A practical governance baseline for companies adopting generative AI, covering approved tools, sensitive information, account access, output review, intellectual property, and incident response.
Answer the questions employees face every day
A policy made only of principles is difficult to apply. Employees need to know which tools are approved, what information cannot be uploaded, whether an output can be published directly, and whom to contact when something goes wrong.
Organize common activities into prohibited, approval-required, and permitted categories with concrete examples. Clarity reduces both complete avoidance and unsafe experimentation.
Set a minimum bar for data and tool approval
Customer data, non-public financial information, source code, and trade secrets require input restrictions aligned to the company’s security classification. New tools should also be assessed for retention, training use, access controls, logging, and deletion.
Prefer governed tools and centralized identity over unmanaged personal accounts where business data becomes difficult to find, secure, or delete.
- Define information that must never be entered
- Maintain an approved-tool register with permitted use cases
- Assign owners for accounts, access, and logs
Sustain the rules through training, sampling, and incident review
Train with role-specific examples and sample real usage after launch. High-risk workflows may need records of source inputs, material edits, and the final approver to preserve necessary accountability.
Define how to suspend use, report, investigate, and improve after an error or exposure risk. Reviews should correct systemic causes instead of focusing only on individual blame.
FAQ
Questions about this topic
Is banning public AI tools enough to keep a company safe?
No. A ban can push usage into less visible personal channels. Companies also need usable approved tools, training, and clear data boundaries.
How often should a generative AI policy be reviewed?
Review it at least every six months and immediately when tools, regulations, business use cases, or material risks change.