AI Associate AI Capabilities in CRM Practice Question
This AI Associate practice question tests your understanding of ai capabilities in crm. 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 notices that Einstein Account Scoring is not generating scores for all accounts. Some accounts have no score even though they meet the data requirements. What is the most likely cause?
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 org has fewer than 100 account records
Einstein Account Scoring requires a minimum of 100 account records to generate meaningful scores. If the org has fewer than 100 accounts, the model cannot establish a baseline for scoring, resulting in no scores for any account. This is a hard threshold enforced by the Einstein AI engine, not a configurable setting.
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 org has fewer than 100 account records
Why this is correct
Einstein requires a minimum data volume (e.g., 100 records) to generate scores.
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.
✗
Einstein features are not enabled in the org
Why it's wrong here
Einstein is enabled by default for Professional and Enterprise editions with Sales Cloud.
✗
Users do not have the 'View Scores' permission
Why it's wrong here
Permission affects visibility, not score generation.
✗
The accounts lack custom fields for scoring
Why it's wrong here
Scoring uses standard and custom fields; lack of custom fields doesn't prevent scoring.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume missing scores are due to permission issues or missing custom fields, but the real constraint is a hard data volume minimum that the Einstein engine enforces silently.
Detailed technical explanation
How to think about this question
Einstein Account Scoring uses a predictive model trained on historical account data. The 100-record minimum ensures statistical significance for the model's regression analysis. Below this threshold, the model cannot compute reliable propensity scores, so it returns null. This is similar to the minimum data requirements for Einstein Lead Scoring and other predictive models in Salesforce.
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.
AI Capabilities in CRM — This question tests AI Capabilities in CRM — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The org has fewer than 100 account records — Einstein Account Scoring requires a minimum of 100 account records to generate meaningful scores. If the org has fewer than 100 accounts, the model cannot establish a baseline for scoring, resulting in no scores for any account. This is a hard threshold enforced by the Einstein AI engine, not a configurable setting.
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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