Analyze, Monitor, and Tune AI-powered Business Solutions AB-100 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   A team observes that the average response time of an AI agent has increased significantly. Which telemetry data would be most useful to interpret this change?

   • AModel version number
   • BUser feedback comments
   • CLatency metrics for the agent's responses
   • DNumber of active users
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2. 2expert · hard

   An AI agent that schedules appointments has a high no-show rate. The backlog shows that appointments booked through the agent are more likely to be no-shows than those booked by humans. User feedback indicates that the agent often books the wrong time or location. The team wants to reduce no-shows. What should they do?

   • ARetrain the model on all historical appointment data to improve accuracy.
   • BReduce the number of appointment slots offered by the agent.
   • CAnalyze the backlog and feedback to identify specific booking errors, then tune the agent's confirmation flow to verify details.
   • DIncrease the number of reminders sent to users before appointments.
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4. 3application · medium

   A media company's AI content recommendation engine shows a sudden drop in click-through rate (CTR). Telemetry indicates that the model's feature distribution has shifted significantly in the last 24 hours. What should the team do to address this?

   • AIncrease the frequency of model retraining to daily.
   • BImmediately retrain the model with the latest data without investigating the shift.
   • CRoll back to the previous model version.
   • DInvestigate the feature distribution shift to identify the cause (e.g., a new user segment or content trend) before retraining.
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5. 4expert · hard

   A manufacturing company's AI quality-control agent has started rejecting products that previously passed inspection. Telemetry shows a change in the distribution of sensor readings from the production line. The team suspects a sensor calibration issue, not a model problem. What should they do to confirm the root cause?

   • AAnalyze the telemetry to compare sensor reading distributions before and after the issue started, and check if the sensor calibration changed.
   • BIncrease the model's tolerance for sensor variations.
   • CRoll back the model to the previous version.
   • DRetrain the model with the new sensor data to adapt to the changed distribution.
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6. 5foundation · easy

   A team reviews the backlog of an AI-powered business solution to understand how users interact with it. Which type of backlog item would be most useful for identifying usage patterns?

   • ABug reports from automated testing
   • BSupport tickets and feature requests from users
   • CTechnical debt items from developers
   • DUser stories describing new features
   Reveal Solution Discussion Select an answer first