SMB AI Acceptable Use Policy (AUP): Simple Guardrails That Actually Work

Alan S
4 days ago
3 min read

AI tools like ChatGPT are now part of day-to-day work for most teams. Writing emails, summarizing meetings, drafting proposals, even troubleshooting technical issues. That productivity boost is real.

But so is the risk: AI makes it easy to accidentally share sensitive information (client details, contracts, passwords, financials) in a place it never should have gone. For small and mid-sized businesses, one “helpful” prompt can turn into a compliance issue, a client trust issue, or a security incident.

The fix isn’t banning AI.

The fix is having a clear, one-page AI Acceptable Use Policy that makes the safe path the easy path. Below you will find a template AUP you can adapt for your SMB.

Why SMBs need an AI policy now (even if you’re “not a target”)

Most data exposure doesn’t happen because someone is malicious. It happens because someone is trying to move fast:

Copy/pasting a client email thread to “summarize it”
Uploading a contract to “simplify the terms”
Sharing a spreadsheet to “find insights”
Dropping in a screenshot that includes names, pricing, or account info
Pasting logs that contain tokens, API keys, or credentials

SMBs are especially vulnerable because they often adopt AI organically, without centralized approvals, training, or technical guardrails.

A simple policy creates alignment fast:

What AI tools are allowed
What data is never allowed
What requires review before it’s sent out
What to do if something goes wrong

What a good SMB AI Acceptable Use Policy should include

A workable policy isn’t a 12-page legal document. It’s a one-pager that’s easy to follow. The best ones cover:

1) What AI can be used for

Examples:

Drafting or polishing non-confidential content
Brainstorming outlines and ideas
Summarizing sanitized notes
Writing templates and internal training material

2) What can NEVER go into AI tools

Clear categories matter. At a minimum, restrict:

PII/PHI (customer or employee sensitive info)
Credentials, API keys, tokens, passwords, MFA codes
Contracts, legal matters, pricing, client lists, proposals
Internal financials (payroll, forecasts, margins)
Security incidents, vulnerabilities, internal diagrams/configs
Proprietary codebases or “secret sauce” logic
Anything under NDA or client confidentiality terms

3) Approved tools and accounts

This is where most businesses slip.

Company-approved tools only
Company-managed accounts (avoid personal accounts for work)
No unapproved AI browser extensions or plugins

4) Human validation rules

AI is helpful, but it’s not a source of truth.Require review for anything:

client-facing
financial, legal, or security related
used in marketing claims or compliance documentation

How to roll this out without slowing down the business

You can implement this in under a week:

Step 1: Pick your “approved AI stack.” Keep it simple: 1–2 tools your team can rely on.
Step 2: Share the one-page policy + a 10-minute walkthrough.Make it practical: show “good” vs “bad” prompts.
Step 3: Add lightweight guardrails. Depending on your environment: SSO, logging, browser controls, DLP, and restrictions on personal accounts.
Step 4: Make the safe path the default. Templates, approved workflows, and a clear escalation path for questions.
Step 5: Review quarterly. AI changes fast. Policies should too.

Download: Free SMB AI Acceptable Use Policy (One Page)

I’m sharing a free, one-page template you can customize for your business.

👉 Download the PDF:

Important note

This template is meant to be a practical starting point. It is not legal advice. If you operate in regulated industries (healthcare, financial services, education, etc.), you may want your counsel/compliance team to review before rollout.

Want help tailoring this to your environment?

If you want to go beyond policy and actually operationalize AI safely, I help SMBs:

select an approved AI toolset
define restricted data categories
implement practical guardrails (without killing productivity)
train teams on safe workflows
set validation standards so AI outputs don’t become business risk

If you’d like, message me and I’ll share a quick implementation checklist you can use alongside this policy.