AI Liability Coverage for Software Companies: What Happens When the Model Gets It Wrong

What AI claims are software companies actually seeing?

The claims splitting out so far fall into four buckets. Performance claims, where a model produced wrong outputs and a customer suffered financial loss. Intellectual property claims, concerning training data and generated output that resembles protected work. Discrimination and regulatory claims, particularly where models influence hiring, lending, insurance, or housing decisions. And privacy claims, where personal data entered a model or was exposed through it. Each of these lands on a different policy, and none of them lands cleanly.

• Erroneous output causing customer financial loss, which points to technology errors and omissions
• Copyright and intellectual property claims over training data and generated content
• Algorithmic bias and disparate impact claims in regulated decision making
• Privacy claims where personal or confidential data was ingested, retained, or leaked through a model
• Contractual claims for failure to meet accuracy, uptime, or explainability commitments
• Regulatory inquiries under state AI, privacy, and consumer protection statutes

Does technology errors and omissions cover AI failures?

Sometimes, and less clearly than it should. A tech E&O policy responds to a negligent act, error, or omission in the performance of technology services or the failure of a technology product to perform its intended function. A model that produces an incorrect output arguably fits that language. The problem is that carriers have begun adding express AI exclusions, and some forms now carve out claims arising from generative artificial intelligence, machine learning outputs, or automated decision making. Reading the exclusion page has become as important as reading the insuring agreement.

• Look for any exclusion naming artificial intelligence, machine learning, generative models, or algorithmic output
• Look for affirmative grants, which some carriers now offer for disclosed AI use
• Check whether the definition of technology products and services expressly includes AI features
• Confirm coverage for contractual liability, since many AI disputes start as breach of contract
• Verify whether defense costs sit inside or outside the limit

Where do cyber and media liability fit?

Cyber liability handles data breach and network security. It is the right policy when a model exposed personal data, when training data was exfiltrated, or when an AI enabled attack hit your environment. Media liability, often embedded in tech E&O, handles content based claims including copyright, trademark, and defamation, which is exactly where generated output claims land. Many software companies carry a combined tech E&O and cyber form, which is good, but the media section often carries a lower sublimit and that sublimit is now the one under pressure.

• Cyber: privacy liability, breach response, business interruption, extortion, and regulatory defense
• Media: copyright, trademark, defamation, and disparagement arising from content
• Generated output claims typically implicate media liability rather than the core E&O grant
• Check the media sublimit, which is frequently 1 million dollars against a 5 million dollar E&O limit
• Confirm that customer data processed through third party model providers is covered under your privacy grant

What about vendor and third party model risk?

Most companies do not train their own foundation models. They build on someone else's, which means the failure modes you are liable for include failures you did not create. Your customer contracts almost certainly make you responsible for the whole stack, while your upstream provider's terms of service almost certainly cap their liability at a trivial multiple of fees paid. That asymmetry is a balance sheet exposure, not a legal technicality, and insurance is the practical way to bridge it.

• Map which models and providers touch customer data and customer facing outputs
• Read upstream liability caps, which are often limited to 12 months of fees paid
• Align your customer facing warranties with what your upstream provider actually commits to
• Confirm your E&O covers claims arising from services performed by subcontractors and vendors
• Require your vendors to carry tech E&O and cyber, and to name you as additional insured where possible
• Document human review steps, since carriers price favorably for a human in the loop on consequential decisions

What should you negotiate at your next renewal?

Bring your AI use to the underwriter proactively. Companies that disclose what models they use, for what purposes, with what human oversight, are getting affirmative coverage grants. Companies that stay quiet are getting exclusions applied by default. Prepare a short written description of your AI features, your data handling, your testing and evaluation process, and your human review controls, and treat it as an underwriting submission document rather than a marketing page.

• Disclose AI usage in writing and request an affirmative coverage grant rather than silence
• Push back on broad AI exclusions and seek narrowing language limited to undisclosed uses
• Raise the media liability sublimit if you ship generative features
• Confirm bodily injury carve backs if your product influences physical world decisions
• Review limits against your largest customer contract's liability cap, which is a practical floor
• Add or increase regulatory defense coverage, since state AI statutes are expanding quickly

Ready to review your AI coverage position?

Grandbay Financial Services helps software companies read the AI language now appearing in technology and cyber forms, and we prepare the disclosure package underwriters want to see. If your renewal is within 120 days, this is the right time to start. Schedule a review at calendly.com/grandbayfinancial.