Commercial Insurance Review · AI Error and Reliance Exposure

Generative AI Errors & Omissions Insurance Review

Generative AI errors and omissions insurance review is for businesses using AI tools, chatbots, copilots, AI-assisted code, automated research, generated reports, or large language model output in work that customers may rely on. The risk is not that AI makes a typo. The risk is that AI gives a confident answer, a customer treats it as your company’s answer, and the mistake causes financial harm.

What this covers

The problem is not “AI.” The problem is a bad answer that someone relies on.

A generative AI error claim usually has a simple chain: output, reliance, financial harm, and a demand against the business. It can involve a support chatbot, a proposal, a report, an AI-assisted calculation, generated code, a research summary, or a recommendation that leaves the company under your name.

Customer support Chatbot gives the wrong answer

A chatbot states the wrong policy, deadline, eligibility rule, warranty term, rate, or customer instruction.

Professional work AI-assisted deliverable is wrong

A report, memo, design, analysis, plan, or recommendation contains a fabricated fact or unsupported conclusion.

Technology Generated code creates failure

AI-assisted code, configuration, documentation, or integration work moves into production and causes customer harm.

Autonomy AI acts before anyone catches it

An AI agent sends, updates, routes, recommends, calculates, or triggers workflow steps before a person approves the output.

customer_support_assistant

> customer: Can I submit this request after the deadline and still qualify?

> ai_assistant: Yes. You can submit it up to 90 days later and still qualify.

The actual rule requires approval before the deadline. The answer sounded confident, looked official, and became the basis for a customer decision.

Real-world reference Chatbot misinformation can become business responsibility

Moffatt v. Air Canada is a useful reminder that a business can be held responsible when a customer relies on incorrect information supplied by a customer-facing chatbot.

Professional-work reference Fabricated citations can still create real consequences

Mata v. Avianca is a cautionary example of generative AI producing fabricated legal authorities that were placed into professional work product and resulted in sanctions.

Interactive Graphic · AI Error Claim Builder

Build the claim path by selecting what actually happened

Select the factors that apply to your workflow. The graphic shows how a wrong AI answer becomes more serious as it moves from an internal draft to customer reliance, financial loss, and autonomous action.

Toggle the claim factors

This is not a quote and does not decide coverage. It is a compact way to identify which facts matter before the policy wording can be reviewed.

Wrong output identified

A bad answer alone is the starting point. The review becomes more urgent when that answer reaches a customer, drives reliance, or creates a financial loss.

Output Reliance Loss Agentic
Interactive generative AI error claim path A visual path showing AI output moving to customer reliance, financial loss, claim demand, and coverage review. 1 Output wrong answer 2 Audience internal draft 3 Reliance not confirmed 4 Claim Review E&O wording CURRENT PATH OUTPUT ERROR REVIEW STARTS WITH E&O / AI WORDING Error-claim review priority Start by mapping where the AI output went and who reviewed it.
Why policy wording matters

Do not assume traditional E&O automatically follows AI output

Errors and omissions coverage should be reviewed closely when AI output becomes customer work. Some policies may be silent, some may be limited by professional-services language, some may depend on the type of work being performed, and some programs may include AI-related limitations or exclusions. Public insurance-industry reporting also describes optional Verisk/ISO generative AI endorsements carriers may use in general liability programs. The practical point is simple: the actual wording controls.

Where AI errors hide

The exposure often lives in routine workflows

A business does not need to sell AI software to create an AI error problem. If AI output becomes part of a customer answer, client deliverable, codebase, analysis, recommendation, calculation, or automated workflow, it deserves a coverage review.

Chatbots Customer-facing answers

Support assistants that quote policies, deadlines, eligibility rules, refund terms, warranty conditions, product specs, or account guidance.

Professional services Reports and recommendations

AI-drafted reports, summaries, financial assumptions, technical recommendations, legal-adjacent research, design concepts, or advisory work.

Software AI-generated code

AI-assisted code, configuration, scripts, documentation, or integrations that become part of a product or system a customer relies on.

Numbers Quotes and calculations

AI-assisted estimates, rates, dates, figures, measurements, recommendations, forecasts, or calculations that influence a business decision.

Research Summaries and citations

AI summaries that misstate sources, invent references, omit important limitations, or present unsupported information as established fact.

Agents Automated workflow decisions

AI agents that send, route, update, approve, calculate, or trigger work without review can turn one error into a repeated error at scale.

What to gather before the appointment

A stronger review starts with the output trail

The most useful broker conversation is specific. Bring examples of the tools, the output, who reviewed it, where it went, and what a customer could rely on.

AI tool inventory

List chatbots, copilots, AI assistants, code tools, research tools, document tools, internal models, vendor AI features, and AI agents.

Output destinations

Identify whether output reaches customers, websites, emails, reports, contracts, support tickets, codebases, dashboards, or automated workflows.

Reliance points

Flag where a customer or user may act on AI-generated advice, instructions, figures, deadlines, policy statements, or recommendations.

Human review rules

Document who checks AI output before it leaves the business and which outputs require manager, technical, legal, or subject-matter review.

Prompt and output logs

Preserve prompts, source materials, outputs, edits, approvals, timestamps, user IDs, and correction records when available.

Vendor terms

Review tool terms, data handling, output ownership, indemnity, limitation language, reliability disclaimers, and model-change terms.

Incident response

Know who corrects wrong output, notifies affected customers, preserves evidence, contacts carriers, and prevents a repeated mistake.

