What best characterizes AI model catalog maintenance?

• A. It tracks AI products/services developed internally.
• B. It catalogs data schemas.
• C. It controls user access.
• D. It stores all training data.

Answer: (A)

Centralizing and keeping up-to-date an inventory of models that the organization has developed is what AI model catalog maintenance focuses on. A well-maintained catalog records each model’s identity, version, deployment status, ownership, intended use, and provenance, plus key metadata such as training data references, performance metrics, and governance or compliance notes. This enables reuse of existing models, helps with reproducibility and auditing, and supports lifecycle management from development through production to retirement. By having clear records of what exists and who is responsible for it, teams can govern risk, ensure proper access, and plan updates or decommissioning safely. Cataloging data schemas, controlling user access, or storing all training data serve other aspects of data management and security, not the model inventory itself.