AI Associate Salesforce Einstein AI Features Practice Question
A company wants to use AI to automatically assign a priority (High, Medium, Low) to incoming cases based on the case description and account history. Which feature should they configure?
⚠ Common exam trap
A common mix-up: candidates confuse Einstein Prediction Builder (which requires custom model creation) with Einstein Case Classification (which is a pre-built, purpose-built solution for case categorization), leading them to choose Option C despite the extra effort required.
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
✓
Einstein Case Classification
Einstein Case Classification is specifically designed to automatically assign categories or priorities (like High, Medium, Low) to incoming cases based on case descriptions and account history, using a pre-built AI model that learns from historical case data. This feature directly addresses the requirement without needing custom model training or flow configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Einstein Discovery with a recipe
Why it's wrong here
Discovery analyzes data but does not auto-classify cases.
- ✗
Einstein Next Best Action with a flow
Why it's wrong here
Next Best Action recommends actions, not classification.
- ✗
Einstein Prediction Builder with a three-class model
Why it's wrong here
Prediction Builder only supports binary classification, not three classes.
- ✓
Einstein Case Classification
Why this is correct
Case Classification is designed to auto-populate case fields like Priority.
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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.