AI Buying Checklist

AI Security Review Checklist for Vendor and Tool Approval

Use this AI security review checklist to evaluate data handling, model training policy, access controls, audit logs, privacy, retention, incident response, and AI-specific failure modes.

Updated 2026-06-243 buying gates5 red flags

Data and model controls

Confirm exactly what data the AI system receives, stores, learns from, and exposes.

Map prompts, files, logs, embeddings, outputs, user feedback, telemetry, and admin activity.
Ask whether customer data is used for model training, evaluation, abuse monitoring, or product improvement.
Review deletion, retention, export, residency, subprocessors, encryption, and data classification controls.

Access and auditability

AI security review needs identity and evidence, not only model claims.

Check SSO, SCIM, role-based permissions, least privilege, admin actions, and service accounts.
Confirm audit logs cover user access, data upload, AI action, workflow change, export, and admin configuration.
Require human review and override for high-impact outputs or external actions.

AI-specific threat handling

Review failure modes that ordinary SaaS questionnaires often miss.

Ask how the vendor handles prompt injection, hallucination, data leakage, unsafe tool calls, and model drift.
Confirm red-team testing, abuse monitoring, incident process, vulnerability disclosure, and rollback paths.
Review how policies, blocked actions, and human approvals are enforced across integrations.

Red flags

The vendor uses customer prompts or files for training by default.
Audit logs cannot show who uploaded data, triggered an AI action, or changed a workflow.
Sensitive data leaves the allowed region without a documented control.
The product can take external actions without human approval or policy gates.
Security answers are generic and do not mention prompt injection, hallucination, or AI tool abuse.

Evidence to collect

Data flow diagram, model training policy, retention policy, subprocessors, region controls, and encryption details.
SSO, SCIM, RBAC, audit log samples, admin controls, and export evidence.
AI risk controls, red-team summaries, incident process, vulnerability policy, and rollback documentation.

How to use it

Turn the checklist into a buying decision

Step 1
Use this checklist before adding the vendor to the final shortlist.
Step 2
Attach the AI security questionnaire and require written answers.
Step 3
Block high-risk workflows until human review, audit logs, and data controls are proven.
Step 4
Re-run the checklist before renewal or major workflow expansion.

Related buyer paths

Use the next artifact

AI Software Buyer Guides

Open commercial AI software categories after the checklist identifies the workflow and owner.

AI Buying Templates

Turn checklist answers into an RFP, scorecard, security questionnaire, POC plan, or business case.

AI Governance Guides

Plan governance frameworks, risk assessments, vendor risk, model risk, compliance automation, and policy management.

AI Cost Guides

Estimate AI software, implementation, RAG, agent, chatbot, and document automation cost before approval.

AI ROI Guides

Calculate ROI, payback, automation savings, chatbot savings, agent ROI, and AI business case readiness.

AI Services Buyer Guides

Evaluate consultants, implementation partners, automation agencies, integration services, and enterprise AI advisors.

AI Vendor Scorecard Calculator

Convert evidence, risk, fit, and pilot results into a weighted vendor decision.

AI Security Questionnaire Template

Copy deeper vendor questions for AI data, model, access, privacy, audit, and incident review.

AI GRC Software Buyer Guide

Compare AI governance, risk, compliance, audit, and control software categories.

What should an AI security review include?

An AI security review should include data flow, model training policy, retention, access controls, audit logs, prompt injection risk, hallucination handling, tool permissions, incident response, and human approval for high-impact actions.

Can a standard SaaS security review cover AI tools?

A standard SaaS review is not enough for most AI tools. Add AI-specific questions about prompts, files, embeddings, training use, generated outputs, human review, model behavior, and tool-call risk.