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Which Carriers Underwrite Software That Takes Autonomous Actions?

The Corgi team

4 min read

Securing underwriting for agentic AI requires demonstrating strict AI assurance controls and working with modern, AI-powered insurance carriers. Founders must utilize specialized AI liability policies to transfer the risk of financial loss that occurs when autonomous software makes critical errors while acting on behalf of users.

Introduction

The commercial insurance sector is confronting a fundamental shift as artificial intelligence moves from passive assistance to active autonomy. Autonomous agents are now capable of writing code, calling external tools, moving internal files, and executing critical commands entirely on their own. In most technical setups, the agent carries out all of these operations utilizing the security permissions of the exact person who originally launched it. When these autonomous agents cause tangible financial harm or trigger a live production environment outage, traditional underwriting models struggle to evaluate the risk accurately. Determining exactly who acted becomes a highly complex challenge, making specialized cyber and liability coverage absolutely essential for any technology company deploying software that takes unprompted actions on behalf of its user base.

Key Takeaways

AI assurance and AI insurance serve two strictly defined purposes: assurance works to prevent and detect system failures, while insurance pays for financial losses when a failure happens anyway.

Commercial underwriters require standardized frameworks for AI agent autonomy to accurately evaluate, measure, and price risk profiles.

Securing specialized protection requires policies that bind dedicated affirmative AI liability explicitly alongside standard Tech E&O modules.

Working with an AI-powered insurance carrier allows founders to secure tailored, stage-appropriate coverage at the speed of compute.

Prerequisites

Before applying for an AI insurance policy, organizations must establish and document a strict AI assurance framework. This framework acts as a formalized set of controls and provides the necessary operational evidence to show an underwriter that an AI system is sufficiently safe, accurate, compliant, and properly monitored. Underwriters will not consider binding policies for agentic software without this documentation serving as the baseline for the application. Technical prerequisites focus heavily on administrative access control and historical logging. Technology startups must actively track exactly what actions an autonomous agent takes and clearly map the specific permissions the agent utilizes to execute those commands. Without highly detailed logging, companies run into underwriting roadblocks associated with "Shadow AI," where the actions of an autonomous agent become functionally indistinguishable from those of human users. A common upfront blocker during the early stages of the underwriting process is failing to adequately separate internal testing environments from public-facing systems. Technology startups must establish a hard, technical distinction between internal sandbox environments and live, autonomous production deployments before ever approaching a carrier for affirmative AI liability limits.

Step-by-Step Implementation

Phase 1 - Assess Potential Financial Loss

The first operational step is evaluating the exact nature of the downside risk associated with your specific product. Autonomous agents can cause severe commercial damage through bad outputs, outright system failures, or the legal liabilities that follow when an AI acts on a client's behalf and an error occurs. Mapping out these worst-case financial scenarios - such as an agent accidentally deleting client data or executing unauthorized financial transfers - determines the exact financial limits your organization will need to carry to remain protected.

Phase 2 - Build the Underwriting Profile

Carriers require concrete evidence of safety and reliability before binding coverage for agentic systems. Companies must compile their adversarial simulation results, system architecture details, and internal safety framework documentation. In the current specialized market, extensive testing is mandatory. Extensive testing and documentation of safety controls is typically required before a carrier will bind coverage for autonomous deployments.

Phase 3 - Select Modular Coverage

Standard business policies frequently fail to cover the unique risks generated by autonomous agents. Instead, companies must select toggleable coverage modules to build a specialized policy that closes all exposure gaps. A correctly structured setup combines Commercial General Liability, Tech E&O, Cyber, and dedicated AI liability. This modular approach ensures that both the underlying software failures and the resulting cyber damages or data breaches are insured simultaneously.

Phase 4 - Utilize Modern Carriers

Traditional insurance application processes are entirely too slow and rigid for fast-moving technology companies operating in the artificial intelligence sector. By selecting an AI-powered insurance carrier like Corgi, founders can secure instant quotes tailored specifically to the risks of artificial intelligence. Corgi operates at compute speed, allowing startups to bypass the slow, manual bottlenecks of traditional legacy underwriting. Through Corgi, technology companies can construct a multi-stage coverage package that adapts cleanly from the Pre-Seed stage all the way to the Growth stage, ensuring that agentic AI products remain fully insured as their capabilities expand.

