By Ryan Windt | Head of Growth Marketing | Updated June 2026
AI is everywhere. It is in your product, your workflow, your client deliverables, and increasingly your contracts. And as AI adoption accelerates, so does the legal and financial exposure for the technology companies building and deploying it.
When an AI-driven tool produces a wrong output, a biased recommendation, or a failure that costs a client money, someone gets sued. That someone is usually the technology provider. This post breaks down the specific risks AI creates for tech companies, how Technology Errors and Omissions (Tech E&O) insurance responds, what the major carriers are actually doing with AI in their policy forms right now, and what to look for in your coverage if you are building or deploying AI today.
What Is Tech E&O Insurance?
Technology Errors and Omissions insurance, also called Tech E&O or professional liability for technology companies, covers claims that your technology product or service failed to perform as promised and caused a client financial harm.
If your software crashes and a client loses a day of revenue, that is a Tech E&O claim. If your platform gives a wrong recommendation that leads to a bad business decision, that is a Tech E&O claim. If your AI model produces a biased output that exposes a client to a discrimination lawsuit, that can be a Tech E&O claim.
Tech E&O is distinct from cyber insurance, which covers losses from security incidents such as breaches, ransomware, and business interruption from an attack. Tech E&O covers performance failures. Many technology companies need both, and the two are increasingly bundled together because the line between a security incident and a performance failure is often blurry in practice.
How AI Is Changing the Risk Landscape for Tech Companies
Traditional Tech E&O claims were relatively straightforward. Software had a bug. A system went down. A service was not delivered. The failure was identifiable and the causation was usually clear.
AI introduces a fundamentally different risk profile.
AI systems can fail in ways that are invisible until they cause harm. A model that gradually drifts from accurate to inaccurate outputs may not trigger an obvious error. It just quietly produces wrong answers until someone loses enough money to notice.
AI decisions are difficult to explain. When a client asks why your algorithm made a specific recommendation that cost them money, “the model determined it” is not a defensible answer in court. Explainability requirements are tightening both legally and contractually.
AI bias creates regulatory and civil liability. If your AI tool produces outcomes that systematically disadvantage a protected class in hiring, lending, healthcare triage, or any other high-stakes context, you are exposed to both regulatory investigation and class action litigation.
AI is increasingly embedded in mission-critical operations. When an AI-driven logistics platform fails, deliveries stop. When an AI-driven risk model misfires, financial decisions are made on bad data. The downstream consequences of AI failure are often larger and faster than traditional software failures.
The Specific AI Risks Tech E&O Covers
Model Errors and Faulty Outputs
This is the core coverage scenario. Your AI system produces an incorrect prediction, recommendation, or classification that a client relies on, and they suffer a financial loss as a result. Tech E&O covers your legal defense and any resulting damages or settlements.
Common examples include diagnostic tools in healthcare that miss a condition or suggest the wrong treatment protocol, financial modeling tools that generate inaccurate projections, fraud detection systems that fail to flag a transaction or flag a legitimate one, and recommendation engines that steer users toward harmful or inappropriate content.
Algorithmic Bias and Discrimination Claims
Regulators and plaintiffs’ attorneys are increasingly sophisticated about AI bias. If your model produces outcomes that have a disparate impact on a protected class, regardless of whether that was intentional, you face potential liability.
This is particularly acute in hiring technology (resume screening tools), lending platforms (credit scoring and approval tools), insurance technology (pricing and eligibility models), and healthcare AI (triage, diagnosis, and treatment recommendation tools).
Tech E&O can cover legal defense costs, regulatory investigations, and settlements arising from these claims.
System Failures and Downtime
If your AI platform is a core part of a client’s operations and it goes down, the business interruption losses they experience may come back to you as a damages claim. Tech E&O covers your exposure when client losses result from your technology failing to perform.
Scope Creep and Contract Liability
AI projects frequently evolve beyond their original scope. When a client argues that your tool did not deliver what was promised, whether that is accuracy rates, uptime, or specific functionality, Tech E&O covers the resulting dispute.
AI Claim Scenarios: Which Policy Responds and What the Outcome Looks Like
These scenarios are drawn from the types of claims Tech E&O carriers are seeing as AI adoption increases. Each one illustrates where coverage applies, where it does not, and where the policy language matters most.
Scenario 1: Healthcare AI misses a diagnosis. A healthtech company’s AI-assisted triage tool fails to flag a high-risk patient. The patient’s condition worsens and they pursue a claim against the hospital, which in turn brings the technology vendor in. The tech vendor’s Tech E&O policy covers legal defense and any settlement attributable to the tool’s failure. Key issue: does the policy’s definition of “professional services” include AI model outputs, or does it only cover implementation services? Carriers vary on this.
