An administrator is troubleshooting a pilot deployment and wants the most appropriate next step. What is the best way to handle factsheets and evidence while staying aligned with the certification objectives?

Here's the deal: think of factsheets and evidence like labeling the cables before you close the rack door. If you skip that discipline, troubleshooting gets ugly fast. In this scenario, answer C is the practical move because it keeps the implementation tied to the real IBM capability instead of chasing a shortcut. The other choices sound tempting, but they either skip governance, ignore operational reality, or solve the wrong problem.

The correct answer is C. Use factsheets and evidence records to document model purpose, data, evaluations, and decisions. That aligns with the 2.0 AI Lifecycle Governance objective because it applies the feature or practice in the context where IBM expects a practitioner to use it. It also keeps the design reviewable, supportable, and realistic for a production environment.

Let's examine why the other options are incorrect: - Option A is incorrect because it narrows the solution to one artifact or metric and misses the broader factsheets and evidence requirement. - Option B is incorrect because it narrows the solution to one artifact or metric and misses the broader factsheets and evidence requirement. - Option D is incorrect because it skips the control or validation that makes factsheets and evidence reliable in production. For the exam, connect the feature to the operational outcome: the right answer is the one that preserves control, accuracy, and maintainability instead of relying on a brittle shortcut. The incorrect options — such as 'Put evidence only in slide decks' and 'Document only the model name' — describe either out-of-sequence steps or unrelated configuration tasks. This concept falls under the 2.0 AI Lifecycle Governance domain of the IBM watsonx.governance certification.