From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework
arXiv:2606.03777v1 Announce Type: new Abstract: AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, because the relevant state changes as the system reasons, retrieves, calls tools, and acts. The relevant question is not only what loss occurred, but what the system was allowed to do, what it actually did, and whether that reconstructed loss can support insurance claim recovery. This paper addresses losses in which the insured's AI system is in the causal chain, including externally triggered failu
The proliferation of advanced AI systems in commercial use is leading to novel loss scenarios that traditional insurance and legal frameworks are not equipped to handle, necessitating new theoretical understandings.
This paper highlights the growing challenge of attributing and insuring AI-driven losses, which is critical for the sustainable adoption and deployment of advanced AI in enterprise settings.
The understanding of AI-mediated loss reconstruction is shifting from simple event analysis to complex state reconstruction, requiring new investigative and actuarial methodologies.
- · AI risk management firms
- · Insurance providers specializing in AI liability
- · Legal tech platforms
- · Traditional insurance models
- · Organizations without robust AI governance
- · Legacy loss adjustment firms
Companies deploying advanced AI will need to implement more sophisticated internal logging and explainability features for their AI systems to support potential insurance claims.
New insurance products and regulatory frameworks will emerge specifically tailored to AI-driven risks, including mandates for 'black-box' recorder-like functionality in AI systems.
The definition of 'control' and 'causality' in legal and insurance contexts will undergo significant reinterpretation as autonomous AI agents become more prevalent, potentially shifting liability from human operators to AI developers or directly to the AI itself.
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Read at arXiv cs.AI