AI Buyer FAQ / Trust-Center FAQ

# AI Buyer FAQ / Trust-Center FAQ

Sample Deliverable

Executive Summary

This FAQ turns AI security posture into buyer-safe answers for sales, procurement, and trust-center use. It does not replace the full questionnaire answer bank. It is the short-form public or semi-public layer that points back to evidence.

The FAQ should be accurate, constrained, reviewed, and tied to source artifacts. It should never drift into unsupported claims about provider training use, retrieval authorization, human oversight, prompt retention, or incident response.

Heads up

Public sample notice

This is a shortened, synthetic excerpt prepared as a public sample. A client version would include system-specific evidence, implementation references, architecture screenshots, control test results, owner sign-offs, and full supporting documentation. This sample uses Northstar Support Cloud / Customer Support Copilot as the synthetic reference system. This sample is not legal advice, not a compliance certification, not an audit opinion, not a warranty, and not proof that any unreviewed system is secure.

Decision · conditional

FAQ publishing decision

Publish only approved or approved-with-caveat answers. Keep legal-review, partial, and planned answers internal until evidence and owner approval are complete.

Metrics

FAQ Snapshot

FAQ answers

Approved answers

Partial answers

Legal-review answers

Planned answers

Note

The FAQ is not marketing copy. It is controlled evidence language.

A good AI trust-center FAQ makes security review faster because every short answer has a longer evidence path behind it.

FAQ answer set

Evidence pack

AI Buyer FAQ

The FAQ maps buyer questions to short answers, buyer-safe answers, evidence, answer status, and public publishing rules.

Synthetic public-safe buyer FAQ for trust-center, sales, procurement, and security review conversations about AI systems.

implemented

partial

missing

planned

Buyer FAQ

Buyer FAQ summary

Question	Status	Evidence
What AI features are included in the product?	Approved	AI System Inventory, Architecture Review
Is customer data used to train foundation models?	Legal review	Provider Boundary Statement
Are prompts, outputs, or retrieved snippets retained?	Partial	AI Trace Schema, Incident Playbook
Can users receive information through AI that they cannot access directly?	Partial	RAG Authorization Review, RAG Test Plan
Do you test against prompt injection?	Approved	RAG Test Plan, Red-Team Findings
Can the AI system take actions on behalf of users?	Approved	Tool Inventory, Permission Matrix
What human oversight exists for AI actions?	Partial	Permission Matrix, Release Gate
Can AI behavior be audited after an incident?	Approved with caveat	Trace Schema, Evidence Appendix
Do AI changes go through security review before release?	Partial	Release Gate, Operating Model
How are AI-specific incidents handled?	Planned	Incident Response Playbook

Public FAQ rules

Checklist

Public FAQ rules

✓Do not publish route-specific provider claims without legal approval.

✓Do not claim complete RAG authorization unless negative tests pass.

✓Do not imply human oversight is meaningful unless approval context is described.

✓Do not publish exploit payloads or confidential traces.

✓Do not conflate internal AI traces with provider logs.

✓Do not let public FAQ language drift from the answer bank.

Findings

FAQ Readiness Findings

Finding · high

Provider training-use language needs legal approval

Evidence: model-provider-boundary-statement

The provider training-use answer is procurement-sensitive and should not be published without route-specific legal approval.

Finding · critical

RAG authorization answer must remain partial

Evidence: rag-authorization-review

The FAQ should not say retrieval authorization is complete until negative tests prove restricted content cannot enter retrieval, reranking, prompt assembly, or generated answers.

Finding · medium

AI incident response answer is not ready for strong trust-center claims

Evidence: ai-incident-response-playbook

The incident response answer should remain planned or internal until the playbook is approved and tabletop-tested.

Update triggers

Checklist

FAQ update triggers

✓Model provider change.

✓Model route change.

✓Retrieval source change.

✓Tool policy change.

✓Approval workflow change.

✓Trace retention change.

✓Customer-facing security questionnaire update.

✓AI incident or tabletop result.

Artifact

Related artifact: Enterprise AI Security Questionnaire Answer Bank

The answer bank is the controlled source for longer questionnaire responses.

/deliverables/enterprise-ai-security-questionnaire-answer-bank

Artifact

Related artifact: Model Provider Boundary Statement

The provider boundary statement supplies approved model-provider language.

/deliverables/model-provider-boundary-statement