AI tools can help a small team draft emails, summarize documents, analyze sales, and answer routine questions. The risk grows when people paste customer details into unfamiliar services or trust an answer without checking it. A short, written AI policy gives everyone the same practical boundaries before the tools become part of daily work.
You do not need a legal department to begin. Start with the rules below, adapt them to your business, and review them whenever your tools or workflows change. The National Institute of Standards and Technology (NIST) offers a voluntary AI Risk Management Framework that organizations of different sizes can use to think through AI risks.
1. Name the business purpose
For every approved AI use, write down the task and the expected benefit. “Draft a first version of a customer support reply” is clearer than “use AI for support.” A defined purpose makes it easier to decide what information the tool needs and whether its output is useful.
2. List approved tools and accounts
Keep a simple list of AI services your team may use, who owns each account, and which tasks are allowed. Prefer business accounts with controls that fit your needs. Tell employees where to ask before signing up for a new tool or connecting it to company email, cloud storage, or a customer database.
3. Set a clear data boundary
Explain what must not be entered into a prompt. A sensible starting rule is to keep passwords, payment details, government IDs, private customer records, employee files, confidential contracts, and unreleased business information out of unapproved tools. When a task can be completed with a fictional example or anonymized data, use that instead.
Before connecting a service to business data, check its privacy and retention settings, who can access the information, and whether the connection can be limited to the files needed for that task. Do not assume every AI service handles data in the same way.
4. Keep a person responsible for decisions
AI can prepare a draft or organize information; a named person should remain responsible for decisions that affect customers, money, hiring, safety, or contractual commitments. Require a human review before sending sensitive messages, changing records, issuing refunds, or making promises on behalf of the business.
5. Verify facts before acting
Ask staff to check names, dates, calculations, citations, product details, and policy claims against a reliable source. For important outputs, keep the original source alongside the AI draft. A confident tone is not proof that an answer is correct.
6. Limit access and connected actions
Give each tool only the access it needs. Start with read-only or draft-only permissions when possible, and require approval before an AI feature sends, edits, deletes, or purchases anything. Review connected apps periodically and remove access when a workflow ends.
7. Tell people when AI is involved
Decide when customers or colleagues should be told that AI helped create a response, image, or recommendation. Be especially clear when someone may reasonably expect a person to be handling the conversation. Transparency helps people understand how to request human assistance.
8. Create a simple incident process
Give employees one place to report a mistaken AI response, an accidental data disclosure, a suspicious output, or an unexpected action. Record what happened, which tool was involved, and what the team changed. If personal or regulated information may have been exposed, follow your organization’s response plan and applicable requirements.
9. Review the policy on a schedule
Choose an owner and revisit the rules every few months, or sooner when a tool adds new capabilities or connects to more systems. Ask staff which rules are unclear, test a workflow with non-sensitive information, and update the approved-tool list as your needs change.
A 30-minute way to get started
Spend ten minutes listing the AI tools already in use. Use the next ten to mark what data may and may not be shared. Then name the person who reviews important outputs and decide how the team reports a problem. Put those decisions in a one-page document, share it with everyone, and set a date to review it.
This checklist is an operational starting point, not legal advice. Privacy, employment, and consumer-protection obligations vary by location and by the information your business handles. For a structured risk-management reference, see the NIST AI Risk Management Framework and its Generative AI Profile.
A good small-business AI policy does not need to predict every future tool. It needs to make today’s boundaries clear: use AI for a defined task, protect information, check the output, and keep a person accountable.
