AI Associate AI Fundamentals Practice Question
A global manufacturing company uses Sales Cloud and has implemented Einstein Opportunity Scoring to prioritize deals. The scoring model was trained on historical data and initially performed well. Over the past month, the scores have become less accurate, with many high-scoring opportunities not closing and some low-scoring ones closing. The admin notices that the sales team has been using a new discounting strategy that heavily influences deal outcomes. The admin wants to improve model performance without manual intervention. Which action should the admin take?
⚠ Common exam trap
Salesforce often tests the misconception that adding a field or cleaning data alone will improve model performance, when in fact the model must be retrained to incorporate the new data and learn the changed relationships.
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
✓
Retrain the Einstein Opportunity Scoring model with the latest opportunity data including discount information.
Retraining the Einstein Opportunity Scoring model with the latest opportunity data, including discount information, allows the machine learning model to automatically learn the new patterns introduced by the sales team's discounting strategy. This aligns with the AI Associate principle that models must be retrained on current data to maintain accuracy when business processes change, without requiring manual intervention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Manually adjust the field weights for discount-related fields in the model.
Why it's wrong here
Manual adjustments are not recommended; retraining is better.
- ✓
Retrain the Einstein Opportunity Scoring model with the latest opportunity data including discount information.
Why this is correct
Retraining incorporates new patterns.
- ✗
Run a data quality report to identify and clean missing discount data.
Why it's wrong here
Data quality is not the root cause.
- ✗
Create a custom field for discount percentage and add it to the model.
Why it's wrong here
Adding a field does not retrain the model.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.