Product and use cases
Expect to describe exactly what the system does, who uses it and what happens when it is wrong. Underwriters separate low stakes uses, such as drafting or summarizing, from high stakes uses where outputs feed automated decisions about people or money. If you serve regulated industries, say so up front and explain how your product fits their compliance needs.
Models, data and oversight
Be ready to say whether you build your own models, fine-tune others or rely on third party providers, since each carries a different chain of responsibility. Underwriters also ask about training data sources and rights, how customer data is separated and protected, and how outputs are tested and monitored. Documented evaluation and a clear human review process are persuasive.
Questions about intellectual property are common as well, such as whether you have licenses for the data you train on and how you respond to takedown requests.
Contracts and customers
Your standard customer agreement tells an underwriter how much risk you have accepted. They look at liability caps, indemnities, warranties about accuracy or performance, and service level commitments. A contract with sensible caps and clear disclaimers is easier to place than one that promises unlimited liability.
Security and governance
Finally comes the security review, covering multi-factor authentication, encryption, access controls, backup testing, incident response planning and any certifications such as SOC 2. Governance questions also appear, such as who owns AI risk inside the company and whether there is a written policy for acceptable use.
A broker who knows how these questions are read can help you assemble the answers before the submission goes out, which tends to save weeks of back and forth and improves how the company is perceived.
Last updated October 22, 2026. Written by the Alton Risk placement team.