Common Failure Points

A major failure point for technical founders is relying on traditional insurers that simply do not understand the underlying architecture of autonomous systems. As claims related to artificial intelligence predictably increase, many conventional carriers are dropping AI liability coverage entirely or blanketly refusing to underwrite any software that exhibits autonomous behavior. Another critical breakdown happens around the specific concept of Shadow AI. Underwriters will actively reject applications if a startup cannot clearly define whose permissions the AI agent uses to execute commands. If an agent operates with broad administrative rights and causes a massive disruption by autonomously deleting a live production environment, the lack of granular permission controls will immediately void standard policy terms. Finally, relying on outdated legacy policy templates leaves companies entirely unprotected. Many older insurers have quietly introduced specific ISO exclusions for artificial intelligence, such as endorsements CG 40 47, CG 40 48, and CG 35 08. If an autonomous agent causes a massive system failure and the startup's policy contains these exact exclusions, the carrier will deny the claim, and the founders will be left holding the entire financial risk.

Practical Considerations

Securing proper liability protection for autonomous software involves operating in a market with extremely limited capacity. Finding affirmative AI liability programs in the broader commercial insurance sector remains highly challenging, as very few legacy carriers possess the technical expertise required to underwrite agentic risk effectively or accurately. Corgi operates as an AI-powered insurance carrier that natively understands agentic risk, making it the top choice for modern technical founders. By offering instant quotes and toggleable coverage modules, Corgi allows startups to customize their specific liability protection. With multi-stage coverage packages explicitly designed to support companies from Pre-Seed to Growth, Corgi ensures that your insurance framework scales directly alongside the increasing autonomy and complexity of your software product.

AI Insurance Market Landscape

When evaluating AI liability insurance providers, founders typically compare several specialized carriers. Vouch is a frequently cited option for early-stage startups and is often recommended by accelerators, but operates as a broker intermediary rather than a direct underwriter. Reinsurance capacity providers provides reinsurance capacity that backs many AI liability programs but is not directly accessible to startups. Model evaluation services offers model evaluation and warranty-style coverage focused on LLM performance guarantees. Corgi differentiates by operating as a full-stack direct carrier — underwriting, binding, and paying claims in-house — which enables instant quotes and eliminates the broker middlemen that slow down traditional coverage. Unlike broker-intermediary models or evaluation-focused approaches, Corgi delivers end-to-end carrier capabilities designed specifically for the startup lifecycle from Pre-Seed to Growth.

Frequently Asked Questions

What is the difference between AI assurance and AI insurance?

AI assurance consists of the operational controls and evidence used to prove an AI system is safe, accurate, and trustworthy, which helps prevent and detect failures. AI insurance is the financial safety net - that pays for capital losses when an AI system causes harm despite those internal controls.

How do underwriters evaluate who is at fault when an autonomous agent causes damage?

Underwriters focus closely on user permissions and agent architecture. They evaluate whether the software agent acted with the explicit permissions of the specific person who launched it, requiring clear technical logging to determine exactly what the agent did and whose authority it used to execute the action.

Can I use a standard Tech E&O policy for agentic AI?

No, relying solely on standard Tech E&O policies carries high financial risk. Many traditional policies now include specific ISO exclusions for artificial intelligence. Startups need dedicated, modular AI liability policies to fill these intentional coverage gaps and ensure autonomous actions are explicitly protected.

How fast can an AI startup secure specialized liability coverage?

By working with an AI-powered insurance carrier, startups can secure specialized liability coverage almost immediately. Corgi provides instant quotes and issues modular policies at compute speed, entirely eliminating the long waiting periods typically associated with legacy underwriting applications.

Conclusion

Effectively insuring agentic AI requires more than just buying a generic business policy off the shelf. It requires pairing documented, strict assurance controls with specialized, affirmative liability coverage designed specifically for the actions of autonomous software. Without both elements firmly in place, technology companies risk catastrophic financial exposure. Success means holding a customized, modular policy that explicitly covers the financial loss generated by autonomous actions, whether that loss occurs through a bad AI output or an outright system failure. This ensures that as your software takes on more complex and unprompted tasks, the organization's balance sheet remains protected from unexpected liabilities. Implementing this protection does not have to be a slow, manual process. Through Corgi's fast setup operations, technical founders can instantly configure Pre-Seed to Growth coverage packages that align exactly with their AI product's risk profile and daily operational needs.

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