The answer is that the outcome field has more than two unique values. Einstein Prediction Builder requires a binary outcome field with exactly two distinct values to perform its classification, and the presence of 'In Progress' and 'Closed' alongside other statuses violates this core requirement. This is because the model uses supervised learning on a binary target—if the field contains three or more values, it cannot determine a clear positive or negative outcome, which prevents predictions from being generated. On the Salesforce AI Associate exam, this scenario tests your understanding of the Einstein Prediction Builder binary outcome requirement, often appearing as a troubleshooting trap where admins overlook extra statuses like 'New' or 'Escalated' in the data source. A common memory tip is to think of it as a yes/no gate: if your outcome field can answer more than just "yes" or "no," the model will refuse to open.
AI Associate Data for AI Practice Question
This AI Associate practice question tests your understanding of data for ai. 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.
A Salesforce admin is troubleshooting an Einstein Prediction Builder model that is not generating predictions. The model was created with a custom object 'Feedback__c'. The admin notices that the model's data source includes records with status 'In Progress' and 'Closed'. What is the most likely cause of the model not generating predictions?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The outcome field has more than two unique values
Option C is correct because Einstein Prediction Builder requires the outcome field to have exactly two unique values (binary classification). The presence of 'In Progress' and 'Closed' as statuses suggests the outcome field likely contains more than two values, which violates this requirement and prevents the model from generating predictions.
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.
✗
The data source is not refreshed daily
Why it's wrong here
Data refresh frequency does not prevent model from generating predictions; it affects recency.
✗
The object is a custom object
Why it's wrong here
Custom objects are fully supported by Prediction Builder.
✓
The outcome field has more than two unique values
Why this is correct
Einstein Prediction Builder requires a binary outcome; status with 'In Progress' creates three distinct values.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The object has fewer than 1000 records
Why it's wrong here
Prediction Builder requires at least 100 rows, not 1000.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume any data quality issue (like stale data or record count) is the cause, but the specific requirement for binary outcome fields in Einstein Prediction Builder is a precise constraint that directly blocks prediction generation.
Detailed technical explanation
How to think about this question
Einstein Prediction Builder uses binary classification algorithms that require the outcome field to have exactly two distinct values (e.g., 'Won' vs 'Lost' or 'True' vs 'False'). If the outcome field contains more than two values, the model cannot determine the positive and negative classes, and the prediction pipeline fails. In practice, admins must ensure the outcome field is a picklist or checkbox with only two active values, and any records with other values are excluded from the training dataset.
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.
Data for AI — This question tests Data for AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The outcome field has more than two unique values — Option C is correct because Einstein Prediction Builder requires the outcome field to have exactly two unique values (binary classification). The presence of 'In Progress' and 'Closed' as statuses suggests the outcome field likely contains more than two values, which violates this requirement and prevents the model from generating predictions.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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