- A
Run Einstein Discovery to validate the model
Why wrong: Discovery is separate; Prediction Builder has its own validation.
- B
Select features (input fields) for the model
Required: choose relevant fields like case origin, priority, etc.
- C
Select the prediction field (binary classification)
Required: choose which field to predict, e.g., 'Escalated' (True/False).
- D
Configure Einstein Copilot to trigger the prediction
Why wrong: Copilot is a separate feature; not part of Prediction Builder creation.
- E
Select the object and records to train on
Required: define the dataset (e.g., all cases from last 6 months).
Question 944 of 1,000
Required Steps for Setting Up Einstein Prediction Builder
This AI Associate practice question tests your understanding of salesforce einstein ai features. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 is using Einstein Prediction Builder to create a model predicting whether a support case will be escalated. Which THREE steps are required during the prediction creation process?
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
✓
Select features (input fields) for the model
Option B is correct because selecting features (input fields) is a fundamental step in building a prediction model with Einstein Prediction Builder. These features are the independent variables that the model uses to learn patterns and make predictions about the target field (e.g., case escalation). Without selecting relevant features, the model cannot be trained effectively.
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.
- ✗
Run Einstein Discovery to validate the model
Why it's wrong here
Discovery is separate; Prediction Builder has its own validation.
- ✓
Select features (input fields) for the model
Why this is correct
Required: choose relevant fields like case origin, priority, etc.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Select the prediction field (binary classification)
Why this is correct
Required: choose which field to predict, e.g., 'Escalated' (True/False).
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure Einstein Copilot to trigger the prediction
Why it's wrong here
Copilot is a separate feature; not part of Prediction Builder creation.
- ✓
Select the object and records to train on
Why this is correct
Required: define the dataset (e.g., all cases from last 6 months).
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 model creation steps with post-deployment integration tools like Einstein Copilot or Einstein Discovery, leading them to select options that are not part of the actual prediction creation wizard.
Detailed technical explanation
How to think about this question
Einstein Prediction Builder uses automated machine learning (AutoML) to train binary classification models on Salesforce data. During feature selection, the builder automatically evaluates each field's predictive power using techniques like correlation analysis and feature importance scoring, and it can handle up to 500 fields. A real-world scenario is predicting case escalation: features like case priority, product type, and customer history are selected, and the model outputs a probability score (0-1) that can be used in a flow to trigger an alert.
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: Select features (input fields) for the model — Option B is correct because selecting features (input fields) is a fundamental step in building a prediction model with Einstein Prediction Builder. These features are the independent variables that the model uses to learn patterns and make predictions about the target field (e.g., case escalation). Without selecting relevant features, the model cannot be trained effectively.
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 →
Same concept, more angles
3 more ways this is tested on AI Associate
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. An admin is building a custom AI prediction with Einstein Prediction Builder for a binary classification problem. Which THREE steps are required in the configuration? (Choose 3)
hard- A.Define a custom Apex class for data transformation
- ✓ B.Select a prediction field (the field to predict)
- ✓ C.Select the data set (records used for training)
- ✓ D.Select features (input fields for the model)
- E.Configure a trigger to retrain the model daily
Why B: The required steps are: select prediction field, select data set, and select features. Apex and triggers are not needed.
Variation 2. An admin is configuring Einstein Prediction Builder to predict case escalation. Which TWO components must be selected during setup?
hard- A.Prediction explanation template
- ✓ B.Prediction field (binary classification target)
- ✓ C.Features (input fields)
- D.Data set (records to train on)
- E.Prediction score field name
Why B: Option B is correct because Einstein Prediction Builder requires a binary classification target field to define the outcome being predicted—in this case, whether a case will escalate. This field must have exactly two distinct values (e.g., 'Yes'/'No' or 0/1) to train the model. Without specifying the prediction field, the builder cannot determine what event to forecast.
Variation 3. An admin is setting up Einstein Prediction Builder to predict whether a lead will convert. The admin has selected the prediction field and data set. What is the next step in the configuration wizard?
hard- A.Train the model immediately
- B.Define the prediction explanation
- C.Choose the prediction score field
- ✓ D.Select features (input fields) to train the model
Why D: The Einstein Prediction Builder wizard proceeds: select prediction field, select data set, select features, define prediction field, then train.
Keep practising
More AI Associate practice questions
- An admin wants to compare the AI-generated forecast with a rep's commit forecast to identify gaps. Which feature should…
- A Salesforce admin implements Einstein Bots for customer service. To ensure the bot does not use biased language, what s…
- Which Einstein feature provides automated statistical analysis of Salesforce data, including story creation and improvem…
- A sales operations team wants to improve forecast accuracy by using AI. They currently use manual rollups. Which TWO Ein…
- A sales rep wants to generate a personalized email to a prospect using AI. Which Einstein GPT feature should they use?
- A healthcare company uses Einstein Prediction Builder to predict patient no-shows. After training a model, they receive…
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.