An AI compliance checklist gives B2B teams a concrete starting point for governing AI: inventory your AI use, classify it by risk, lock down data handling, require human oversight and disclosure, vet vendors, write a policy, and review it on a cadence. Here's the practical list.

You don't need a full governance program to start reducing AI risk — you need to work through the essentials in order. Use this checklist as a self-assessment; the gaps it surfaces are your priorities.

1. Inventory every AI use

List all AI in use — standalone tools, features embedded in existing software, internal models, and the shadow AI your team already uses without approval. You can't govern what you can't see, and shadow AI is usually the biggest blind spot.

2. Classify each use by risk

Sort uses by exposure and by regulatory tier — the EU AI Act tiers are a useful lens. High-risk and customer-facing uses get the most scrutiny; minimal-risk uses get less. This is the core of an AI risk assessment.

3. Control what data goes into AI tools

Define which data classes (public, internal, confidential, regulated, personal) can go into which tools. Most real AI incidents are data incidents — confidential or customer data pasted into a consumer tool. Approve specific tools for specific data.

4. Require human oversight where it matters

Anything customer-facing, legal, financial, or high-stakes should have a human reviewing AI output before it's used. Document where review is mandatory.

5. Set disclosure rules

Decide when AI involvement must be disclosed — to customers, in content, in chatbots. This is both an ethics and a regulation question, and it's central to responsible AI in marketing.

6. Vet AI vendors

Before adopting a tool, check how it handles your data, whether it trains on your inputs, its security posture, and its own compliance. See AI vendor risk assessment. Put an approval step in front of new tools so adoption doesn't reopen closed risks.

7. Check bias and accuracy on consequential uses

Where AI outputs affect people (hiring, credit, customer treatment) or where wrong outputs cause harm, test for bias and accuracy rather than assuming the model is right.

8. Write an AI use policy

Turn the above into a clear, usable AI use policy with acceptable use, oversight, disclosure, data rules, and vendor approval — fitted to how your company actually works.

9. Assign ownership

Name an owner for AI governance and for each policy area. Unowned policies don't get followed or updated.

10. Review on a cadence

AI and its regulation change fast. Set a recurring review to re-inventory, re-assess, and update policy — the essence of AI governance and of ongoing advisory.

Turn the checklist into a program

Working through this list is the fastest way to see where you stand. If you'd rather have it run for you — assessment, policy, and a plan — that's our AI risk assessment and AI compliance and policy assessment. (This checklist is practical guidance, not legal advice.)

Frequently asked questions

What should be on an AI compliance checklist?

Inventory all AI use, classify by risk, control data handling, require human oversight, set disclosure rules, vet vendors, test bias and accuracy on consequential uses, write an AI use policy, assign ownership, and review on a cadence.

Where do most AI compliance problems come from?

Data handling — confidential, customer, or regulated data entered into unapproved AI tools — and ungoverned shadow AI. Controlling what data goes into which tools closes the most common incidents.

How do I classify AI risk for compliance?

By exposure (data, privacy, bias, IP, reputation) and by regulatory tier — the EU AI Act's tiers are a useful lens. High-risk and customer-facing uses get the most scrutiny.

Do B2B companies really need AI compliance?

Yes. Even without customer-facing AI, most teams use AI tools with confidential data and no oversight, and enterprise buyers increasingly ask how you govern AI. A basic program reduces real risk and supports sales.

Is an AI compliance checklist enough?

It's a strong start and a good self-assessment, but compliance is ongoing. Turn the checklist into a policy with owners and a review cadence so it keeps up with new tools and evolving regulation.