What you get
A current commercial checklist covering AI inventory, data handling, approvals, human review, vendor terms, and executive visibility.
AI Security Checklist
Open the checklist immediately, review what it covers, and optionally send a copy to your inbox. This page is designed to be useful first, not a hard gate.
- Best for: teams tightening AI governance, buyer diligence responses, or executive reporting.
- Format: practical control prompts you can review in one sitting.
- Use it when you need a clear first pass before a fuller AI Risk Audit.
How to use it
Work through the prompts with your security, IT, legal, and operations leads. Flag anything that is unclear, missing, or unowned.
What it is not
This is a practical readiness tool, not a full audit. Use it to sharpen the first conversation and identify where a deeper AI Risk Audit is warranted.
Preview the asset before you send anything
Inventory + approvals
- Do you maintain a current list of approved AI tools and use cases?
- Is there a named approval path for new AI vendors or workflows?
- Can you distinguish approved use from shadow AI quickly?
Data + guardrails
- Are restricted or regulated data classes clearly off-limits by default?
- Do employees know when prompts, uploads, or outputs require redaction?
- Are high-impact outputs subject to human review before external use?
Oversight + reporting
- Are AI incidents, misuse cases, or unsafe outputs part of incident response?
- Do vendor terms cover retention, training use, and security expectations?
- Can leadership see approved AI use, high-risk use, and open actions in one view?
Printable checklist
Use the list below directly in browser, then save as PDF if you want an internal working copy.
1. AI inventory and approvals
- Approved AI tools and high-value use cases are inventoried by owner.
- New AI vendors or models require a lightweight approval review.
- Shadow AI discovery is part of ongoing governance, not an annual surprise.
2. Data handling and prompt hygiene
- Permitted and prohibited data classes are defined for AI use.
- Employees know when redaction or sanitization is required.
- Prompt and output handling expectations are documented clearly enough to follow.
3. Human review and workflow controls
- High-impact workflows have named reviewers before output is used externally.
- AI-assisted decisions in finance, legal, HR, or customer commitments are treated as higher risk.
- Exception paths exist when teams need faster review or temporary approval.
4. Vendor terms and monitoring
- AI vendor terms are reviewed for retention, training use, and security commitments.
- Monitoring exists for misuse, unsafe output, or policy drift.
- AI-specific incident triggers are tied into the broader response process.
5. Executive visibility
- Leadership can see current AI use, top risks, and open actions in one reporting view.
- Ownership for AI controls is explicit across security, legal, IT, and business teams.
- The next decision for leadership is documented, not implied.
Optional email copy
Want a copy in your inbox as well? Use the lightweight form below. The checklist is already available on this page.
Prefer email first? Reach us at john@vantageciso.com.