Scenario 2: Financial AI generates inaccurate projections. A SaaS platform providing AI-driven financial forecasting produces materially wrong revenue projections. A client makes a capital allocation decision based on those projections and loses $2.1M. They sue the SaaS company for the loss. Tech E&O covers the claim. Key issue: were the projections presented as AI-generated estimates or as guaranteed outputs? Contract language around accuracy representations determines whether the carrier defends the claim or disputes coverage.
Scenario 3: Hiring AI produces biased screening outcomes. A recruiting software company’s resume screening tool is found to systematically reject candidates from certain universities that correlate with race. A class action follows, and the EEOC opens an investigation. Tech E&O covers the legal defense and regulatory proceedings. Key issue: some carriers have begun adding exclusions or sublimits specifically for AI bias claims. If your product operates in hiring, lending, or healthcare, check whether your policy has any such restriction.
Scenario 4: LLM-powered product produces harmful output. A company builds a customer service chatbot on top of a third-party large language model. The chatbot gives a user incorrect medical advice that leads to a harm claim. The technology vendor is named in the lawsuit. Coverage depends on how the policy defines the “technology services” being provided and whether third-party AI components are within scope. This is an unsettled area across carriers.
Scenario 5: AI model trained on proprietary data. A client claims that the vendor’s AI model was trained on their proprietary data without authorization and that the model’s outputs constitute misappropriation. Standard Tech E&O may not cover IP claims of this type. This is one of the clearest gaps in current AI coverage, and it is worth a direct conversation with your underwriter if your training data sourcing could be questioned.
How Major Carriers Are Handling AI in Tech E&O Right Now
The market is not uniform on AI. Carriers are taking meaningfully different approaches to AI-related Tech E&O exposure, and the differences matter for technology companies whose products are AI-driven.
Coalition. Coalition’s bundled cyber and Tech E&O form does not currently have broad AI-specific exclusions for most technology company accounts. Their underwriting approach focuses on the risk profile of the insured’s technology services generally rather than treating AI as a separate category. For companies building AI into existing software products, this tends to work in their favor. Coalition’s external attack surface monitoring also means they have visibility into your infrastructure posture, which they weigh alongside the nature of your services.
At-Bay. At-Bay has been active in the technology sector and their Tech E&O appetite extends to AI-driven companies. Their underwriters are asking more specific questions about AI use cases at application, particularly for healthcare and financial services applications, and are pricing accordingly. Companies with documented bias testing and model monitoring practices tend to fare better in their process.
Chubb. Chubb offers more customizable Tech E&O forms and has been developing AI-specific endorsements and coverage language for larger technology accounts. For enterprise AI companies with significant revenue, complex contracts, or international exposure, Chubb’s ability to customize policy language is valuable. Their underwriters engage directly on AI risk in a way that smaller digital-first carriers typically do not.
Beazley. Beazley is one of the most experienced Tech E&O markets globally and has been thoughtful about AI liability. They have developed specific coverage language addressing AI system failures and are ahead of most markets in their ability to structure coverage for companies with material AI exposure. For mid-market and larger AI companies, particularly those in regulated industries, Beazley is worth including in any market comparison.
What this means for buyers. If your product is AI-driven, do not assume your current Tech E&O policy was written with your current exposure in mind. A policy written two years ago almost certainly was not. At renewal, ask your broker to pull the specific policy language around AI-generated outputs, algorithmic decisions, and third-party model components. The differences between carriers on these points are material.
What Tech E&O Does Not Cover
Understanding the limits of Tech E&O is as important as understanding what it covers.
Cyber incidents are separate. A ransomware attack that takes your platform offline is a cyber claim, not a Tech E&O claim. A data breach that exposes client data is a cyber claim. You need both policies if you want complete protection.
Intentional wrongdoing is excluded. If a claim alleges fraud or deliberate misrepresentation, Tech E&O will not respond.
Bodily injury and property damage have limited coverage. Traditional Tech E&O is focused on economic and financial harm. If your AI system contributes to a physical injury in a medical device context, the exposure may fall outside standard Tech E&O and require specialized coverage.
Intellectual property infringement. If a client claims your AI model was trained on their proprietary data without authorization, or that your outputs infringe on copyrighted material, standard Tech E&O may not cover it. AI-specific IP exposure is an emerging and unsettled area of coverage that deserves close attention in your policy review.
How the AI Regulatory Environment Is Raising the Stakes
The legal and regulatory landscape around AI liability is moving fast, and it is moving toward more accountability for technology providers.
The EU AI Act is the most comprehensive AI regulation currently in force. It creates tiered requirements based on risk level and places significant obligations on providers of high-risk AI systems, which includes tools used in healthcare, financial services, employment, and critical infrastructure. U.S. companies selling into the EU are subject to it.
