Why captives should prepare for AI liability risks

By Randy Sadler

Artificial intelligence has moved beyond proof of concept. Businesses are adopting it at a record pace, from customer service to medical diagnostics. Yet as adoption accelerates, so do the risks and few companies have addressed who will be accountable when things go wrong.

The challenge is not only the potential for harm but an undefined and increasingly litigious liability landscape. When algorithms produce biased results or chatbots dispense faulty medical advice, it is unclear whether responsibility falls on the company deploying the tool or the developer behind it. For businesses that rely heavily on AI, particularly those with captive insurance companies, now is the time to examine these risks and consider how captives can close a widening protection gap.

AI failures already have consequences — and lawsuits

The idea that AI risks are distant or theoretical no longer holds. In 2024, a federal judge allowed a class-action lawsuit to proceed against Workday, a major provider of AI-driven hiring software, after a job applicant alleged the platform rejected him based on age, race, and disability. The suit, backed by the Equal Employment Opportunity Commission, raised difficult questions about accountability when automated tools produce biased outcomes. Workday argued it only supplied the software, not the hiring decisions, while plaintiffs claimed the technology itself was discriminatory.

The EEOC has since clarified that employers, not technology vendors, typically bear responsibility for civil rights violations tied to AI hiring tools. Together, these developments highlight a clear trend: AI is being deployed in decisions with legal and regulatory consequences, and the fallout — whether reputational, financial or compliance-related — usually falls on the business using the system.

A legal and regulatory framework is forming

The global regulatory environment is evolving quickly. In March 2024, the European Union adopted the EU AI Act, the first comprehensive legal framework for AI. In the U.S., states like California and New York are proposing laws targeting AI bias and safety. Several federal agencies, including the FTC and the Department of Justice, have made it clear that existing laws, from consumer protection to antitrust, apply to AI.

In Deloitte’s Q3 2024 global survey of 2,700 senior executives, 36 percent cited regulatory compliance as a top barrier to deploying generative AI. Yet less than half were actively monitoring regulatory requirements or auditing their AI tools. The gap between risk awareness and preparedness is widening, and businesses with captives are in a unique position to act.

The role of captives in addressing AI liability

Captive insurance is not a replacement for commercial coverage but an important complement for emerging risks the traditional market is reluctant to underwrite. Because captives are owned by the businesses they insure, they can tailor policies to actual AI use and risk tolerance.

A captive can cover defense costs and settlements tied to AI errors that fall outside cyber or general liability policies, such as liability for generative AI marketing content or discrimination claims from algorithmic hiring tools. Captives may also fund regulatory response costs or administrative fines where permitted, and respond when third-party AI vendors fail and indemnification falls short, reimbursing the parent company for business interruption or revenue losses.

Building AI into captive strategy

To incorporate AI risk effectively, captive owners must assess their exposure. This requires collaboration across legal, compliance, IT, risk management and business units to identify where AI is in use, what decisions it influences, and what harm could result if those decisions are flawed.

This analysis should include:

Inventorying all internal and third-party AI systems
Mapping potential points of failure and legal exposure
Quantifying financial impact from regulatory enforcement, litigation or reputational damage
Evaluating existing insurance coverage for exclusions or gaps
Modeling worst-case outcomes using internal data or external benchmarks

Once complete, captive owners can work with actuaries and captive managers to design coverage, including standalone AI liability policies, endorsements to existing coverages, or reserves for emerging risks.

Boards are paying attention

AI is no longer just a back-office issue. In 2024, public companies and shareholders sharply increased their focus on artificial intelligence, especially on board-level oversight and shareholder proposals. A Harvard Law article shared how board oversight disclosures grew more than 80 percent year over year, while shareholder proposals related to AI more than quadrupled compared with 2023. This intensifying scrutiny signals a mandate for risk managers and captive owners to deliver proactive solutions. Captives offer companies a flexible tool to fund, control and adapt their responses to the evolving AI risk landscape.

AI is changing how businesses operate, as well as how they are exposed. As regulatory frameworks tighten and litigation accelerates, businesses must prepare for the reality that AI-related liability is no longer speculative. For companies that rely on AI, the question is no longer whether liability will emerge. It is whether they are positioned to handle it.