Insurability of AI Risks

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ID: 328747
2026
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Abstract
Abstract This chapter examines whether AI-related risks are insurable within English insurance law and practice by applying Berliner’s actuarial, market, and societal criteria. It argues that AI risks are not inherently uninsurable, but their autonomy, opacity, adaptivity, scalability, and systemic potential strain traditional assumptions of randomness, independence, predictability, adequate pooling, affordable pricing, and clear accountability. The chapter shows how information asymmetries, moral hazard, limited historical data, silent AI exposure, and uncertain liability rules complicate underwriting and market capacity, while public policy and regulatory developments shape the permissible scope of coverage. At the same time, the chapter highlights how insurers’ own use of AI, through improved modelling, dynamic monitoring, and more accurate pricing, may enhance insurability over time. The chapter concludes that AI risk insurability is best understood as a spectrum, requiring careful product design, governance, and, for extreme systemic losses, possible public-private support.
Reference Key
openalex_W7213422990 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Feng Wang
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Journal Oxford University Press eBooks
Year 2026
DOI
10.1093/law/9780198953586.003.0004
URL
https://doi.org/10.1093/law/9780198953586.003.0004
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