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Generative AI Leader Practice Question: A compliance officer requires that all…
A compliance officer requires that all AI-generated content in Google Workspace be reviewed before sharing externally. Which change management approach BEST supports this requirement while maintaining user adoption?
⚠ Common exam trap
The trap here is conflating 'preventive control' with 'post-hoc audit' — candidates pick auditing or hard blocking because they sound strict, but the question requires both compliance enforcement and maintained user adoption, which only a phased pilot with training achieves.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Roll out the feature to a pilot group with training and a feedback loop before company-wide deployment
A phased pilot with training and a feedback loop lets the compliance team validate that AI-generated content is reviewed before external sharing while giving users time to adapt, which preserves adoption. This change management approach balances governance with user enablement, reducing resistance and surfacing issues before broad rollout.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Roll out the feature to a pilot group with training and a feedback loop before company-wide deployment
Why this is correct
A pilot with training and a feedback loop surfaces review-workflow friction on a small scale, letting the compliance requirement for pre-sharing review be validated before company-wide rollout. This preserves user adoption by incorporating feedback rather than imposing controls abruptly.
- ✗
Allow all sharing but audit logs after the fact
Why it's wrong here
Auditing after the fact detects violations only once content has already been shared externally, so it cannot satisfy a requirement that review occur before sharing. Pre-share review gates enforce the control at the point of disclosure.
- ✗
Disable AI features in Workspace for all users until a review tool is built
Why it's wrong here
Disabling AI features outright blocks the compliance officer's review requirement by removing the content needing review, and stalls adoption through lost capability. It is tempting when governance demands strict control before rollout, yet it suits only environments where AI use is prohibited entirely, not one needing reviewed AI output.
- ✗
Immediately block all external sharing of AI-generated content
Why it's wrong here
Blocking external sharing outright prevents the compliance review step from ever occurring, since content cannot reach the reviewer for approval before release. It is tempting because sharing restrictions genuinely enforce data-loss prevention, and would suit environments where AI output must never leave the tenant at all. Here the requirement is review before sharing, not prohibition.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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