Insurers and AI, a systemic risk

Core Viewpoint - Major insurers are retreating from providing coverage for risks associated with artificial intelligence due to the potential for multibillion-dollar claims and systemic risk posed by correlated losses across multiple incidents [1][2][12] Group 1: Insurers' Response to AI Risks - Insurers like AIG, Great American, and WR Berkley are introducing explicit exclusions for AI-related risks, particularly concerning agents and language models [1] - The potential losses related to AI could reach several hundreds of millions of dollars, with the primary concern being the possibility of simultaneous, massive losses that cannot be mutualized [1][2] Group 2: Systemic Risk and Interconnectedness - The interconnected nature of AI systems creates a breeding ground for contagion, where a single error can propagate rapidly across a network, affecting thousands of users simultaneously [5][10] - Financial systems exhibit a "robust-yet-fragile" dynamic, where they can withstand numerous shocks but may collapse suddenly when a specific shock travels through interconnected channels [3][4] Group 3: Challenges in Insurability - Insurability relies on the law of large numbers, which requires events to be independent; however, cyber risks and generative AI create environments where losses are highly correlated and difficult to attribute [6][8] - Generative AI amplifies the structural fragility of cyber insurance, as a single defect or vulnerability can lead to widespread, identical losses across an entire sector [7][8] Group 4: Legal and Regulatory Implications - The issue of "AI liability" remains largely unexplored, with significant contractual asymmetry where AI providers limit their liability and transfer risk to users [19][20] - This creates a regulatory gap, a contractual gap, and an insurance gap, leading to a legal systemic risk characterized by diffuse responsibility and concentrated dependency [23]