AI0-001 AI Implementation and Operations Practice Question
Exhibit
Refer to the exhibit. ``` > show model-monitor Model: customer_churn_v2 Status: DEPLOYED Inference: REALTIME Latency (p99): 250ms Error Rate: 0.2% Last Drift Check: 2025-03-15 14:00 UTC Drift Detected: YES ```
Refer to the exhibit. The monitoring dashboard for a deployed churn prediction model shows a drift detected flag. However, the error rate and latency are within acceptable ranges. What is the most appropriate immediate action?
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
✓
Investigate the type and severity of drift before deciding
When drift is detected but performance metrics like error rate and latency are still acceptable, it is important to investigate the type and severity of drift before taking any action. Drift may be benign or may indicate a shift that will eventually degrade performance. Option A is wrong because automatic retraining could be risky if the drift is temporary or benign. Option B is wrong because rolling back immediately discards potential improvements and could be unnecessary. Option C is wrong because ignoring drift may lead to future degradation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Trigger automatic retraining using the latest data
Why it's wrong here
Retraining immediately acts on a drift flag without first diagnosing whether drift affects predictions; error and latency being stable means no confirmed degradation, so retraining risks replacing a working model. It is tempting because retraining is the standard remedy once drift is shown to harm accuracy.
- ✗
Roll back to the previous model version immediately
Why it's wrong here
Rolling back discards a model whose error rate and latency remain acceptable, and the previous version faces the same drifted data. It is tempting because rollback is the correct response when a deployment itself causes failures, not when input distribution shifts while outputs stay sound.
- ✗
Ignore the drift since performance metrics are stable
Why it's wrong here
Ignoring drift leaves the underlying cause unexamined; stable error and latency may simply lag, and drift can later degrade predictions. It is tempting because no immediate harm is visible, and ignoring would be defensible only if investigation confirmed the drift was benign and monitored.
- ✓
Investigate the type and severity of drift before deciding
Why this is correct
A drift flag alone does not indicate degraded performance, since error rate and latency remain acceptable. Investigating the drift's type and severity first establishes whether it is genuine, benign, or requires retraining, avoiding unnecessary remediation that could destabilise a currently healthy model.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.