Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions
A company is adopting generative AI for customer support. Which TWO strategies should they implement to manage risks related to brand reputation?
⚠ Common exam trap
Google Cloud often tests the distinction between passive risk communication (like disclaimers) and active risk mitigation (like human-in-the-loop or automated monitoring), trapping candidates who think a disclaimer is sufficient to manage brand reputation risk.
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
✓
Establish a human-in-the-loop escalation process for sensitive interactions.
A human-in-the-loop escalation process ensures that sensitive or ambiguous customer interactions are reviewed by a human agent before an AI-generated response is sent. This directly mitigates brand reputation risk by preventing the AI from inadvertently making offensive, legally problematic, or factually incorrect statements that could go viral. The human reviewer acts as a safety net, catching edge cases that automated filters might miss, such as nuanced sarcasm or cultural insensitivity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Establish a human-in-the-loop escalation process for sensitive interactions.
Why this is correct
Human oversight ensures appropriate handling of sensitive issues.
- ✗
Publish a disclaimer that the AI may make mistakes.
Why it's wrong here
Disclaimers do not prevent reputational damage.
- ✓
Implement automated monitoring for toxic or off-brand language.
Why this is correct
Monitoring helps catch issues before they reach customers.
- ✗
Deploy the model without any content filters to maximize helpfulness.
Why it's wrong here
Unfiltered outputs may contain offensive or harmful content.
- ✗
Disable customer support AI entirely to avoid any risk.
Why it's wrong here
This eliminates benefits of AI.
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Written by Johnson Ajibi, MSc IT Security
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