Coverage stack

Compare E&O, technology E&O, cyber, media liability, general liability, umbrella/excess, and AI-specific wording.

Related coverage pages

Find the AI insurance issue connected to the error

Search the coverage map below. These are normal crawlable HTML links first, with a small on-page filter for visitors who want to move quickly.

No matching page found. Try “chatbot,” “code,” “E&O,” “agent,” “data,” “governance,” or “technology.”

Why Kelly Insurance Group

AI error exposure needs a broker who can organize the facts

A clean review connects the AI workflow to the policy wording: what the tool generated, where the output went, who relied on it, what records exist, and which policy part may respond.

Our team of agents

Kelly Insurance Group is proud of its team of agents. For AI errors and omissions exposure, the value is in asking specific questions, organizing the output trail, and helping the account make sense before coverage is discussed.

Meet the team

Insurance lineage since 1881

The agency’s history traces back to an insurance lineage beginning in 1881. New technology still needs old-fashioned discipline: facts first, wording second, assumptions last.

Read our history

Client portal convenience

Once you are a customer, most customers are given access to the Kelly Insurance Group custom client portal, where policy documents and certificate tools can be available, including certificate of insurance functions when enabled.

Client portal
Start the review

Tell us where AI output reaches customers

The most useful first conversation is specific. Tell us what AI creates, who reviews it, whether it reaches customers, whether anyone relies on it, whether code ships into production, and whether any AI agent can act without approval at every step.

1

Book a conversationUse the appointment link when you are ready to walk through AI-generated output, reliance, controls, and coverage questions.

2

Bring real examplesChatbot flows, generated reports, AI-assisted code, review rules, prompt logs, customer complaints, and vendor terms are useful.

3

Compare the coverage stackThe review compares AI error exposure against E&O, technology E&O, cyber, media liability, general liability, umbrella/excess, and AI-specific wording.

Questions businesses ask

Generative AI errors and omissions questions

What is a generative AI error claim?
It is a claim or demand connected to inaccurate, incomplete, fabricated, outdated, or unsupported AI output that someone relied on. The issue is not only that AI was wrong; the issue is that the wrong output reached a person, contract, deliverable, system, or decision path where it caused harm.
Is this the same as traditional E&O insurance?
Not automatically. Traditional E&O wording should be reviewed, especially when AI output becomes customer work, code, advice, analysis, or automated workflow activity. The actual policy forms, definitions, exclusions, endorsements, and claim facts decide whether coverage may apply.
Does human review remove the exposure?
Human review can reduce the chance that a bad AI answer reaches a customer, and it can help explain the risk to underwriters. It does not create coverage by itself and does not guarantee that every fluent fabrication will be caught.
What if AI is only used internally?
Internal use still deserves review if the output later becomes customer-facing work, shipped code, a report, a recommendation, a calculation, a quote, a contract input, or a workflow decision. The right question is where the output travels after it is created.
What if a vendor AI tool caused the wrong output?
Vendor involvement does not end the review. The business should review vendor terms, output ownership, indemnity language, limitation language, data handling, model-change terms, and whether the business used or published the output under its own name.
What records help with the insurance review?
Helpful records include the AI tool inventory, chatbot scripts, prompt/output logs, human review rules, customer-facing workflows, generated reports, code review records, vendor terms, incident response plans, and examples of how AI output is approved before use.
How do I start with Kelly Insurance Group?
Book an appointment and prepare a short summary of how AI is used, what output is generated, whether that output reaches customers, who reviews it, whether customers rely on it, and whether any AI workflow can act without approval at every step.
Public reference points

Risk-management language that helps the conversation

These resources are included for general risk-management context. They are not insurance policy wording and do not determine whether a specific claim is covered.

This page provides general insurance information for businesses evaluating generative AI errors and omissions insurance review, AI hallucination insurance review, AI chatbot liability, AI-generated code E&O, AI professional liability, AI output reliance, AI customer-support error exposure, AI report and research error exposure, AI calculation error exposure, AI vendor tool error exposure, agentic AI error exposure, technology E&O, cyber insurance, and AI-specific coverage wording. It is not legal advice, not a coverage opinion, and not a guarantee that any policy will respond to a particular claim or event. Coverage depends on the actual policy forms, endorsements, exclusions, underwriting, contracts, facts, jurisdiction, and carrier position.

Disclaimer: Coverage availability and eligibility may depend on many factors, including underwriting review, carrier guidelines, policy terms, state requirements, business operations, risk characteristics, and other information provided during the application or quoting process. Kelly Insurance Group cannot guarantee that every individual, customer, organization, or business seeking coverage will qualify for, receive, or successfully place insurance coverage. All policy coverages, exclusions, conditions, limits, endorsements, and terms should be carefully reviewed by the consumer, insured, or applicant to confirm that the coverage requested is the coverage being quoted, offered, or provided. Insurance coverage, policy changes, endorsements, cancellations, and other policy terms are not bound, changed, confirmed, or altered unless and until written confirmation is provided by a licensed Kelly Insurance Group team member, the applicable insurance carrier, or an authorized underwriter. This page is provided for general informational purposes only and does not provide legal advice, legal opinions, insurance coverage opinions, or policy interpretations. Information on this page should not be relied upon as a substitute for reviewing the actual policy language or consulting appropriate professional advisors. Kelly Insurance Group does not employ, supervise, or direct attorneys.