The FTC has signaled increasing scrutiny of algorithmic accountability and has brought actions against companies whose AI tools produced discriminatory or deceptive outputs. The CFPB has issued guidance requiring explainability for credit-related AI decisions.
Several states including California, Colorado, and Illinois have passed or are advancing AI-specific legislation covering transparency, bias auditing, and consumer rights.
Client contracts are also evolving. Enterprises increasingly include specific AI performance warranties, accuracy benchmarks, audit rights, and liability clauses in technology vendor agreements. If your contract promises an accuracy rate and your model underperforms, you have contractual exposure on top of tort exposure.
The practical implication: the risk of an AI-related Tech E&O claim is higher today than it was two years ago, and it will be higher two years from now than it is today.
What to Look for in Your Tech E&O Policy If You Are Building AI
AI-specific coverage language. Some carriers have begun including explicit coverage for AI-related claims. Others have added exclusions for certain AI risks. Read the policy language carefully, as a generic Tech E&O policy written three years ago may not contemplate your current AI exposure.
Scope of covered services. Make sure your policy’s definition of covered technology services includes AI development, training, deployment, and ongoing model management. If you have added AI capabilities to your product since your last renewal, confirm they are within scope.
Regulatory defense coverage. If you operate in a regulated industry or sell to clients in regulated industries, confirm your policy covers regulatory investigations and proceedings, not just civil litigation.
Sublimits on specific claim types. Some policies apply lower sublimits to specific claim categories. Know what your actual coverage is for a bias claim, a model failure claim, and a regulatory investigation, not just the headline limit.
Retroactive date. Claims-made policies only cover claims arising from services provided after the retroactive date. If you have been providing AI-related services for several years, make sure your retroactive date reflects that history.
Tech E&O vs. Cyber: Why AI Companies Often Need Both
| Scenario | Tech E&O Responds | Cyber Responds |
|---|---|---|
| AI model produces wrong output, client sues | Yes | No |
| Ransomware takes your platform offline | No | Yes |
| Data breach exposes client data | No | Yes |
| Client claims AI tool did not perform as promised | Yes | No |
| Bias claim from affected third party | Yes | No |
| Business interruption from your own system failure | Yes (client claims) | Yes (your losses) |
| Regulatory investigation for AI discrimination | Yes | No |
| Social engineering attack results in wire fraud | No | Yes |
The overlap zone, where both policies may be relevant, is growing as AI systems become more deeply embedded in business operations. A single incident can trigger both a performance claim and a security investigation simultaneously. For a full breakdown of how the two policies coordinate, see our guide to Tech E&O vs. cyber insurance.
Frequently Asked Questions
Does my existing professional liability policy cover AI claims?
It depends on the policy language. Traditional professional liability was written for service businesses such as consultants, accountants, and lawyers. Tech E&O is the technology-sector equivalent and is specifically designed to cover software and technology product failures. If you are a technology company, generic professional liability is likely inadequate for AI-related exposure.
We are a small AI startup. Do we need Tech E&O already?
Yes, and in many cases you need it before you think you do. Enterprise clients frequently require Tech E&O as a condition of signing a vendor agreement. If you are pitching to any company with a procurement or legal team, expect to provide a certificate of insurance. Getting covered before you need it for a contract avoids a last-minute scramble.
How is Tech E&O priced for AI companies?
Underwriters look at the type of AI you are building, the industries you serve, the risk level of the decisions your AI influences, and the strength of your QA and testing processes. High-risk AI, meaning tools that influence healthcare, financial, or employment decisions, carries higher premiums than lower-stakes applications. Documented bias testing, model monitoring, and explainability practices can positively impact your rate.
What is the difference between Tech E&O and product liability?
Tech E&O covers economic and financial harm resulting from technology failures. Product liability covers physical injury or property damage from a defective product. For AI systems embedded in physical devices such as medical equipment, autonomous vehicles, or industrial machinery, you may need both.
Does Tech E&O cover open-source AI models we have built on top of?
This is an emerging area with limited case law. Carriers are evaluating it differently. If your product relies heavily on third-party or open-source foundation models, discuss this specifically with your underwriter to confirm how your policy responds to a claim that originates from a defect in the underlying model.
Related Resources
• Technology Errors and Omissions Insurance: A Plain-English Guide for Tech Companies and MSPs
• Tech E&O vs. Cyber Insurance: How Each Policy Responds Across Real-World Scenarios
• Tech E&O for MSPs: Coverage, Limits, and How It Coordinates with Cyber
• Cyber Insurance for Tech Companies
• Cyber Insurance Exclusions: What Most Policies Won’t Cover
• What Underwriters Look For in a Cyber Insurance Application
AI liability is one of the fastest-moving areas in Tech E&O underwriting, and the coverage terms available vary significantly by carrier. If you want to understand how your current policy handles AI-related errors or want to see what the market offers for your specific product, contact SeedPod Cyber.