AI Associate Practice Test 12 — 15 Questions

Question 1

An organization uses Einstein Lead Scoring and notices that leads with a score above 80 are being sent to the sales team too quickly, overwhelming them. The admin wants to adjust when leads are automatically assigned. What should the admin do?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Modify the lead assignment rule to only assign leads with scores above a higher threshold. Einstein Lead Scoring assigns a score (0–100) to each lead based on predictive models. The default assignment rule triggers when a lead's score exceeds a threshold (e.g., 80). To reduce the volume of leads sent to sales, the admin should raise that threshold in the lead assignment rule so only higher-scored leads are automatically assigned. This directly controls the flow without altering the scoring model itself.

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Reduce the number of features used in scoring

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Disable Einstein Lead Scoring and use a custom scoring model

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Create a new lead queue and manually review all leads

Question 2

A sales manager wants to automatically prioritize leads based on their likelihood to convert. Which Einstein feature should be used?

Accepted Answer

Einstein Lead Scoring. Einstein Lead Scoring is the correct feature because it uses predictive models to automatically rank leads based on their likelihood to convert, enabling the sales manager to prioritize follow-up efforts. It analyzes historical lead data and engagement patterns to assign a score, directly addressing the requirement for automated prioritization without manual rules.

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Einstein Prediction Builder

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Einstein Relationship Health

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Einstein Activity Capture

Question 3

A sales manager wants to understand why certain opportunities are predicted to close won while others are not. They need a visual breakdown of the key factors influencing the prediction. Which Einstein feature provides this automatically?

Accepted Answer

Einstein Discovery. Einstein Discovery is the correct feature because it automatically analyzes historical data to identify and visualize the key factors (drivers) that influence prediction outcomes, such as why certain opportunities close won. Unlike scoring features that provide a single score, Einstein Discovery offers a visual breakdown of influential factors, making it ideal for understanding the 'why' behind predictions.

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Einstein Lead Scoring

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Einstein Forecasting

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Einstein Opportunity Scoring

Question 4

A company uses Einstein Conversation Insights to analyze sales call recordings. They want to automatically capture the next steps mentioned in calls. Which feature of Conversation Insights should they configure?

Accepted Answer

Next Step Capture. Next Step Capture, is correct because it is the specific Einstein Conversation Insights feature designed to automatically identify and extract action items or follow-up tasks mentioned during sales calls. This allows the system to surface commitments and next steps without manual note-taking, directly addressing the requirement to capture next steps from call recordings.

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Talk-time Metrics

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Keyword Tracking

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Call Summary

Question 5

A sales team is implementing Einstein Lead Scoring. Which two actions should they take to ensure the model is effective? (Choose 2)

Accepted Answer

Ensure the training data includes both converted and unconverted leads.. Einstein Lead Scoring requires training data that includes both converted and unconverted leads to build a predictive model that can distinguish between leads likely to convert and those that are not. Without unconverted leads, the model cannot learn the negative patterns, leading to biased predictions and poor accuracy.

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Include only demographic data for scoring.

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Set a fixed score threshold for all users.

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Disable the model for low-volume leads.

Question 6

A company uses Salesforce and wants to provide automated chat responses for common customer inquiries. Which Einstein feature should be configured?

Accepted Answer

Einstein Bots. Einstein Bots is the correct feature because it enables automated chat responses for common customer inquiries using natural language processing (NLP) and predefined dialog flows. It integrates directly with Salesforce Chat to handle routine questions without human intervention, reducing response times and agent workload.

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Einstein Sentiment

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Einstein Case Routing

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Einstein Recommender

Question 7

A Salesforce admin wants to automatically classify incoming service cases by Priority (High, Medium, Low) based on case fields like Subject, Description, and Account Type. Which Einstein feature should they use?

Accepted Answer

Einstein Case Classification. Einstein Case Classification is the correct feature because it is specifically designed to automatically classify incoming service cases based on fields like Subject, Description, and Account Type. It uses natural language processing (NLP) and machine learning models trained on historical case data to predict the Priority (High, Medium, Low) without requiring custom code or manual rules.

Answer

Einstein Discovery

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Einstein Prediction Builder

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Einstein Bots

Question 8

A company wants to use Einstein to predict which customers are likely to churn in the next 30 days. Which type of prediction should be created in Einstein Prediction Builder?

Accepted Answer

Binary classification. Einstein Prediction Builder is designed for binary outcomes, such as whether a customer will churn (yes/no) within a specified time frame. A binary classification model predicts one of two possible labels, making it the correct choice for this churn prediction use case.

