS

Support chatbots and AI assistants that quote prices, policies, eligibility, or specifications directly to customers in real time.

CLIENT DELIVERABLES

Reports, analyses, designs, and recommendations drafted with AI and delivered as your firm's professional work product.

AI-GENERATED CODE

Code written or completed by AI and shipped into the products and systems your customers depend on.

RESEARCH & SUMMARIES

AI-summarized facts, figures, and citations that feed decisions — where an invented detail can travel a long way before anyone checks.

QUOTES & CALCULATIONS

AI-assisted pricing, estimates, and calculations that customers act on, where a wrong number becomes a wrong commitment.

AUTONOMOUS WORKFLOWS

Agentic tools that generate and act on output with no human approving each step — the highest-severity version of this exposure.

⚠ AGENTIC = INSTANT YES
WHO WE PLACE THIS FOR

BUILT FOR ESTABLISHED, AI-RELIANT BUSINESSES

This affirmative market is designed for companies at scale, where AI-assisted work already reaches customers and a single error can carry real financial weight.

ELIGIBILITY AT A GLANCE

MINIMUM SIZE FOR THIS MARKET

$10M+Minimum annual revenue
$15KMinimum premium
THE FULL COVERAGE MAP

PART OF THE GENERATIVE AI INSURANCE STACK

Errors & omissions is one trigger. Explore how it connects to the rest of the cluster.

FREQUENTLY ASKED

GEN AI ERRORS & OMISSIONS QUESTIONS

WHAT EXACTLY IS A "GENERATIVE AI ERROR" CLAIM?
It is a claim arising when your AI system produces inaccurate, incomplete, or fabricated output, a third party relies on that output, and the reliance causes a financial loss. The defining feature is reliance on a confident answer that turned out to be wrong.
ISN'T THIS THE SAME AS MY TECH E&O POLICY?
Not necessarily. Traditional E&O was written around human professional negligence and predates generative AI. Some carriers have begun excluding AI-related claims from professional liability, and standard general liability forms now offer AI exclusions as of January 2026. Affirmative coverage is built to respond to AI error on purpose; we review your wordings to find the gap.
DOES A HUMAN REVIEWING THE OUTPUT REMOVE THE RISK?
It reduces the frequency of errors reaching customers and it strengthens your underwriting profile, but it does not eliminate the exposure or create coverage on its own. A fluent fabrication can slip past a quick review, which is exactly why affirmative coverage matters alongside good process.
WE ONLY USE AI INTERNALLY. ARE WE STILL EXPOSED?
The key question is whether AI-assisted output ever reaches a customer or the public, even indirectly. Internal drafts that become client deliverables, or code that ships into products, carry error exposure. A short internal audit of where AI output travels is the right starting point.
IS THERE A MINIMUM COMPANY SIZE FOR THIS COVERAGE?
Yes. This market is built for established businesses, with a minimum of $10 million in annual revenue and premiums starting at $15,000. If you are below that threshold but still rely on AI, reach out anyway and we will talk through your exposure and other options.
HOW DO I GET A QUOTE FROM KELLY INSURANCE GROUP?
Book an appointment or start an intake form and describe how AI is used in your business and where its output reaches customers. We map the error exposure, review your controls, and take a structured submission to the specialty markets writing affirmative AI coverage. Call or text (412) 212-2800.
Kelly Insurance Group is a specialty commercial insurance brokerage. This page is general information about generative AI errors and omissions exposures and is not legal advice, a coverage opinion, or a guarantee that any policy will respond to a particular loss. Coverage triggers, terms, exclusions, and availability vary by carrier and by deployment; the ISO endorsements referenced (CG 40 47 and CG 40 48, effective January 1, 2026) are optional forms individual carriers may or may not adopt. Case references, including Moffatt v. Air Canada (2024 BCCRT 149), are summarized for illustration. Always review the actual policy wording for terms, conditions, and exclusions.