Quick Answer
The answer is Einstein Lead Scoring and Einstein Opportunity Scoring. These two features are core Einstein AI capabilities in Sales Cloud because they apply predictive models to historical data, automatically assigning a numeric score to leads and opportunities based on their likelihood to convert. For leads, the model analyzes attributes like source and engagement; for opportunities, it evaluates deal size, stage duration, and past win patterns—both enabling sales reps to prioritize high-value records. On the Salesforce AI Associate exam, this question tests your understanding of which Sales Cloud AI tools are native to Einstein, not third-party add-ons. A common trap is confusing Einstein Activity Capture or Einstein Automated Contacts with scoring features; remember that scoring is always about prediction, not automation. Memory tip: think “Lead and Opp — the two scoring pops” — if it doesn’t have “score” in the name, it’s not the core scoring capability tested here.
This AI Associate practice question tests your understanding of ai capabilities in crm. 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.
Which TWO features are part of Einstein AI capabilities in Salesforce Sales Cloud?
Einstein Opportunity Scoring
Part of Sales Cloud Einstein.
Einstein Case Classification
Why wrong: Service Cloud feature.
Einstein Lead Scoring
Part of Sales Cloud Einstein.
Einstein Bots
Why wrong: Service Cloud feature.
Einstein Article Recommendations
Why wrong: Service Cloud feature.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Einstein Opportunity Scoring
Einstein Opportunity Scoring is a core Einstein AI capability in Sales Cloud that uses predictive models to analyze historical data and assign a score to each opportunity, indicating its likelihood to close. This helps sales reps prioritize their efforts on deals most likely to convert, directly leveraging AI to enhance sales productivity.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Einstein Opportunity Scoring
Why this is correct
Part of Sales Cloud Einstein.
Related concept
Read the scenario before looking for a memorised answer.
Einstein Case Classification
Why it's wrong here
Service Cloud feature.
Einstein Lead Scoring
Why this is correct
Part of Sales Cloud Einstein.
Related concept
Read the scenario before looking for a memorised answer.
Einstein Bots
Why it's wrong here
Service Cloud feature.
Einstein Article Recommendations
Why it's wrong here
Service Cloud feature.
Common exam traps
Salesforce often tests the distinction between Sales Cloud and Service Cloud Einstein features, so the trap here is assuming that all Einstein AI capabilities are available across all clouds, when in fact features like Case Classification and Article Recommendations are exclusive to Service Cloud.
Detailed technical explanation
Einstein Opportunity Scoring uses a gradient-boosted machine learning model trained on your org's historical opportunity data, including fields like amount, stage, and lead source, to generate a score from 1 to 99. The model is automatically retrained every 24 hours to adapt to changing patterns, and the score is displayed directly on the opportunity record and in list views, enabling real-time prioritization. In a real-world scenario, a sales rep might filter opportunities by scores above 80 to focus on high-probability deals, reducing time spent on low-likelihood opportunities.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
AI Capabilities in CRM — This question tests AI Capabilities in CRM — Read the scenario before looking for a memorised answer..
The correct answer is: Einstein Opportunity Scoring — Einstein Opportunity Scoring is a core Einstein AI capability in Sales Cloud that uses predictive models to analyze historical data and assign a score to each opportunity, indicating its likelihood to close. This helps sales reps prioritize their efforts on deals most likely to convert, directly leveraging AI to enhance sales productivity.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 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.
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