Trout et al. blueprint AI insurance stack for $trillion agent economy

A new arXiv paper by Cristian Trout and 36 co-authors lays out the first comprehensive blueprint for insuring the AI agent economy. The authors draw parallels with historical insurance enablers—maritime trade, commercial nuclear power—to argue that AI agents, projected to handle trillions of dollars in transactions by 2030, are currently underpriced and silently covered across existing lines. They warn that agent capabilities are outpacing reliability, leading to rising incident severity, while concentration among foundation model providers creates correlated loss risks. Traditional actuarial models cannot keep pace with frontier AI's rapid evolution.

To solve this, the paper proposes an eight-component AI insurance stack: incident data collection, catastrophe modeling, standards, contract design, risk selection, pricing, monitoring, and claims management. This infrastructure would enable insurers to offer affirmative AI coverage with limits in the billions by 2030—but only through industry-wide coordination. The authors also discuss catastrophic tail risks from frontier AI (AI CAT), including CBRN, critical infrastructure collapse, and loss of control. They recommend purpose-built instruments: a frontier model developer mutual, catastrophe bonds, bespoke liability regimes, and government backstops. The paper cites successful precedents like Underwriters Laboratories and the Closed Claims Project to show this is achievable.