AI Associate Practice Test 31 — 15 Questions

Question 1

A Salesforce admin is training an Einstein Bot to answer customer questions. Which data source should the bot use to provide accurate responses?

Accepted Answer

Knowledge articles with a published status.. Knowledge articles with a published status are the correct data source because they contain curated, approved, and structured information that Einstein Bot can reliably use to generate accurate responses. The bot leverages natural language processing to match customer questions against these articles, ensuring answers are based on verified content rather than unstructured or transient data.

Answer

Chatter posts from the product team.

Answer

Case records from the last 30 days.

Answer

Lead and contact reports.

Question 2

Which TWO of the following are capabilities of Einstein Conversation Insights?

Accepted Answer

Keyword tracking across call recordings. Einstein Conversation Insights includes a keyword tracking feature that allows users to define specific keywords or phrases to be detected across call recordings. This enables the system to surface relevant conversations and trends based on predefined terms, which is a core capability for analyzing customer interactions at scale.

Answer

Lead scoring based on call sentiment

Answer

Real-time transcription during calls

Answer

Automated email generation for follow-ups

Question 3

A company using Einstein Bots wants to improve the bot's ability to understand varied customer expressions (e.g., 'I want a refund', 'money back', 'return my purchase'). Which component should they configure to map these expressions to a common intention?

Accepted Answer

Intents. Intents are the correct component because they define the purpose or goal behind a customer's input. In Einstein Bots, intents are trained to recognize varied phrasings (e.g., 'I want a refund', 'money back', 'return my purchase') and map them to a single, common intention, such as 'Request_Refund'. This allows the bot to understand and route the conversation appropriately without requiring exact keyword matches.

Answer

Entities

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NLP training

Answer

Dialog flows

Question 4

A company uses Einstein Conversation Insights to analyze sales call recordings. They want to automatically capture action items from each call. How can they achieve this?

Accepted Answer

Enable the 'Next Step Capture' feature in Conversation Insights settings. Einstein Conversation Insights includes a built-in 'Next Step Capture' feature that automatically identifies and extracts action items from sales call recordings. This feature uses natural language processing (NLP) to detect commitments, tasks, and follow-ups mentioned during the conversation, eliminating the need for manual transcription review or external integrations.

Answer

Use Einstein Call Summaries in Sales GPT

Answer

Manually create tasks from the call transcript

Answer

Integrate with Einstein Bots to capture steps

Question 5

A company uses Einstein Lead Scoring and notices that leads with a score above 90 are not converting as expected. They suspect the model is overfit to historical patterns. What should they do to improve model performance?

Accepted Answer

Retrain the model by including more recent leads and removing outdated ones. Overfitting occurs when a model learns historical patterns that are no longer relevant. By retraining the model with more recent leads and removing outdated ones, the model can adapt to current conversion behaviors and reduce overfitting, improving predictive performance.

Answer

Increase the score range from 1-99 to 1-100

Answer

Manually adjust lead scores for high-scoring leads

Answer

Add more features to the model to capture more signals

Question 6

A company uses Einstein Discovery to analyze sales data. They want to understand the key drivers of deal closures. Which THREE output types can Einstein Discovery provide? (Choose 3)

Accepted Answer

Stories that explain key factors in natural language. Einstein Discovery generates 'Stories' that automatically describe key factors influencing outcomes in natural language, enabling users to understand drivers of deal closures without manual analysis. These stories are derived from statistical models that identify the most impactful variables in the dataset.

Answer

Sentiment analysis scores

Answer

Custom binary prediction models

Question 7

An organization wants to use Einstein Conversation Insights to analyze sales call recordings. Which THREE pieces of information can Einstein Conversation Insights provide?

Accepted Answer

Next step capture. Einstein Conversation Insights can automatically capture and highlight next steps mentioned during a sales call, such as follow-up actions or commitments. This feature uses natural language processing (NLP) to identify action items and surface them directly in the call summary, enabling sales teams to act on key takeaways without manual note-taking.

Answer

Full transcript generation

Answer

Sentiment analysis of the call

Question 8

A company uses Einstein Recommendation Builder in Experience Cloud to suggest products. They notice that users who frequently purchase from one category are not getting relevant recommendations. What is the most likely cause?

