An AI security checklist gives a business a calm way to decide whether a useful new tool belongs in everyday work. It turns “Is this AI safe?” into practical decisions about information, access, accountability, and what the team will do if something goes wrong.
AI often arrives quietly. A familiar software provider adds a writing assistant. A meeting tool offers summaries. A browser extension promises faster research. Each feature may be useful, but it can also change where business information travels and which systems a vendor can reach.
The right goal is not to ban useful technology. It is to let businesses adopt it with clear boundaries. Use this checklist before an AI tool receives business information, connects to a company account, or influences a decision that affects customers, money, people, or security.
1. Name the business purpose and an accountable owner
Start with the work the tool is meant to improve. Write down the task, the team using it, and the person responsible for approving it. “Use AI for productivity” is too broad. “Draft first-pass responses to public event inquiries, with staff approval before sending” is a use that can be reviewed.
Clear ownership prevents a trial from becoming permanent simply because it is convenient. The owner does not need to be a technical specialist. They do need authority to set limits, ask for help, and revisit the decision when the workflow changes.
2. Identify the information the tool will see
List what employees might type, upload, summarize, or retrieve through a connection. Include direct prompts as well as background access to email, calendars, shared files, meeting recordings, customer systems, or cloud storage.
For most businesses, a simple distinction works well: public information can be used only in approved tools; internal information needs a company-managed account and a known purpose; confidential or restricted information needs a documented review before it enters an AI workflow. That includes customer records, financial data, passwords, access tokens, security details, private contracts, and information protected by an obligation to someone else.
3. Use a company-managed account
A personal account may be easy to create, but it gives the business less visibility and less control. Use a company-managed account when AI is part of work. Confirm who can add and remove users, require stronger sign-in protection, and make sure access can be removed promptly when a person leaves or changes roles.
This is also the point to check vendor settings. Can the business limit sharing, control integrations, and understand how prompts and files are handled? If the answers are unclear, keep the use limited while the business gets a clearer picture.
4. Review connections and permissions
An AI tool can create risk without a single sensitive prompt. A meeting assistant may access recordings. A search feature may read shared drives. A browser extension may see pages an employee opens. Record every connection the tool requests and give it only the access needed for the approved use.
The OWASP guidance for AI applications is a useful reminder that sensitive-information disclosure and excessive permissions deserve attention. Businesses do not need to become AI laboratories. They do need to ask whether a requested connection is necessary and whether the available controls match the risk.
5. Set the human review point
AI can prepare, summarize, classify, and suggest. It should not quietly become the final decision-maker for customer commitments, payments, hiring, access changes, security actions, or other consequential work. Define who checks the output and what they must verify before the business acts.
The NIST AI Risk Management Framework organizes AI risk work around governing, mapping, measuring, and managing risk. For a business, that translates into a simple habit: set the rule, understand the use, check the result, and respond when the risk changes.
6. Decide what is approved, limited, or off-limits
- Approved: A low-risk use with a company-managed account, limited data, and clear human review.
- Approved with safeguards: A useful tool that needs named data limits, limited connections, and a review date.
- Pilot only: A use that touches sensitive information or important workflows, but can be tested within tight boundaries.
- Not approved: A tool with unclear data practices, unnecessary permissions, or no realistic way to supervise the use.
Write the decision down in plain English. A good record says what is allowed, what must not happen, who owns the use, and when it will be reviewed.
7. Give teams a route to report a problem
People need to know what to do after an accidental upload, an unexpected connection, or a result that does not look right. Make the route short: pause the activity, preserve enough detail to understand what happened, and tell the named owner or technology contact promptly.
This is not about blame. Early reporting gives the business a chance to review access, limit exposure, and improve the rule before a small mistake becomes a larger problem. Pair the checklist with an AI acceptable use policy so the day-to-day expectations are equally clear.
Make the checklist part of normal technology decisions
Keep the checklist alongside vendor and account records, then use it when teams enable a new AI feature, connect a new service, or expand a pilot. Review approved uses at least annually, and sooner when the vendor adds a major capability, requests broader permissions, or begins handling a new type of information.
Businesses that want a clearer view of existing AI use can start with an AI risk assessment. H3Systems can help owners and teams connect that review to practical controls around accounts, data, vendors, and response planning, so useful adoption does not come at the cost of visibility or control.
Request a Risk Review with H3Systems to turn this checklist into an approach that fits the systems and information your business relies on.
