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AIエージェント経済を支える:AI保険スタックの青写真

原題: Underwriting the Agent Economy: The Blueprint for an AI Insurance Stack
著者: Cristian Trout, Sanmi Koyejo, Sasha Romanosky, Giorgio Ripamonti, Lynn Thompson, Desiree Spain, Alex Taylor, Kevin Casey, Stephen Casper, Matthew Botvinick, Sean McGregor, Miles Brundage, A. Feder Cooper, Patricia Paskov, Adrien Ecoffet, Ben Bucknall, Kevin Wei, Markus Anderljung, Lukasz Szpruch, Bri Treece, Tom Zick, Gabriel Weil, Ugur Ozer, Kevin Kalinich, Jesus Gonzalez, Vitaly Baranov, Moran Koren, Guy Laban, Gil Arazi, Henri Winand, Derek Blum, Toby Clowes, Adam Kleinman, Anita Srinivasan, Tom Fehring, Rune Kvist, Rajiv Dattani
公開日: 2026-07-13 | 分野: AI 経済 リスク管理 cs.CY AIエージェント AIガバナンス

※ 日本語タイトル・ポイントはAIによる自動生成です。正確な内容は原論文をご確認ください。

ポイント

  • AIエージェントによる経済活動のリスクを適切に評価・管理するための包括的な保険インフラの設計案を提示した。
  • 既存の保険モデルではAI特有の急速な進化や相関リスクに対応できないため、業界全体での標準化と協調が不可欠である。
  • データ収集から災害リスクモデルまで8つの要素からなる保険スタックを構築し、AIによる壊滅的リスクへの備えを提案した。

Abstract

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.

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