An AI policy is useful only when an employee can apply it during real work. A document filled with broad principles may satisfy an initial legal review but still leave people unsure whether they can summarize a meeting, upload a spreadsheet, draft a client message, or use an agent to take action.
An operational policy translates risk appetite into decisions, owners, and examples.
The minimum policy structure
Purpose and scope
State which employees, contractors, tools, models, agents, and business processes are covered. Clarify that the policy applies to free accounts, browser extensions, embedded AI features, APIs, and custom applications—not only named chat products.
Approved and prohibited use
Describe permitted categories and prohibited activities. Use examples tied to work. A simple matrix can distinguish public-content drafting from restricted-data processing or consequential decisions.
Data boundaries
Define what data may enter which environment. Address confidential information, personal data, credentials, privileged material, source code, regulated records, and third-party information. Link to existing classification rules rather than inventing a second vocabulary.
Human accountability
State that capability does not equal permission. An AI system may be technically able to recommend, send, publish, approve, or modify something without being authorized to do so. Identify outputs that require review and the person accountable for the final decision.
Evaluation and recordkeeping
Require appropriate testing before higher-impact use. Define what evidence must be retained: use-case owner, model or tool, test set, limitations, approvals, monitoring results, and incidents.
Exceptions and escalation
Give employees a fast route to request a new tool or use case. Define who can approve exceptions, for how long, and with which conditions.
Make the policy usable
Publish a one-page employee standard alongside the full policy. Include an approved-tool list, data examples, review rules, and a contact point. Train managers with scenarios because they are often the first people asked to interpret the rules.
Avoid hard-coding product claims that change frequently. Link to a maintained tool register that records product tier, contractual terms, retention settings, administrator controls, and current approval status.
Roll out policy with capability
Policy alone does not create safe behavior. Pair it with approved access, practical training, role-based workflow examples, office hours, and an intake process. When employees understand both the boundary and the supported path, compliance becomes easier.
Review cadence
Review the policy on a defined schedule and after material changes: a new product tier, a significant incident, a new agent capability, a regulatory change, or expansion into a higher-impact workflow. Record the owner and next review date.
A strong company AI policy should shorten decision time. It should help people move useful work forward while making restricted activity and accountable ownership unmistakable.