Accepted Answer

There is insufficient interaction data for the product category. Recommendation Builder relies on user interactions (views, purchases) to train models. Lack of interaction data for a category would lead to poor recommendations. The other options are less likely or unrelated.

Answer

The recommendation field is not added to the page layout

Answer

Einstein Vision is required for product image analysis

Answer

The recommendation model was trained on too many records, causing overfitting

Question 9

A company wants to use Einstein Discovery to analyze sales data and automatically uncover key drivers of deal closure. What must the admin provide to create a story?

Accepted Answer

At least one numeric field to predict. Einstein Discovery requires at least one numeric field as the prediction target (e.g., deal amount, probability score) to train its regression or classification model. Without a numeric field to predict, the story cannot define what outcome the AI should analyze or uncover key drivers for.

Answer

A date field for time series analysis

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A foreign key to relate objects

Answer

A text field for sentiment analysis

Question 10

What is the primary purpose of the Einstein Copilot feature in Salesforce?

Accepted Answer

To provide a conversational AI assistant within the CRM. Einstein Copilot is a conversational AI assistant embedded directly in the Salesforce CRM interface. It allows users to ask natural-language questions, get summaries of records, generate field values, and execute actions without navigating menus. This aligns with option D, as its primary purpose is to provide an AI-powered chat experience within the CRM, not to automate logging, analyze calls, or generate marketing campaigns.

Answer

To automatically log emails and events

Answer

To analyze call recordings for talk-time metrics

Answer

To generate marketing email campaigns

Question 11

Refer to the exhibit. A company uses an AI model for loan approvals. The error log shows a drift warning for a specific zip code, followed by a retraining failure due to insufficient data. What is the MOST ethical concern?

Accepted Answer

The model may produce biased outcomes for underserved groups. The drift warning indicates that the model's performance has degraded for a specific zip code, likely due to changes in the underlying data distribution. When retraining fails due to insufficient data, the model cannot adapt to these changes, which can lead to biased outcomes for underserved groups in that zip code. This is the most ethical concern because it directly impacts fairness and equity in automated decision-making.

Answer

The system failed to log the error

Answer

The system ignored the drift warning

Answer

The retraining process is too slow

Question 12

A company wants to use Einstein Conversation Insights to analyze sales call recordings. Which TWO capabilities does this feature provide?

Accepted Answer

Keyword tracking and trend analysis. Einstein Conversation Insights analyzes call recordings for keyword tracking, talk-time metrics (speaker speed, interruptions), and next step capture. It does not provide real-time transcription (it's post-call) or email analysis.

Answer

Automatic email logging

Answer

Real-time transcription of calls

Answer

Sentiment analysis of customer emails

Question 13

A sales admin wants to automatically log emails and events from a sales rep's email client to Salesforce without manual entry. Which feature should they enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (D) is the correct feature because it automatically logs emails and events from a connected email client (like Outlook or Gmail) into Salesforce without requiring manual entry. It uses server-side synchronization to capture interactions based on configured rules, making it the direct solution for this use case.

Answer

Einstein Conversation Insights

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Einstein Lead Scoring

Answer

Einstein Email Insights

Question 14

What is the primary purpose of the Einstein Trust Layer in Salesforce's AI architecture?

Accepted Answer

To provide a secure gateway for AI data processing, including data masking and toxicity detection. The Einstein Trust Layer is designed to provide security, privacy, and governance controls for AI features within the Salesforce platform.

Answer

To replace all third-party AI services with Salesforce-owned models

Answer

To automatically generate AI models without any human oversight

Answer

To train large language models on customer data for better predictions

Question 15

Which TWO of the following are ethical considerations when deploying AI in Salesforce?

Accepted Answer

Providing transparency in AI-generated outcomes. Transparency in AI-generated outcomes is a core ethical principle, especially in Salesforce's Einstein platform, where users must understand how predictions (e.g., lead scoring or opportunity insights) are made. Salesforce provides tools like 'Why This Prediction?' to explain model outputs, ensuring trust and accountability. Without transparency, users cannot validate or challenge AI decisions, leading to potential bias or misuse.

Answer

Maximizing model complexity for better accuracy

Answer

Using only historical data without review for biases