Most companies now have staff using AI tools that management never approved and never reviewed. That gap is where data leaks and wrong answers enter the business. Appjad (أبجد) works with owners across the Gulf on exactly this: making AI useful under rules everyone can see. This is a checklist you can work through today and turn into a one-page policy your team actually follows.
Key takeaways
- Find out where AI already touches your company before you write any rules.
- Decide what data may and may not reach an AI tool, and put it in writing.
- Every AI output that reaches a customer or a decision needs a named human owner.
- A policy nobody has read protects nobody — one page and a short briefing beat a manual.
Map where AI already enters your company
Before setting rules, learn the current reality. Ask department heads a direct question: which tools, plugins or AI features are already in use, even informally? Most owners discover more entry points than expected.
- List every AI tool staff use, including features hidden inside office software and browsers.
- Mark which ones touch customer data, financial data or internal documents.
- Note which have no approved account, no admin control and no usage record.
Draw the line on data before anything else
The single most important decision in an AI policy is what information may be entered into which tool. Make it concrete, not general. Appjad recommends naming categories, not writing vague warnings.
- Write down the data categories your company holds: customer records, contracts, pricing, staff files, financials.
- For each category, decide: may it be entered into an external AI tool, only into approved internal systems, or nowhere?
- Define what counts as confidential in one sentence your staff can repeat from memory.
- State the rule for pasted text: if you would not email it outside the company, it does not go into an external AI tool.
Decide who approves what AI produces
AI drafts, summarizes and suggests. A person must still own the result. Assign that ownership explicitly, or it defaults to nobody.
- Customer-facing messages: a named person reviews before anything is sent.
- Decisions on pricing, credit or hiring: AI may prepare analysis, but a manager decides and signs.
- Published content: an editor confirms facts and tone before release.
- When an AI assistant serves customers directly, define the topics it may answer and the point at which it hands over to a human.
An AI policy is not a document about technology. It is a set of decisions about who may see what, and who answers for the result.
Write the policy in one page, not a manual
A long policy gets skimmed and forgotten. One clear page, reviewed with the team, changes behavior. Appjad writes client policies to answer five questions in plain language.
- Which AI tools are approved, and how do I request a new one?
- What data may I enter, and what must never be entered?
- Who reviews AI output before it reaches a customer or a decision?
- What do I do if sensitive data was entered by mistake, or if an AI answer looked wrong?
- Who is the named person I ask when I am unsure?
Review conversations, access and rules on a schedule
A policy written once and never revisited drifts out of date as tools and staff change. Put the review itself on the calendar.
- Monthly: sample AI assistant conversations for quality and off-topic answers.
- Quarterly: review who has access to which AI systems, and remove what is no longer needed.
- Twice a year: revisit the approved tool list and the data rules against new features and new risks.
Next step: put the policy in front of your team
Block one hour this week, run the checklist above, and turn your answers into the one-page policy. Then brief the team and name the person who owns it. If you want the policy aligned with your systems, data flows and customer-facing AI from the start, Appjad (أبجد) can review your current setup and draft it with you — contact us to start with a short diagnostic.
