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This paper develops a comprehensive mathematical framework for underwriting and pricing insurance specifically tailored for agentic AI systems, addressing unique challenges posed by their autonomy and decision-making capabilities. By representing deployments through a risk state that encompasses various factors such as operational authority and governance maturity, the framework allows for the mapping of risk to critical insurance metrics, facilitating optimized contract design. Key findings include the identification of insurability properties and the demonstration of the framework's application in a healthcare case study, showcasing automated claims processing and contract optimization.
The new AI-native insurance framework reveals how to effectively underwrite and price policies for autonomous AI systems, balancing risk and governance.
Agentic AI introduces new insurance challenges because autonomous AI systems can make decisions, invoke tools, modify external environments, and interact with third-party services. This paper develops an AI-native mathematical framework for underwriting, pricing, and contract design for agentic AI deployments. A deployment is represented by a risk state that captures autonomy level, operational authority, permission exposure, governance maturity, and dependency concentration. The framework maps the risk state to event probabilities, loss severities, governance costs, premiums, deductibles, coverage allocation, and policy covenants, and formulates an optimization problem for insurance contract design under participation, profitability, and incentive compatibility constraints. The paper establishes structural properties of insurability, including characterization of an insurability region, monotone deterioration of feasibility with increasing exposure, and governance certification thresholds. Insurance is further interpreted as both an operational cost and a regulatory mechanism for AI deployment. A healthcare case study illustrates contract optimization, sensitivity analysis, and automated claims processing for agentic AI systems.
