AI Governance Checklist

AI Governance Checklist for Enterprise Teams

Use this checklist to evaluate whether your organization has the visibility, policy enforcement, privacy guardrails, data ownership, and review paths needed for secure AI adoption.

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Checklist Coverage

Usage visibility

Review the controls and ownership expectations needed before AI adoption scales.

LLM governance

Review the controls and ownership expectations needed before AI adoption scales.

Data protection

Review the controls and ownership expectations needed before AI adoption scales.

Policy enforcement

Review the controls and ownership expectations needed before AI adoption scales.

Auditability

Review the controls and ownership expectations needed before AI adoption scales.

Shadow AI risk

Review the controls and ownership expectations needed before AI adoption scales.

Checklist Preview

Start with the areas most teams need to review first

Preview the first sections below, then unlock the full ten-part checklist for LinkedIn campaign follow-up, governance planning, and internal readiness reviews.

AI usage visibility

Identify which teams use ChatGPT, LLMs, copilots, agents, and AI-powered workflows.
Define where approved AI usage should happen and where unmanaged usage creates risk.
Give security, privacy, and compliance teams enough visibility to review adoption patterns.

ChatGPT and LLM governance

Document which models and AI tools are approved for business use.
Clarify what employees can and cannot share with ChatGPT and LLM tools.
Create governed paths for common AI workflows before teams default to personal accounts.

Sensitive data protection

Define sensitive data categories that need stronger AI guardrails.
Review how customer, employee, proprietary, regulated, and operational data may appear in prompts.
Set expectations for source access, output review, and data handling across AI workflows.

Get The Full Checklist

Unlock all ten AI governance review areas

Share your details to view the full checklist on this page. You will also be able to request access to InfoDump when you are ready to turn the checklist into a governed adoption path.

Related Governance Topics

Turn the checklist into a governed AI adoption path

AI governance layer

See how InfoDump frames the governance layer between teams, AI tools, models, and systems.

AI policy enforcement

Connect policy expectations to the way employees, models, tools, and systems interact.

AI usage monitoring

Understand how teams adopt AI before unmanaged workflows become the default.

Shadow AI governance

Reduce unmanaged AI risk by creating approved paths for useful AI work.

ChatGPT data privacy

Use ChatGPT and LLM tools with stronger privacy and data ownership expectations.

FAQ

Questions before using the checklist

Who should use this AI governance checklist?

Security, privacy, legal, compliance, platform, operations, and executive teams can use this checklist to evaluate whether AI adoption has enough visibility, policy coverage, and data ownership control.

Is this checklist a replacement for an AI policy?

No. The checklist helps teams turn AI policy goals into practical review areas, but organizations still need policies that reflect their own data, risk, and operating requirements.

How does InfoDump help with these checklist areas?

InfoDump gives organizations an AI governance layer for privacy guardrails, policy enforcement, controlled source access, AI usage visibility, and data ownership across ChatGPT, LLMs, and AI tools.

Use The Checklist With InfoDump

Ready to make AI adoption easier to govern?

Talk with InfoDump about privacy, policy enforcement, AI usage monitoring, and data ownership before unmanaged workflows become the default.