What should the glossary section of an AI policy do?

• A. Clearly explain and define AI terms and acronyms
• B. Provide a detailed implementation roadmap
• C. Describe data governance roles only
• D. Set the project budget and timeline

Answer: (A)

Establishing a shared vocabulary is essential. The glossary should clearly explain and define AI terms and acronyms so all readers interpret the policy consistently. By providing precise definitions for terms like AI, machine learning, models, datasets, bias, explainability, privacy, and governance concepts, the policy becomes accessible to both technical and non-technical stakeholders and reduces ambiguity. This foundation supports clear requirements, compliance alignment, and effective governance across the policy’s lifecycle.

Other options pull the reader into how to implement or manage the project rather than clarifying language. A detailed implementation roadmap belongs in an implementation or execution plan, not a glossary. Describing data governance roles only narrows the scope, whereas a glossary should cover terms broadly. Setting the project budget and timeline is about project management, not ensuring shared understanding of terminology.