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Generative AI Leader Using Vertex AI to generate report summaries Practice Question
A company is using Vertex AI to generate report summaries. They want to measure ROI. Which three metrics should they track? (Choose THREE)
⚠ Common exam trap
A common mix-up: candidates confuse adoption metrics (active users, training count) with ROI metrics, but ROI for Vertex AI requires direct financial or efficiency quantification, not just usage statistics.
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
✓
Error rate (e.g., factual errors in summaries)
Error rate directly measures the quality and reliability of generated summaries, which is a key factor in determining ROI. If summaries contain factual errors, they require human correction, reducing the time savings and potentially introducing business risks. Tracking error rate helps quantify the cost of inaccuracies against the benefits of automation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Error rate (e.g., factual errors in summaries)
Why this is correct
Reducing errors improves trust and saves correction time.
- ✗
Number of employees trained on the system
Why it's wrong here
Training count does not measure business value.
- ✗
Number of active users per month
Why it's wrong here
Active users indicate adoption but not direct ROI.
- ✓
Accuracy score of generated summaries compared to human-written ones
Why this is correct
Quality improvement is essential for ROI justification.
- ✓
Time saved per report (minutes)
Why this is correct
Reduction in manual effort is a key productivity metric.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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