# Insurance of Agentic AI

arXiv: https://arxiv.org/abs/2606.05449 · HTML: https://mlsanity.com/paper/2606.05449/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 34 references that are in the map.
- First posted on arXiv 3 Jun 2026.

## Builds on (most cited first, 10 of 10)

- [Explaining and Harnessing Adversarial Examples](https://mlsanity.com/paper/1412.6572/) (2014)
- [Intriguing properties of neural networks](https://mlsanity.com/paper/1312.6199/) (2013)
- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)
- [Towards Evaluating the Robustness of Neural Networks](https://mlsanity.com/paper/1608.04644/) (2016)
- [Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats](https://mlsanity.com/paper/2507.10621/) (2025)
- [Foundations of Cyber Resilience: The Confluence of Game, Control, and Learning Theories](https://mlsanity.com/paper/2404.01205/) (2024)
- [Toward a Dynamic Stackelberg Game-Theoretic Framework for Agentic AI Defense Against LLM Jailbreaking](https://mlsanity.com/paper/2507.08207/) (2025)
- [Optimal Cyber-Insurance Contract Design for Dynamic Risk Management and Mitigation](https://mlsanity.com/paper/1804.00998/) (2018)
- [Dynamic Contract Design for Systemic Cyber Risk Management of Interdependent Enterprise Networks](https://mlsanity.com/paper/1908.04431/) (2019)
- [Mitigating Moral Hazard in Cyber Insurance Using Risk Preference Design](https://mlsanity.com/paper/2203.12001/) (2022)

## Built on by (most cited first, 3 of 3)

- [The Internet of Agentic AI: Communication, Coordination, and Collective Intelligence at Scale](https://mlsanity.com/paper/2606.12835/) (2026)
- [AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models](https://mlsanity.com/paper/2606.24616/) (2026)
- [AI-Native Insurance for Agentic AI: Pricing, Underwriting, and End-to-End Automation](https://mlsanity.com/paper/2607.13230/) (2026)

## Abstract (arXiv)

Agentic artificial intelligence (AI) systems are transforming the risk landscape by extending beyond information generation to autonomous planning, tool invocation, decision execution, and persistent modification of digital and physical environments. These capabilities introduce novel exposures that do not fit neatly within traditional insurance categories such as cyber, professional liability, product liability, or directors and officers coverage. This paper examines the emerging insurance market for agentic AI and develops a framework for understanding its underwriting, pricing, reinsurance, and product-design implications. We characterize agentic AI as a continuum of autonomy and delegated authority, emphasizing the distinction between informational outputs and systems capable of independently generating insured events through external actions. We analyze major risk pathways, including hallucinations, prompt-injection attacks, autonomous decision errors, model drift, dependency failures, and cyber-physical harms, and evaluate how existing insurance products are adapting to address these exposures. The paper further proposes an actuarial framework based on exposure assessment, scenario analysis, dependency mapping, and accumulation-risk management, drawing parallels to the evolution of cyber insurance. Finally, we present a coordinated insurance architecture that integrates cyber, technology errors and omissions, product liability, performance-warranty, and affirmative AI-liability coverages through explicit allocation mechanisms and dedicated AI aggregates. The analysis suggests that the future of agentic-AI insurance lies not in a single monoline product but in a layered ecosystem of complementary coverages supported by improved governance, transparency, telemetry, and regulatory clarity.