The answer is to verify that the recommendation model is published and active and to check that article view events are being captured. These two checks are the foundational first steps because Einstein Article Recommendations rely entirely on a trained, active model to serve suggestions, and that model depends on a steady stream of user interaction data—specifically article view events—to learn and generate relevant recommendations. If the model is not published or active, no recommendations can be served regardless of data quality, and if event capture is broken, the model has no input to learn from. On the Salesforce AI Associate exam, this question tests your understanding of the core data pipeline for Einstein features, often appearing as a trap where test-takers jump to advanced diagnostics like query tuning or permission checks. A reliable memory tip is to think of the two-part engine: the model must be “on” (active) and the fuel (events) must be flowing.
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 data analyst is troubleshooting Einstein Article Recommendations that are not showing up on the site. Which TWO checks should be performed first? (Choose 2)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Check that article view events are being captured in the data
Option C is correct because Einstein Article Recommendations rely on user interaction data, specifically article view events, to generate personalized recommendations. If these events are not being captured, the model has no input to learn from, and recommendations will not appear. Checking event capture is a fundamental first step in troubleshooting data pipeline issues.
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.
✗
Ensure at least 100 articles are in the knowledge base
Why it's wrong here
No strict minimum; even fewer articles can work if views exist.
✗
Confirm that article authors have the correct profile permissions
Why it's wrong here
Author permissions do not affect recommendation display.
✓
Check that article view events are being captured in the data
Why this is correct
Without view data, the model has no basis to recommend.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the recommendation frequency from daily to hourly
Why it's wrong here
Frequency is not usually the cause of missing recommendations.
✓
Verify that the recommendation model is published and active
Why this is correct
An unpublished model will not serve recommendations.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Salesforce often tests the misconception that increasing data volume or frequency (Options A and D) will fix recommendation issues, when in fact the core problem is usually missing event data or an inactive model.
Detailed technical explanation
How to think about this question
Einstein Article Recommendations use a collaborative filtering model that analyzes user-article interaction events (e.g., View, Click) stored in the Data Platform. The model must be published and active (Option E) to serve predictions via the API; if it is in draft or inactive state, no recommendations are generated. Event capture relies on the Einstein Activities connector, which must be correctly configured to send events from the site to Salesforce's Data Cloud.
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: Check that article view events are being captured in the data — Option C is correct because Einstein Article Recommendations rely on user interaction data, specifically article view events, to generate personalized recommendations. If these events are not being captured, the model has no input to learn from, and recommendations will not appear. Checking event capture is a fundamental first step in troubleshooting data pipeline issues.
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: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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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