AI Associate Practice Test 28 — 15 Questions

Question 1

A company is implementing Einstein Activity Capture. Users have enabled the feature, but emails are not being automatically logged. Which configuration should the administrator verify first?

Accepted Answer

Confirm that the Einstein Activity Capture permission set is assigned to users.. Einstein Activity Capture requires the dedicated permission set to be assigned to users before it can automatically log emails and events. Without this permission set, the feature is enabled at the org level but users lack the necessary access rights to capture activities, so verifying this assignment is the first logical step.

Answer

Check that the users' email clients are supported.

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Verify that Email-to-Salesforce is enabled.

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Ensure users have the 'Log a Task' permission.

Question 2

A global retail company with 50,000+ users has deployed Einstein Activity Capture across Sales and Service Clouds. After two weeks, the VP of Sales reports that only 60% of emails sent from Outlook are being logged in Salesforce. Users have installed the Einstein Activity Capture plugin and have the correct permission set. The admin has verified that the email logging settings are enabled for all users. The company uses Exchange Online. What should the admin investigate first?

Accepted Answer

Confirm that the Salesforce connected app is authorized in Exchange Online.. Einstein Activity Capture for Exchange Online requires an OAuth 2.0 connected app authorization in Exchange Online to access mailbox data. Even if the plugin is installed and permissions are set, without the connected app being authorized, the service cannot retrieve email metadata, causing a significant logging gap. This is the first thing to verify since it is a common misconfiguration during initial setup.

Answer

Review the Exchange Online mailbox audit logs to see if emails are being accessed.

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Check the email synchronization frequency in the Einstein Activity Capture settings.

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Ensure that all users have the 'Email Integration' permission enabled in their profiles.

Question 3

A retail company wants to display personalized product recommendations on their Experience Cloud site based on customer browsing behavior. Which Einstein feature should they implement?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is the correct choice because it is specifically designed to deliver personalized product recommendations on Experience Cloud sites by analyzing customer browsing behavior, purchase history, and other engagement signals. It uses AI to surface the most relevant products in real time, directly matching the requirement for personalized product recommendations based on browsing behavior.

Answer

Einstein Next Best Action

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Einstein Prediction Builder

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Einstein Article Recommendations

Question 4

A customer support team wants to automatically categorize incoming cases into predefined categories such as Billing, Technical, or Account. Which NLP task is most appropriate?

Accepted Answer

Text classification. Text classification assigns predefined labels to text, making it the right choice for categorizing support cases.

Answer

Intent detection

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Entity extraction

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Sentiment analysis

Question 5

An admin wants to automatically log emails and events from Outlook or Gmail to Salesforce without manual user action. Which feature should they enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (C) is the correct feature because it automatically logs emails and events from Outlook or Gmail into Salesforce without requiring manual user action. It uses a background synchronization process that captures activities based on configured rules, eliminating the need for plugins or add-ins.

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Einstein Conversation Insights

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Einstein Bots

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Einstein Email Insights

Question 6

A company wants to train an AI model to predict customer churn using historical data that contains many missing values. What is the best practice for handling missing data?

Accepted Answer

Impute missing values using mean or median.. Imputing missing values using mean or median is a standard practice that preserves the dataset size and statistical properties, allowing the AI model to learn from all available features without introducing bias from data removal. This approach is particularly effective for numerical features in customer churn prediction, where missing values are often random and imputation maintains the distribution for algorithms like logistic regression or gradient boosting.

Answer

Use only features without missing values.

Answer

Ignore missing values as they do not affect AI training.

Answer

Remove all records with missing values.

Question 7

A financial services company is deploying Einstein Prediction Builder to predict customer churn. The data includes both numerical and categorical fields. Which step is essential to ensure the model is not biased against protected attributes like race or gender?

Accepted Answer

Exclude any protected attributes from the training data and ensure the model does not use correlated proxies.. Excluding protected attributes like race or gender from the training data and ensuring the model does not use correlated proxies is essential to prevent bias in Einstein Prediction Builder. This approach directly removes the risk of the model learning discriminatory patterns based on these attributes, as the platform relies on the data provided and does not automatically enforce fairness constraints. Including such attributes or relying on built-in fairness would not guarantee unbiased predictions because the model could still infer protected characteristics from correlated features.

Answer

Include race and gender as predictors to allow the model to adjust for them.

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Rely on the model's built-in fairness constraints.

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Use a deep learning algorithm to automatically handle bias correction.

Question 8

A company receives a complaint that their Einstein Next Best Action recommendations are consistently suggesting different products based on the customer's ZIP code, leading to unequal access. What should the company do first?