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Numeric prediction

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Multi-class classification

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Regression

Question 9

Refer to the exhibit. The fairness evaluation shows a disparate impact of 0.85, equal opportunity difference of 0.12, and demographic parity difference of 0.18. Which fairness thresholds are violated?

Accepted Answer

Equal opportunity and demographic parity.. The fairness evaluation shows violations of both equal opportunity and demographic parity thresholds. The equal opportunity difference of 0.12 exceeds the commonly accepted threshold of 0.1, and the demographic parity difference of 0.18 exceeds the typical threshold of 0.1. Disparate impact of 0.85 is within the acceptable range (typically 0.8 to 1.25), so it is not violated.

Answer

Demographic parity only.

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Equal opportunity only.

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Disparate impact only.

Question 10

A social media platform uses an AI model to automatically detect and remove hate speech. The model uses natural language processing and was trained on public posts. Recently, an internal audit reveals that the model removes posts from minority ethnic groups at a rate 3 times higher than from majority groups, even when the content is similar. The model achieves high precision and recall on the test set. The platform's content moderation team is overwhelmed with appeals. The company wants to maintain a safe environment while being fair. Which approach best addresses both goals?

Accepted Answer

Conduct an audit of the training data to identify gaps, then retrain with more representative data including diverse examples of hate speech and non-hate speech.. A comprehensive audit and retraining with diverse data addresses the bias at the root. Option A gives special treatment that could be seen as unfair. Option C removes moderation, risking harmful content. Option D does not solve the underlying bias.

Answer

Disable the AI moderation and rely solely on user reports.

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Add more human moderators to review all flagged content from minority groups.

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Adjust the detection threshold only for minority group posts to reduce flags.

Question 11

An administrator is configuring Einstein Activity Capture and wants to prevent automatic logging of emails sent to a specific external domain (e.g., legal@acme.com) due to confidentiality. How should they achieve this?

Accepted Answer

Add the domain to the Excluded Addresses list in Activity Capture settings.. Einstein Activity Capture includes a built-in 'Excluded Addresses' list within its configuration settings. Adding a domain (e.g., acme.com) to this list prevents any emails sent to or from addresses matching that domain from being automatically logged, which directly addresses the confidentiality requirement without requiring custom code or post-processing.

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Set up a flow to delete the email record after it is logged.

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Use Einstein Email Insights to flag emails from that domain for manual review.

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Create a validation rule on the Email Message object to block logging.

Question 12

A company is using Einstein Discovery to improve customer retention. The data scientist wants to understand the key drivers of churn and receive actionable recommendations. Which THREE capabilities of Einstein Discovery support this goal?

Accepted Answer

Improvement suggestions. Einstein Discovery provides automated statistical analysis to identify key drivers, waterfall charts to show how factors combine to influence outcomes, and improvement suggestions for actions. Stories are an output, but 'story creation' is a feature; 'improvement suggestions' is listed explicitly in the domain; 'operational prescriptions' are similar to improvement suggestions but the term 'improvement suggestions' is more specific to Einstein Discovery. The correct three are: automated statistical analysis (identifies key drivers), waterfall charts (visualize contribution of factors), and improvement suggestions (recommend actions). Story creation is more about narrative summary; operational prescriptions are part of Einstein Discovery but typically refer to prescriptions that can be operationalized; however, improvement suggestions is the standard term.

Answer

Chatbot integration

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Story creation

Question 13

A company wants to use its data from Salesforce to train an Einstein AI model. However, they need to exclude records where the customer has opted out of data use. Which field should they configure in the Data Manager?

Accepted Answer

A checkbox field named Data Use Opt-Out. The Data Manager in Einstein AI uses a standard checkbox field named 'Data Use Opt-Out' to identify records that should be excluded from model training. When this checkbox is true, the system automatically filters out those records during data preparation, ensuring compliance with data privacy requirements.

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The Record Type of the object

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A picklist field on the object

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A formula field that evaluates to true

Question 14

A sales rep wants to generate a personalized email to a prospect using AI. Which Einstein GPT feature should they use?

Accepted Answer

Sales GPT. Sales GPT includes email generation capabilities. It can create personalized email drafts based on CRM data and context.

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Service GPT

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Prompt Builder

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Einstein Copilot

Question 15

A service team wants to automatically suggest relevant knowledge articles to agents while they are working on a case. Which Einstein feature should be enabled?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations uses AI to suggest articles based on case details.

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Einstein Recommendation Builder

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Einstein Case Classification

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Einstein Next Best Action