An AI policy helps define how employees can use AI tools responsibly at work, balancing innovation with security, compliance, and governance. As employees use AI to summarize meetings, draft content, analyze data, generate code, and automate routine tasks, undefined usage may introduce security, compliance, and quality risks, such as sharing confidential information with unapproved tools or relying on inaccurate outputs. An effective policy may address approved tools and acceptable use cases, data privacy and security requirements, human review and accountability, and training and escalation paths. These categories are not exhaustive; each organization should adapt them based on its AI use cases, risk profile, regulatory environment, and workforce needs. Responsible AI generally refers to using AI with appropriate oversight, transparency, and accountability, while ethical AI focuses on fairness, privacy, bias, and potential impacts on people. The real goal is creating a policy employees can understand, trust, and apply in day-to-day work, supporting innovation while helping teams handle sensitive information responsibly and account for compliance requirements. For technical decision makers, this means balancing governance with usability so policies are practical enough to follow across the organization.