AI and the Evolution of Insurance Law

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ID: 328749
2026
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Abstract
Abstract This book examines the capacity of English insurance law to respond to the risks generated by AI. It argues that AI does not require the abandonment of established insurance law concepts, but it does expose the limits of their existing application. Beginning with the technical foundations of AI and the distinctive features of AI-related risk, the book analyses how autonomy, opacity, adaptivity, data dependence, scale, and correlation complicate the identification, disclosure, pricing, proof, and allocation of insured risk. It then considers the consequences for insurability, causation, liability, liability insurance, and the duty of fair presentation under the Insurance Act 2015, with particular attention to the legal meaning of knowledge in data-driven underwriting and AI deployment. The book shows that many AI-related losses remain capable of private insurance, but often only through more exacting underwriting, technical documentation, audit duties, policy limits, exclusions, aggregation controls, and reinsurance. It further argues that insurers will become important private governors of AI by translating legal and ethical expectations into commercial conditions of insurability, while remaining constrained by concerns of legitimacy, transparency, and market capacity. For highly correlated or systemic risks, the book proposes a layered institutional response: ordinary private insurance should remain primary; an AI mutual or market pool may provide collective risk sharing; and public-private support should be confined to residual cases where private capacity is demonstrably inadequate. The book thus offers a legally grounded account of how insurance practice and law can preserve compensation, accountability, innovation, and market resilience in the AI age.
Reference Key
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Authors Feng Wang
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Journal Oxford University Press eBooks
Year 2026
DOI
10.1093/law/9780198953586.001.0001
URL
https://doi.org/10.1093/law/9780198953586.001.0001
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