AI 中文总结
研究人工智能智能体经济下保险面临的风险及可保性问题，提出构建含八个组件的人工智能保险堆栈，通过行业协调实现限额承保，还探讨了前沿人工智能灾难性风险承保及所需工具，以助保险公司管理相关风险。
AI 中文摘要
从海上贸易到商业核电，保险通过定价风险、限制下行风险和传播最佳实践，推动了重大经济和技术发展。预计到2030年，新兴的人工智能智能体经济将处理数万亿美元的交易，有望成为下一个这样的发展领域。然而，目前保险公司对人工智能智能体风险的承保在现有保险产品线中大多未定价；在这种隐性承保和日益增加的除外责任之间，保险范围不符合目的。此外，可保性正朝着错误的方向发展：人工智能智能体的能力似乎超过了可靠性，导致事故严重性上升；少数基础模型提供商的集中化威胁到相关损失；传统的精算建模将难以跟上像前沿人工智能这样快速发展的技术。本报告认为，到2030年，通过行业范围内的协调，可以实现数十亿美元限额的肯定性人工智能保险，但前提是建立一个涵盖事件数据收集、灾难建模、标准、合同设计、风险选择、定价、监测和理赔管理等八个组成部分的人工智能保险堆栈。建立这一基础设施将使保险公司能够可持续地大规模承保和管理人工智能智能体风险。最后，我们讨论了前沿人工智能（“人工智能巨灾”）的灾难性风险承保，包括化生放核、关键基础设施崩溃和失控场景。应对这些尾部风险将需要专门的工具，可能包括前沿模型开发者互助组织、巨灾债券、定制责任制度和政府支持。
英文摘要
From maritime trade to commercial nuclear power, insurance has been the enabler of major economic and technological developments by pricing risk, limiting downside, and spreading best practices. The emerging AI agent economy, projected to handle trillions of dollars in transactions by 2030, looks to be the next such development. Yet insurers' exposure to AI agent risk currently sits largely unpriced across existing insurance lines; between this silent coverage and growing exclusions, coverage is not fit for purpose. Furthermore, insurability is trending the wrong way: AI agent capabilities appear to be outpacing reliability, leading to rising incident severity; concentration among a few foundation model providers threatens correlated losses; and traditional actuarial modeling will struggle to keep pace with a technology evolving as rapidly as frontier AI. This report argues that affirmative AI coverage with limits in the billions is achievable by 2030, but only with industry-wide coordination. Drawing on successful historical precedents such as Underwriters Laboratories, the Closed Claims Project, and others, we lay out an eight-component AI insurance stack spanning incident data collection, catastrophe modeling, standards, contract design, risk selection, pricing, monitoring, and claims management. Building out this infrastructure is what will enable insurers to cover and manage AI agent risk sustainably and at scale. Finally, we discuss coverage for catastrophic risk from frontier AI ("AI CAT"), including CBRN, critical infrastructure collapse, and loss of control scenarios. Addressing these tail risks will require purpose-built instruments, potentially including a frontier model developer mutual, catastrophe bonds, bespoke liability regimes, and government backstops.
