Why an AI policy matters
Employees are already using AI to summarize emails, write documents, analyze data, troubleshoot code, and draft customer responses. Without guidance, sensitive data may be pasted into tools the business does not control.
The goal is not to ban AI. The goal is to make safe use easy and risky use clearly prohibited.
Data that should not go into public AI tools
Do not enter patient data, customer records, employee files, passwords, API keys, contracts, source code, financial data, unreleased business plans, CUI, or confidential vendor information into public tools unless the business has approved the tool and data handling terms.
Approved use cases
Good starter uses include rewriting public marketing copy, drafting generic policies, brainstorming training ideas, summarizing non-sensitive notes, creating templates, and improving internal process documentation.
Higher-risk uses require review: clinical content, legal content, regulated data, financial decisions, customer communications, and automated actions.
Human review
AI output should be reviewed by a responsible person before being used for customer, patient, legal, financial, employment, or compliance decisions.
Do not allow AI to become the final approver for sensitive business actions.
Secure AI workflows
Use approved accounts, role-based access, logging where available, data minimization, prompt templates, and internal review steps. For regulated data, consider local or private workflows before cloud AI.
Starter employee policy language
Employees may use approved AI tools for authorized business purposes. Employees may not submit confidential, regulated, customer, patient, employee, credential, or contract data into unapproved AI systems. AI-generated output must be reviewed before business use.
Manager checklist
Define approved tools, prohibited data, review requirements, escalation path, recordkeeping expectations, and consequences for unsafe use.
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