AI Associate Practice Test 2 — 10 Questions

Question 1

A sales manager wants to automatically track emails and events from their sales team's Gmail accounts into Salesforce without manual logging. Which Salesforce feature should they enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (B) is the correct feature because it automatically syncs emails and events from Gmail (and Microsoft 365) into Salesforce without requiring manual logging by users. It uses a background synchronization process that captures activities based on configured rules, eliminating the need for manual entry or third-party integrations.

Answer

Einstein Lead Scoring

Answer

Einstein Email Insights

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Einstein Conversation Insights

Question 2

A manufacturing company uses Salesforce Sales Cloud with Einstein Activity Capture to log emails and events automatically. The sales team has noticed that some emails from Microsoft Outlook are not appearing in the Einstein Activity Capture dashboard, even though the users have configured the connection correctly. The administrator checks the activity capture settings and sees that the data source is enabled and users have the correct permissions. The missing emails are from a specific domain, @supplier.com, which is a known vendor. What should the administrator do to ensure these emails are captured?

Accepted Answer

Add the @supplier.com domain to the allowlist in Einstein Activity Capture settings.. Einstein Activity Capture uses allowlists and blocklists to control which emails are captured. By default, emails from external domains may be excluded to reduce noise. Adding @supplier.com to the allowlist ensures that emails from that domain are explicitly included in the capture process, overriding any default filtering.

Answer

Increase the sync frequency for Einstein Activity Capture to every 5 minutes.

Answer

Instruct users to manually log the supplier emails as activities in Salesforce.

Answer

Assign the 'Einstein Activity Capture User' permission set to the supplier's email domain.

Question 3

A company is building a text classification model for customer support tickets. They have a dataset of 10,000 tickets. The team decides to use active learning for labeling. Which approach best aligns with active learning principles?

Accepted Answer

Train a preliminary model and prioritize labeling tickets with low prediction confidence.. Active learning iteratively selects the most informative unlabeled data points for labeling, typically those with low prediction confidence from a preliminary model. This minimizes labeling effort while maximizing model performance, which is the core principle of active learning.

Answer

Randomly select 2,000 tickets and label them manually.

Answer

Use a pre-trained model to label all tickets automatically.

Answer

Have subject matter experts label all 10,000 tickets.

Question 4

A company has international customers and wants Einstein Prediction Builder to forecast deal closure probability. The data includes fields like 'region', 'product line', and 'deal amount'. What is a best practice to ensure the model works for all regions?

Accepted Answer

Group regions into broader categories like 'Americas', 'EMEA', 'APAC'.. Grouping regions into broader categories like 'Americas', 'EMEA', and 'APAC' reduces high cardinality and sparsity in categorical features, which improves model stability and prevents overfitting in Einstein Prediction Builder. This approach ensures each region group has sufficient training data to learn meaningful patterns, enabling the model to generalize better across all regions without introducing bias from rare categories.

Answer

One-hot encode the region field using 50+ dummy variables.

Answer

Remove the region field to avoid bias.

Answer

Use region as a numeric rank based on past conversion rates.

Question 5

Universal Containers (UC) uses Einstein Lead Scoring to prioritize leads. They have 500,000 leads in the system. Recently, the model scores have been inconsistent: some leads with low activity receive high scores, while active leads score low. The model was trained 3 months ago. UC updates lead records daily via an external system, but the data is often incomplete (e.g., missing company size). Support has reported slow performance on lead views. The admin notices that the 'Data Refresh Status' for Einstein Lead Scoring shows 'Pending' for 2 weeks. UC wants to improve model accuracy and performance.

Which action should the admin take first?

Accepted Answer

Schedule a data transform to cleanse and refresh lead data before model training. The 'Data Refresh Status' has been 'Pending' for two weeks, indicating that the model is not receiving updated lead data. Scheduling a data transform to cleanse and refresh lead data before model training directly addresses the root cause: incomplete and stale data (e.g., missing company size) leads to inconsistent scores. This action ensures the model trains on clean, current data, improving both accuracy and performance.

Answer

Increase data retention period for lead records

Answer

Rebuild the Einstein Lead Scoring model using different fields

Answer

Increase the model training frequency to weekly

Question 6

An admin is configuring Einstein Lead Scoring. They want to ensure the lead score is visible in list views and reports. Which TWO settings or actions are required?

Accepted Answer

Add the Lead Score field to the list view layout. The Lead Score field must be added to the list view layout to make it visible in list views and reports. Without adding the field to the layout, users cannot see the score in those contexts, even if scoring is enabled.

Answer

Run a lead scoring batch job manually

Answer

Create a custom report type for Lead Score

Answer

Assign the 'View Lead Score' permission to users

Question 7

Which Salesforce Einstein feature provides automated statistical analysis of data, generates stories in natural language, and offers improvement suggestions in a waterfall chart?

Accepted Answer

Einstein Discovery. Einstein Discovery is the correct answer because it is the Salesforce AI feature specifically designed to perform automated statistical analysis on data, generate natural language narratives (stories) that explain key insights, and provide actionable improvement suggestions visualized in a waterfall chart. Unlike other Einstein features, Discovery focuses on surfacing hidden patterns and recommending specific actions to improve business outcomes.

Answer

Einstein GPT

Answer

Einstein Analytics

Answer

Einstein Prediction Builder

Question 8

A service team uses Einstein Discovery to analyze customer churn. The story shows 'Average Resolution Time' is a key driver. What is the best action?

Accepted Answer

Reduce Average Resolution Time through process changes. Einstein Discovery identifies drivers; reducing resolution time directly addresses root cause. Custom reports just show data, flows send alerts, processes update records but don't reduce time.

Answer

Update account records via process builder

Answer

Configure a flow to send churn alerts

Answer

Create a custom report on churn

Question 9

Which THREE capabilities are provided by Einstein GPT in Sales and Service?

Accepted Answer

Summarizing case conversations from service interactions.. Einstein GPT leverages generative AI to automatically summarize case conversations from service interactions, enabling agents to quickly grasp key details without reading entire transcripts. This capability is built on Salesforce's proprietary AI models that process natural language from service records to produce concise, actionable summaries.

Answer

Generating report charts and dashboards.

Answer

Creating workflow rules based on user behavior.

Question 10

A company wants to use Einstein Bots to handle customer inquiries. They need to train the bot to understand different customer intents. Which TWO components are essential for defining bot understanding?

Accepted Answer

Intents. Intents are essential because they define the purpose or goal of a customer's input, such as 'Check Order Status' or 'Cancel Subscription'. The bot uses intents to classify user messages and determine the appropriate response or action. Without intents, the bot cannot understand what the customer wants, making them a foundational component of natural language understanding (NLU) in Einstein Bots.

Answer

Actions

Answer

Topics

Answer

Dialogue flows