The AI Questionnaire Answer Guide
Enterprise security questionnaires now routinely include an AI section, and most vendors are answering it for the first time under deal pressure. Here's what the six most common question categories are actually checking for, and how to answer them honestly without either overclaiming or stalling a deal.
1. AI Use Disclosure
What it's really asking: Whether your product uses AI/ML at all, and where, specifically, not just "do you use AI" as a yes/no.
How to frame your answer: List every AI/ML component by product area, including anything embedded from a sub-vendor (a support chatbot, a recommendation engine, an OCR step in a pipeline). If a component is a third-party model you call via API rather than one you trained, say so explicitly: reviewers read "we don't train models" very differently from "we don't use AI."
Common mistake: Answering "No" because you didn't build the model yourselves. If a vendor tool inside your product uses AI, you use AI, from the reviewer's standpoint.
2. Model / System Inventory
What it's really asking: For a specific system: its purpose, who owns it, what risk tier it falls under, and whether that inventory is current.
How to frame your answer: Answer with an owner name or role, not a team name ("the ML team"). If you don't have a formal risk-tier classification yet, say what you use instead (e.g. an internal severity rating) rather than leaving the field blank.
Common mistake: Naming a team instead of a person. Reviewers are specifically checking for Ownership Debt: a governance structure with no accountable individual reads as unowned, even if a team is technically responsible.
4 more categories below: Training Data Provenance, Human Oversight, Third-Party / Embedded AI, and Evidence & Auditability.
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