AI Associate Practice Test 49 — 15 Questions

Question 1

A sales manager wants to automatically log emails from a specific customer domain to Salesforce, but exclude internal company emails and spam. Which feature should they configure?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture is the correct feature because it automatically logs emails and events from supported email clients (like Gmail and Outlook) into Salesforce, with configurable rules to include or exclude specific domains. This allows the sales manager to set a rule to log emails from the customer domain while excluding internal company emails and spam, without requiring manual user action or complex automation.

Answer

Einstein Email Insights

Answer

Einstein Lead Scoring

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Einstein Conversation Insights

Question 2

Refer to the exhibit. What effect does this masking policy have on the data used for training an Einstein model?

Accepted Answer

SSN and CreditCard fields are partially masked, showing only the last four characters.. The masking policy in Einstein applies a partial mask to sensitive fields like SSN and CreditCard, showing only the last four characters while obscuring the rest. This ensures that the data used for training retains its structural utility for model learning without exposing full sensitive values, which is why option D is correct.

Answer

Only SSN is masked.

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SSN and CreditCard fields are encrypted.

Answer

SSN and CreditCard fields are completely removed from training data.

Question 3

A marketing manager wants to recommend products to visitors on a community site based on their browsing behavior. Which Salesforce feature is designed for this use case?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is the correct feature because it is specifically designed to generate personalized product or content recommendations based on user behavior, such as browsing history and past interactions on a community site. It uses collaborative filtering and deep learning models to surface relevant items, matching the marketing manager's goal of recommending products to visitors.

Answer

Einstein Prediction Builder

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Einstein Next Best Action

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Einstein Article Recommendations

Question 4

A support manager wants to automatically suggest relevant knowledge articles when agents open a case. Which Einstein feature should they enable?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations automatically suggests relevant knowledge articles to agents based on the case details, helping resolve cases faster.

Answer

Einstein Recommendation Builder

Answer

Einstein Next Best Action

Answer

Einstein Case Classification

Question 5

A system administrator receives an error when running a Data Cloud data transform: 'Row-level security settings are preventing access to the source data.' The admin has appropriate permissions. What is the most likely cause?

Accepted Answer

The source object has sharing rules that restrict access for the data transform's running user.. Data Cloud data transforms run under a specific running user context, and row-level security (RLS) settings on the source object can restrict that user's access to rows, even if the admin has broad permissions. The error indicates that the running user lacks visibility to certain source data rows due to sharing rules or RLS policies, which is a common cause of this specific error message.

Answer

The target object has field-level security.

Answer

The data stream is scheduled during maintenance.

Answer

The data transform is set to run as the admin's default user.

Question 6

An admin is training an Einstein Prediction Builder model for binary classification (lead conversion). The model performance is poor. Which THREE actions should the admin take to improve it?

Accepted Answer

Increase the number of records in the training dataset. Increasing the number of records in the training dataset provides more examples for the model to learn patterns from, which is critical for binary classification tasks like lead conversion. In Einstein Prediction Builder, a larger dataset helps reduce variance and improves the model's ability to generalize, especially when the initial performance is poor due to insufficient data.

Answer

Use fewer records to avoid overfitting

Answer

Add more features, even if they are not related

Question 7

A sales operations manager wants to improve the accuracy of Einstein Opportunity Scoring. Which TWO actions should they take? (Choose two.)

Accepted Answer

Ensure that historical opportunity data includes both won and lost records. Einstein Opportunity Scoring is a predictive model that learns from historical opportunity data to identify patterns that lead to wins or losses. Including both won and lost records ensures the model has a balanced training set, which is essential for accurately distinguishing between likely wins and losses. Without lost records, the model would be biased and unable to effectively predict negative outcomes.

Answer

Use Einstein Discovery to analyze the same data

Answer

Increase the number of records by duplicating existing opportunities

Answer

Manually override scores for high-value opportunities

Question 8

A data scientist is training a model to predict customer churn. To ensure fairness, what should the data scientist do?

