A project lead is turning a proof of concept into a governed production workflow. For IBM Certified watsonx Governance Lifecycle Advisor, the topic is change management. What should the team do?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Change management for AI is like a pilot's updated flight plan — any significant deviation requires a new clearance, not just relying on the old one. Option D ensures new clearances happen: reassess when data, purpose, version, or risk conditions materially change. Permanent approval ignores reality. Skipping prompt-change reviews for generative AI is especially risky. Monitoring only the first version means flying blind after that. New conditions demand new review — option D!
Full explanation below image
Full Explanation
The correct answer is D. Reassess models when data, purpose, version, or risk conditions materially change. aligns directly with the 2.0 AI Lifecycle Governance exam objective and reflects how IBM watsonx.governance operationalizes this practice in enterprise environments. IBM watsonx.governance is designed to provide the tooling, workflows, and evidence collection mechanisms that make AI trustworthy and auditable from intake through retirement. Choosing this option ensures the implementation is both defensible to regulators and maintainable by governance teams across the full AI lifecycle. Option A is incorrect because it assumes static conditions and eliminates the reassessment that IBM watsonx.governance explicitly requires. Option B is incorrect because it eliminates a required control and leaves the governance program without a critical safeguard. Option C is incorrect because it narrows the scope to a single artifact or metric and misses the full governance requirement. On scenario-based exam questions, the correct answer is consistently the one that operationalizes the IBM governance practice with structured controls rather than approximating it with shortcuts, manual workarounds, or oversimplified rules.