Insurance & AI Risk Transfer

Traditional insurance policies weren't designed with AI risks in mind, and many organisations discover gaps in their coverage only when they need it. Errors and omissions policies may not clearly cover losses caused by AI system failures. Cyber insurance may not address AI-specific risks like model manipulation or training data poisoning. Product liability policies may have exclusions or ambiguities around AI-generated outputs. The insurance market is adapting, with new products emerging specifically for AI-related risks, but the landscape is still evolving and coverage can vary significantly between providers. Organisations should review their existing insurance coverage in light of their AI activities, identify gaps, and work with brokers who understand AI risks to find appropriate solutions. This means being able to clearly articulate what AI systems you're running, what decisions they influence, and what could go wrong - which is itself a useful governance exercise. Be prepared for insurers to ask detailed questions about your AI governance, testing, and monitoring practices, as underwriters increasingly differentiate pricing based on the maturity of your risk management. Good governance doesn't just reduce risk; it can reduce the cost of transferring it.