AI is in our institutions. The rules must catch up.

Artificial intelligence is already at work inside many Black businesses, churches, nonprofits and community organizations. It may not have arrived through a formal strategy or a major technology purchase. It may have entered through an employee drafting a grant proposal, a pastor preparing study materials, a volunteer creating social media content or a manager reviewing job applications.

The tool is already in the building. In many cases, the rules are not.

That gap creates a leadership problem. People are making daily decisions about what information to enter, which results to trust and how much work to turn over to a machine. Without clear direction, each person creates a personal standard. One employee may protect confidential information carefully. Another may place client records, personnel details or internal financial information into a public system without understanding where that information goes.

The absence of an AI policy does not mean an organization has chosen not to use AI. It usually means AI is being used without shared boundaries or accountability.

Black institutions have always done more with less. That history makes AI attractive. A small staff can use it to summarize documents, prepare first drafts, organize information and reduce administrative work. A business owner can complete tasks that once required outside help. A nonprofit can stretch limited resources. A church can support ministry without adding another position.

Those benefits are real. So are the risks.

Our institutions often hold sensitive information about employees, customers, donors, members and families. They operate through relationships built over years. A careless use of AI can expose private information, spread false claims or produce language that does not reflect the values of the organization. A poorly reviewed recommendation can affect hiring, discipline, lending, services or access to opportunity.

Large organizations may have legal teams, security departments and technology specialists to address these problems. Smaller institutions may have none of them. That does not reduce the responsibility. It makes a clear policy more important.

An AI policy does not need to begin as a 50-page manual. It should start by stating what the organization permits and prohibits.

Leaders should identify which tools employees may use for organizational work. They should define which tasks are appropriate for AI assistance and which require direct human judgment. Drafting routine correspondence may be acceptable. Allowing a system to make a final decision about hiring, discipline or financial eligibility should require much greater scrutiny.

The policy should apply to everyone who handles the organization’s work, including employees, contractors, board members and volunteers. Risk does not change because the person using the tool is unpaid.

Next, organizations should protect information before it leaves the building. A policy should state which information must never be entered into a public AI system. The list should include personal identifying information, health information, employee records, client files, legal matters, passwords, financial account details and confidential business plans.

People often treat an AI conversation like a private exchange with a trusted assistant. It is not. Information entered into an outside system may be stored, reviewed or processed under terms the user has never read. Good intentions do not protect information once it has been disclosed.

The safest rule is simple. If the information would not be sent to an unknown outside party, it should not be placed into an unapproved AI tool.

Organizations should also require verification. AI can produce writing that sounds polished and authoritative while containing false information, invented sources or missing context. Fluency is not the same as accuracy.

Every organization should require a person to review AI-assisted work before it is published, submitted or used to make a decision. That person should be able to evaluate the subject, not merely proofread the wording. The reviewer must confirm facts, examine sources and consider whether the result treats people fairly.

Responsibility remains with the person and the institution whose name appears on the work. Blaming the tool after an error will not restore trust.

Some decisions carry too much consequence to be handed to a system at all. Employment, discipline, pastoral care, financial assistance and access to services require context, empathy and accountability. AI may help organize information, but a responsible person must remain answerable for the outcome.

That human review must be meaningful. A person who routinely approves whatever the system recommends is not providing oversight. The reviewer needs the authority, information and time to challenge the result.

Finally, every organization using AI should name one person responsible for overseeing its use. That person does not need to be a technology expert. The role requires enough authority to set expectations, respond to concerns and make sure the policy is followed.

Leadership cannot assign responsibility to a tool or a vendor. When an AI system affects people, the institution remains accountable for the decision.

Black institutions should use AI. We should use it to reduce administrative burdens, extend our reach and direct more energy toward the people we serve. We should do so with discipline.

The choice is not between using AI and avoiding it. The choice is between using it intentionally and allowing it to spread without direction. The rules do not need to be complicated. They need to be written, understood and enforced.

Dwayne C. Dixon is an ethical AI strategist and a member of the National Black MBA Association AI Advisory Council. His column, Bridging the Code, runs monthly in the MSR.  For more, visit www.dwaynedixon.com and www.ethicalaibook.com. You can also reach him directly at dcd@dwaynedixon.com.