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AI Liability Insurance: Approaches to Mitigating Generative Algorithmic Risk
- AI liability insurance is not currently a standalone policy, but is typically addressed through a combination of established insurance products
- It’s important that appropriate disclosures are made to insurers about the use of AI when arranging professional indemnity / tech E&O.
- Some insurers have started to provide affirmative cover for technology based companies, which reduces any ambiguity.
Legal and Insurance Frameworks
Artificial Intelligence is transforming how businesses make decisions, deliver services, analyse data, and automate complex workflows. However, the legal and insurance frameworks surrounding AI have not evolved at the same pace as the technology itself.
As businesses deploy generative AI, arguably a new category of liability is emerging. The insurance industry is currently adapting to a new environment where AI influences how potential claims arise and link to existing insurance products. Whilst the technology evolves rapidly, the regulatory landscape, legal liabilities and precedent typically follows one step behind.
As a business looking to use or develop artificial intelligence, it’s important to understand the potential risks, liabilities and insurance covers available. At Indemnity, we assist businesses navigate the rapidly evolving AI insurance landscape and secure specialist solutions tailored to their technology, regulatory obligations, and contractual commitments.
The AI Insurance Gap
When insurance policies neither specifically include nor exclude exposures, this can be referred to as ‘silent’ coverage.
As brokers we can seek to make the appropriate disclosures and clarify the intention of the drafting of the policy wording to gain comfort that the existing cover will provide cover to AI-related losses.
However, as AI adoption accelerates, insurers are becoming increasingly concerned about the unpredictability and aggregation potential of algorithmic losses specifically within Professional Indemnity and Tech E&O. With certain insurers now signalling that policies will not automatically respond to AI-related claims, without express clauses in the policy wording or by endorsement.
Who is legally responsible when using AI?
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If AI causes financial loss, regulatory breach, bodily injury, or emotional distress, responsibility will typically fall with business deploying the AI. Sufficient training, due diligence, and human oversight should be in place to mitigate the risks.
If coding errors occur, design flaws, inadequate disclaimers, or if the AI fails to operate as contractually required. It could also be the responsibility of the developer or supplier of the AI. Disclaimers can assist a legal defence, however the application will entirely be up to the court to access.
While the directors and senior management at either the business deploying the AI, or the developer / supplier of the AI, could also be held accountable. D&O insurance claims typically arise when the legal entity is not available to pursue a compensation claim under contract, but the directors are.
Unique AI Liability Risks
Hallucinations and Algorithmic Errors
Plausible but false information can be presented as truthful and accurate. Notable examples include legal cases where fake case law has been cited, such as in the case of Mata v. Avianca. ChatGPT did not retrieve actual cases from legal databases but instead fabricated non-existent precedents.
For example, if an AI-driven financial model makes a miscalculation, a client may suffer substantial financial loss. Given AI systems can scale rapidly, errors may affect hundreds or thousands of decisions simultaneously, potentially multiplying the liability risk.
Algorithmic Bias and Discrimination
Models are trained on large data sets, which can recreate or exacerbate discrimination against certain groups. This is most prevalent in areas such as credit scoring, recruitment, insurance pricing, and other decision making. Under the Equality Act 2010, businesses may be liable for indirect discrimination, even where no intent existed.
For example, an AI recruitment tool filters candidates based on patterns that disadvantage certain protected groups. The consequences may include an employment tribunal claim, regulatory scrutiny, compensation awards, and reputational damage.
Even if the discrimination originated within the algorithm’s training data, the business deploying it may be responsible.
Training Data IP & Copyright Infringement
Since the creation of generative AI, content creators have raised concerns that their intellectual property is being exploited. Books, music and images have all been used to train these models.
In September 2025, Anthropic AI agreed to settle a class action lawsuit brought by a number of authors for $1.5 billion, which alleged the illegal use of book content to train the foundation LLM. An estimated 500,000 books are covered by the settlement.
Unresolved legal questions surround the lawfulness of training data, ownership of AI-generated outputs, copyright infringement and trade mark risks.
Underwriting Questions for Businesses Deploying Bespoke AI
Q1) The output of the AI is not intended to constitute professional advice, including but not limited to, financial advice, legal advice, medical advice, and investment advice?
Insurers will not accept an affirmative answer at this moment in time.
Q2) The source of data ingested by the AI that you use is always verified/validated, by an authorised human employee, to ensure it is accurate?
Insurers will expect you to maintain a human within the control loop for data ingestion.
Q3) Do you regularly test/audit the AI that you use and its algorithm, to ensure your compliance with relevant data security regulations/controls are maintained?
Insurers will expect you to maintain a level of control that requires you to test and audit to ensure compliance within the industry sector.
Underwriting Questions for Businesses using Standard AI Tools
Q1) How do you currently use or plan to use AI in the future?
Insurers want to understand the use of AI within the business.
Q2) How is the generated information from AI vetted?
Insurers will expect you to maintain a human within the control loop for data ingestion.
Q3) Will this information be used internally or externally?
Insurers will expect you to maintain a level of control that requires you to test and audit to ensure compliance within the industry sector.
Other Products Impacted By AI-Related Claims
Why Choose Us?
Artificial Intelligence is creating an entirely new category of liability that sits between Professional Indemnity (Tech E&O), Cyber Insurance, and Management Liability. Understanding where these risks arise and where traditional insurance stops is becoming increasingly important.
Whether you are deploying AI, developing AI, or embedding AI into client facing services, as a specialist Technology Insurance Broker we help ensure your insurance programme evolves alongside the technology.
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