- A
Model algorithm type
Why wrong: The algorithm is automatically chosen by Prediction Builder.
- B
Prediction explanation settings
Why wrong: Explanation settings are optional and not required for model creation.
- C
Data set (records to train on)
The dataset defines which records are used for training.
- D
Features (input fields)
Why wrong: Features are optional; the builder automatically selects relevant fields.
- E
Prediction field (the field to predict)
A binary outcome field like 'Converted' must be selected.
Question 991 of 1,000
AI Associate Salesforce Einstein AI Features Practice Question
This AI Associate practice question tests your understanding of salesforce einstein ai features. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
An admin wants to create a custom AI model to predict lead conversion using Einstein Prediction Builder. Which TWO items must they select when creating the model? (Choose two)
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
✓
Data set (records to train on)
Option C is correct because the data set defines the records (e.g., leads, opportunities) that the model will use for training. Without specifying which records to train on, the model has no source of historical data to learn patterns from. Einstein Prediction Builder requires you to select a data set (such as a report or object) to provide the training examples.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model algorithm type
Why it's wrong here
The algorithm is automatically chosen by Prediction Builder.
- ✗
Prediction explanation settings
Why it's wrong here
Explanation settings are optional and not required for model creation.
- ✓
Data set (records to train on)
Why this is correct
The dataset defines which records are used for training.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Features (input fields)
Why it's wrong here
Features are optional; the builder automatically selects relevant fields.
- ✓
Prediction field (the field to predict)
Why this is correct
A binary outcome field like 'Converted' must be selected.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the required selections (data set and prediction field) with optional or automated settings like algorithm type or feature selection, leading them to pick options that are not mandatory.
Detailed technical explanation
How to think about this question
Einstein Prediction Builder uses automated machine learning (AutoML) to train models on the selected data set and prediction field. The system automatically performs feature engineering, algorithm selection (e.g., gradient boosting, logistic regression), and hyperparameter tuning. In a real-world scenario, an admin might choose a data set filtered to the last 12 months of leads to ensure the model learns from recent conversion patterns.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Salesforce Einstein AI Features — study guide chapter
Learn the concepts, then practise the questions
- →
Salesforce Einstein AI Features practice questions
Targeted practice on this topic area only
- →
All AI Associate questions
1,000 questions across all exam domains
- →
Salesforce AI Associate AI Associate study guide
Full concept coverage aligned to exam objectives
- →
AI Associate practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related AI Associate practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Ethical AI and Data Privacy practice questions
Practise AI Associate questions linked to Ethical AI and Data Privacy.
Salesforce Einstein AI Features practice questions
Practise AI Associate questions linked to Salesforce Einstein AI Features.
AI Fundamentals practice questions
Practise AI Associate questions linked to AI Fundamentals.
AI Capabilities in CRM practice questions
Practise AI Associate questions linked to AI Capabilities in CRM.
Ethical Considerations of AI practice questions
Practise AI Associate questions linked to Ethical Considerations of AI.
Data for AI practice questions
Practise AI Associate questions linked to Data for AI.
AI Associate fundamentals practice questions
Practise AI Associate questions linked to AI Associate fundamentals.
AI Associate scenario practice questions
Practise AI Associate questions linked to AI Associate scenario.
AI Associate troubleshooting practice questions
Practise AI Associate questions linked to AI Associate troubleshooting.
Practice this exam
Start a free AI Associate practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this AI Associate question test?
Salesforce Einstein AI Features — This question tests Salesforce Einstein AI Features — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Data set (records to train on) — Option C is correct because the data set defines the records (e.g., leads, opportunities) that the model will use for training. Without specifying which records to train on, the model has no source of historical data to learn patterns from. Einstein Prediction Builder requires you to select a data set (such as a report or object) to provide the training examples.
What should I do if I get this AI Associate question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.