Accepted Answer

Review the training data for geographic bias.. The first step in addressing biased AI recommendations is to investigate the root cause. Geographic bias in training data is a common source of unequal outcomes in machine learning models like Einstein Next Best Action. Reviewing the data allows the company to identify and mitigate the bias before taking any other action.

Answer

Contact Salesforce support for a refund.

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Increase the number of recommendations shown.

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Disable the recommendation engine immediately.

Question 9

A support manager wants to automatically classify incoming cases into the correct Type and Priority fields based on the case description. Which Einstein feature should be configured?

Accepted Answer

Einstein Case Classification. Einstein Case Classification is the correct feature because it uses machine learning to automatically predict the Type and Priority fields for incoming cases based on the text in the case description. This directly matches the requirement to classify cases without manual intervention, leveraging pre-trained or custom models within Salesforce.

Answer

Einstein Article Recommendations

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Einstein Next Best Action

Answer

Einstein Discovery

Question 10

Refer to the exhibit. A Salesforce CLI output shows the status of Einstein models in the org. Which model should the administrator investigate first?

Accepted Answer

Case_Escalation because it has an Error status.. An Einstein model with an 'Error' status indicates a critical failure that prevents the model from generating predictions or scoring records. This requires immediate investigation to restore functionality, as the model is non-operational and may impact business processes relying on its output.

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Lead_Score_Model because its accuracy is lower than expected.

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Campaign_Response because it has the oldest training date.

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Opportunity_Forecast because it is still training.

Question 11

A sales representative uses Einstein Activity Capture to log emails automatically. However, some critical emails are not being captured. What is the most likely reason?

Accepted Answer

The sender or recipient is not a Salesforce user with a license.. Einstein Activity Capture relies on Salesforce user licenses to associate email activities with records. If the sender or recipient is not a licensed Salesforce user, the system cannot link the email to a user identity, causing it to be skipped during capture. This is the most common reason for missing emails because the feature is designed to log activities only for licensed users.

Answer

The emails were sent from a non-Outlook or Gmail client.

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The Einstein Activity Capture feature is disabled for that specific user.

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The emails contain attachments that exceed the size limit.

Question 12

A data scientist is building a predictive model for customer churn using Salesforce data. The dataset has 20 features, and the target variable is highly imbalanced (5% churn, 95% non-churn). Which technique should be applied to handle the class imbalance before training?

Accepted Answer

Use Synthetic Minority Over-sampling Technique (SMOTE). SMOTE (Synthetic Minority Over-sampling Technique) is the correct choice because it generates synthetic samples for the minority class (churn) by interpolating between existing minority instances, effectively balancing the dataset without simply duplicating data. This prevents the model from being biased toward the majority class (non-churn) and improves recall for the churn class, which is critical in imbalanced classification problems.

Answer

Apply Principal Component Analysis (PCA) for dimensionality reduction

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Create interaction features between existing variables

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Use accuracy as the evaluation metric

Question 13

A sales team uses Einstein Email Insights to identify important emails. Which TWO email characteristics are likely to be flagged as important?

Accepted Answer

Emails with negative sentiment (e.g., complaints). Einstein Email Insights uses natural language processing (NLP) and machine learning models to analyze email content and sender relationships. Emails with negative sentiment, such as complaints, are flagged as important because they often indicate urgent issues requiring immediate attention. This is based on sentiment analysis scoring, where negative sentiment correlates with high-priority business impact.

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Emails from external domains

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Emails from contacts with high open rates

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Emails from contacts with recent expired support contracts

Question 14

A sales manager wants to see an AI-generated prediction of how likely each opportunity is to close, alongside the sales rep's own forecast commit. Which feature should they use?

Accepted Answer

Einstein Forecasting. Einstein Forecasting is the correct feature because it directly combines AI-generated predictions (based on historical data and pipeline trends) with the sales rep's own forecast commit, allowing a side-by-side comparison. This enables sales managers to see both the predicted likelihood of closing and the human forecast in one view, which is exactly what the question describes.

Answer

Einstein Discovery

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Einstein Opportunity Scoring

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Einstein Prediction Builder

Question 15

A sales manager is reviewing the AI predictions from Einstein Opportunity Scoring. Which THREE actions should the manager take to ensure ethical use of AI according to Salesforce Trusted AI principles?

Accepted Answer

Provide sales reps with explanations of the key factors influencing each score.. Accuracy validation, transparency through explanation, and human oversight align with Salesforce's principles.

Answer

Keep the model's logic secret to prevent gaming the system.

Answer

Override the scores without review if they conflict with intuition.