Governance & compliance
A clear policy is what lets a team move fast without stepping on legal or reputational landmines. It turns AI from a free-for-all into a managed capability.
In plain terms
An AI policy is a company's written rules for how AI may and may not be used, covering data, approved tools, and human oversight.
An AI policy tells staff what they may use, what they may not paste, and who to ask. It should fit on a page they will actually read. Tools that are allowed. Data that is banned. When a person must review before something goes to a customer. Where to report a mistake.
A policy nobody can apply in the moment is a PDF. Put the one-page version where the work happens, and make the approved tool easier than the personal one. Review the page when you approve a new tool. The riskiest gap is not a missing paragraph. It is staff who have never seen the page.
Think of it this way: An AI policy is the equivalent of an acceptable use policy for company devices. It does not stop every misuse, but it sets clear rules, removes ambiguity, and creates a documented basis for accountability.
A media company publishes a one-page internal AI policy: which tools are approved, what data cannot enter AI tools, how AI-generated content must be disclosed, and who to contact with questions. Adoption of approved tools doubles.
A company publishes a twelve-page AI policy. Six months later, a contractor pastes client source code into a free tool. They had signed the policy. They had not been given an allowed tool or a short list of banned data. The replacement is one page, a default tool on their account, and five minutes in onboarding.
Write the policy before employees need to make their own judgment calls. A clear policy in place before an incident is an asset. A policy written after an incident is a defense. An AI policy without enforcement and approved alternatives is security theater. The policy is the starting point; the approved tool stack and training are what make it operational.
RaftLabs writes the control into the system: which data can enter, who approves the result, and how you explain it later. The rule and the product stay the same story. The related work on our side is AI governance.
This sits with the other governance & compliance terms on the glossary. The rules that keep AI legal, and keep customer data out of the wrong tool. Worth reading next: Data Privacy / PII, GDPR & Compliance, and Model Governance.
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