Question 908 of 1,000
Salesforce Einstein AI FeatureseasyMultiple SelectObjective-mapped

AI Associate Salesforce Einstein AI Features Practice Question

This AI Associate practice question tests your understanding of salesforce einstein ai features. 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.

A sales team wants to use Einstein GPT for Sales to generate call summaries. Which two data sources can be used to populate the call summary prompt?

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

Related Opportunity or Account fields

Option C is correct because Einstein GPT for Sales can pull structured data from related Salesforce records, such as Opportunity or Account fields, to populate the call summary prompt with relevant context like deal stage or customer details. This allows the generative AI to produce summaries that are tailored to the specific sales context without requiring external data sources.

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.

  • Case details from Service Cloud

    Why it's wrong here

    Case details are more relevant for service call summaries, not sales calls.

  • Email threads from Einstein Email Insights

    Why it's wrong here

    Email Insights highlights important emails but is not typically used for call summaries.

  • Related Opportunity or Account fields

    Why this is correct

    These provide context such as deal value and contact information.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Call recording transcript from Einstein Conversation Insights

    Why this is correct

    The transcript provides the content of the call.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Einstein Discovery stories

    Why it's wrong here

    Discovery stories provide analytical insights, not call-specific data.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may assume any Salesforce data source is eligible, but Einstein GPT for Sales specifically requires data that is directly relevant to the call context, such as the transcript and related CRM records, excluding service or analytics-only sources.

Detailed technical explanation

How to think about this question

Einstein GPT for Sales uses a retrieval-augmented generation (RAG) architecture where the prompt is dynamically enriched with data from the Salesforce CRM, such as Opportunity fields (e.g., Amount, Stage) and Account fields (e.g., Industry, Type). The call recording transcript from Einstein Conversation Insights is also a key data source because it provides the raw conversation text that the LLM summarizes, ensuring the output is grounded in the actual dialogue. In a real-world scenario, a sales rep might see a summary that includes both the transcript highlights and the current deal value, enabling faster follow-up actions.

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.

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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: Related Opportunity or Account fields — Option C is correct because Einstein GPT for Sales can pull structured data from related Salesforce records, such as Opportunity or Account fields, to populate the call summary prompt with relevant context like deal stage or customer details. This allows the generative AI to produce summaries that are tailored to the specific sales context without requiring external data sources.

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.

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Last reviewed: Jul 4, 2026

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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.