Spreading the Risk of Scalable Legal Services: The Role of Insurance in Expanding Access to Justice

Abstract

Liability insurance for AI-powered legal services offers a promising solution to two critical barriers in using AI to expand access to justice: mitigating catastrophic risk to individual users from inadequate advice and ensuring meaningful accountability when failures occur. Existing accountability mechanisms face significant challenges: tort liability frameworks encounter barriers including judgment-proof providers and costly information asymmetries, while current regulatory approaches revolve around human oversight requirements, creating cost and scalability barriers which limit access to justice. This Article argues that an insurance-based framework offers a promising response to these challenges by distributing risks across users while establishing market-driven incentives for quality improvement through performance-based premiums. The Article proposes a comprehensive insurance model for AI legal services that establishes clear risk thresholds, streamlined compensation mechanisms, and continuous performance monitoring. Rather than attempting to eliminate all risks through restrictive ex-ante oversight requirements or relying on ineffective ex-post remedies, insurance enables efficient risk spreading while facilitating the scaling of automated legal services. This framework demonstrates how carefully structured insurance mechanisms can help realize AI's transformative potential to democratize legal assistance while maintaining robust user protections through sophisticated risk management rather than direct oversight.