Accepted Answer

Ensure the training data is representative of the entire customer base.. Ensuring the training data is representative of the entire customer base directly addresses fairness by preventing underrepresentation or overrepresentation of specific demographic groups. A representative dataset helps the model learn unbiased patterns across all segments, reducing the risk of disparate impact. This aligns with the principle of fairness in AI, where the model's predictions should not systematically disadvantage any group.

Answer

Focus solely on model accuracy ignoring demographic groups.

Answer

Remove all demographic attributes from the dataset.

Answer

Use only historical data without checking for bias.

Question 9

A Salesforce admin wants to create a prompt template that generates a custom field value for a record based on other field values. Which Prompt Builder template type should they use?

Accepted Answer

Field Generation. Field Generation is the correct Prompt Builder template type because it is specifically designed to automatically populate a custom field on a record by generating a value based on other field values within the same record. This template uses a Large Language Model (LLM) to analyze the provided field data and produce a deterministic output that is written directly to the field, fulfilling the admin's requirement.

Answer

Flex Prompt

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Case Summary

Answer

Sales Email

Question 10

A legal firm wants to automate contract clause generation using AI with preapproved language. Which approach should they use?

Accepted Answer

Einstein GPT with Clause Library. Einstein GPT with Clause Library is specifically designed to generate contract clauses using preapproved language. It leverages generative AI combined with a library of approved legal clauses, ensuring compliance and consistency while automating clause creation within Salesforce.

Answer

Email Templates

Answer

Flow

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Document Templates

Question 11

A sales rep wants to automatically generate a personalized email draft to a lead based on recent account activity. Which Einstein feature should be used?

Accepted Answer

Einstein GPT - Sales GPT. Sales GPT, part of Einstein GPT, is specifically designed to generate personalized email drafts using natural language generation (NLG) based on CRM data such as recent account activity. It leverages generative AI to create context-aware content, unlike other Einstein features that focus on prediction, scoring, or data capture.

Answer

Einstein Activity Capture

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Einstein Recommendation Builder

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Einstein Opportunity Scoring

Question 12

A developer creates a custom AI model using Salesforce's AI platform. They want to ensure the model is fair. What should they do first?

Accepted Answer

Collect diverse training data. Collecting diverse training data is the foundational step to ensure fairness in an AI model because it helps mitigate bias at the source. Without diverse data representing all relevant groups, the model may learn skewed patterns that lead to discriminatory outcomes, regardless of subsequent testing or monitoring.

Answer

Use a pre-trained model

Answer

Test on a small sample

Answer

Deploy and monitor

Question 13

A company wants to use Einstein to forecast sales beyond simple manager rollups, comparing AI predictions with rep commitments. Which feature should they enable?

Accepted Answer

Einstein Forecasting. Einstein Forecasting is the correct feature because it is specifically designed to generate AI-driven sales forecasts by analyzing historical data, pipeline trends, and external factors, then comparing those predictions against rep commitments. Unlike simple manager rollups, it provides a statistical baseline that helps identify gaps between AI predictions and human estimates, enabling more accurate revenue planning.

Answer

Einstein Discovery

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Einstein Prediction Builder

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Einstein Opportunity Scoring

Question 14

A sales operations manager wants to automatically prioritize leads based on their likelihood to convert. Which Einstein feature should they use to achieve this?

Accepted Answer

Einstein Lead Scoring. Einstein Lead Scoring is specifically designed to automatically prioritize leads based on their likelihood to convert. It uses a predictive model that analyzes historical lead data and assigns a score (0–100) to each lead, enabling sales teams to focus on high-conversion leads without manual effort.

Answer

Einstein Prediction Builder

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Einstein Discovery

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Einstein Opportunity Scoring

Question 15

A sales rep wants to automatically generate a personalized email to a lead based on their recent activity. Which Einstein GPT feature should the rep use?

Accepted Answer

Sales GPT. Sales GPT is the correct feature because it is specifically designed for sales use cases, such as generating personalized emails to leads based on their recent activity. It leverages Einstein GPT to create tailored sales communications, unlike Service GPT which focuses on service interactions.

Answer

Service GPT

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Prompt Builder

Answer

Einstein Copilot