AI Associate Salesforce Einstein AI Features Practice Test 2 — 15 Questions

Question 1

After deploying an Einstein Prediction Builder model, a user sees a new field on the record. What is this field called and what does it contain?

Accepted Answer

Prediction Score field, containing a percentage between 0 and 100. When an Einstein Prediction Builder model is deployed, it automatically creates a Prediction Score field on the record. This field contains a percentage value between 0 and 100 that represents the model's predicted likelihood for the target outcome. The score is the primary output of the model, not a category, confidence level, or text explanation.

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Prediction Category field, containing the predicted category label

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Prediction Confidence field, containing a confidence level of the model

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Prediction Explanation field, containing a text explanation of the prediction

Question 2

A company uses Einstein GPT for Sales to generate email drafts. They want to ensure that the generated content always includes the correct product pricing from a separate system. How should they achieve this?

Accepted Answer

Use Prompt Builder with a Flex Prompt template that includes a flow to retrieve pricing data.. Prompt Builder with a Flex Prompt template allows the inclusion of a flow that can dynamically retrieve product pricing from an external system via Apex or an external data source. This ensures that the generated email drafts always contain accurate, up-to-date pricing without manual intervention, leveraging Einstein GPT's generative AI capabilities with real-time data integration.

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Ask the sales reps to manually copy pricing into each prompt.

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Use Einstein Recommendation Builder to suggest pricing.

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Use Einstein Discovery to generate pricing insights.

Question 3

An admin is training a new Einstein Prediction Builder model to predict whether a support case will be escalated (binary). They have selected the prediction field 'Escalated__c' and the data set of all cases from the past year. Which step is essential to ensure the model can distinguish between escalated and non-escalated cases?

Accepted Answer

Ensure the 'Escalated__c' field has both 'True' and 'False' values in the training data.. Einstein Prediction Builder requires the target prediction field to contain both positive and negative examples (e.g., 'True' and 'False') in the training data. Without both values, the model cannot learn the decision boundary between escalated and non-escalated cases, making binary classification impossible.

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Set the prediction window to the next 30 days.

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Select at least 20 features from the case object.

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Ensure the data set contains at least 500 records.

Question 4

A company wants to use a custom image classification model to automatically identify product defects from photos uploaded by field technicians. Which Salesforce Einstein platform should they use?

Accepted Answer

Einstein Vision and Language Platform. Einstein Vision and Language Platform provides the APIs and tools needed to build custom image classification models. This platform includes the Vision API, which can be trained on labeled images of product defects to automatically classify new photos uploaded by field technicians, making it the appropriate choice for this use case.

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Einstein Prediction Builder

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Einstein Bots

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Einstein GPT

Question 5

A Salesforce admin is building an Agentforce agent to handle customer support interactions. They need to define the topics the agent can handle and the actions it can perform. Which three components must be configured in Agent Builder?

Accepted Answer

Testing in Agent Builder. Testing in Agent Builder (A) is correct because it allows the admin to validate the agent's behavior by simulating conversations before deployment. This ensures that the configured topics and actions respond as expected, which is a critical step in the development lifecycle within Agent Builder.

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Custom Instructions

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AI Model Selection

Question 6

A sales team wants to use Einstein GPT for Sales to generate call summaries. Which two data sources can be used to populate the call summary prompt?

Accepted Answer

Related Opportunity or Account fields. Einstein GPT for Sales can pull structured data from related Salesforce records, such as Opportunity or Account fields, to populate the call summary prompt with relevant context like deal stage or customer details. This allows the generative AI to produce summaries that are tailored to the specific sales context without requiring external data sources.

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Case details from Service Cloud

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Email threads from Einstein Email Insights

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Einstein Discovery stories

Question 7

In Einstein Discovery, which visualization best explains the key drivers behind a business outcome, such as why a metric increased or decreased?

Accepted Answer

Waterfall chart. In Einstein Discovery, the Waterfall chart is specifically designed to decompose the net change in a metric (e.g., increase or decrease) into its contributing factors, showing how individual drivers add or subtract from the total. This makes it the ideal visualization for explaining key drivers behind a business outcome, as it visually breaks down the additive contributions of each predictor variable. Scatter plots, bar charts, and pie charts do not provide this sequential decomposition of change.

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Scatter plot

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Bar chart

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Pie chart

Question 8

A company wants to build a chatbot in Service Cloud that can understand natural language intents like 'check order status' and 'return a product'. Which Einstein feature provides the underlying NLP engine for intent and entity recognition?

Accepted Answer

Einstein Bots. Einstein Bots is the correct answer because it is the Salesforce feature that provides the underlying NLP engine for intent and entity recognition in Service Cloud chatbots. It uses Einstein's natural language processing to interpret user utterances like 'check order status' and map them to configured intents, while also extracting entities such as order numbers or product names to trigger appropriate bot dialog flows.

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Einstein Vision and Language Platform

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Einstein Case Classification

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Einstein Next Best Action

Question 9

A nonprofit organization wants to automatically recommend relevant knowledge articles to service agents while they are working on a case. Which feature should they enable?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations is the correct feature because it specifically uses AI to analyze the context of a service case (such as subject, description, and product) and automatically surfaces relevant knowledge articles to the agent without requiring manual search. This directly matches the requirement of recommending articles while the agent works on a case.

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Einstein Next Best Action

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Einstein Recommendation Builder

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Einstein Case Classification

Question 10

A company wants to build an autonomous AI agent that can handle customer inquiries end-to-end. Which TWO tools are part of Agentforce for building and testing agents?

Accepted Answer

Topics and Actions. Topics and Actions is correct because it is the core mechanism within Agentforce that allows you to define the specific intents (Topics) and the corresponding API calls or logic (Actions) that the agent will use to handle customer inquiries. This enables the agent to understand what the customer wants and execute the appropriate response or backend operation.

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Einstein Bots

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Prompt Builder

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Einstein Copilot

Question 11

Which feature uses automated statistical analysis to identify key drivers in your data and generate natural language stories about the insights?

Accepted Answer

Einstein Discovery. Einstein Discovery is the correct answer because it is the Salesforce feature specifically designed to perform automated statistical analysis (using regression, classification, and clustering algorithms) on your data to identify key drivers and patterns, then automatically generate natural language narratives that explain those insights in plain English. This combines machine learning with automated insight communication, which directly matches the question's description.

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Einstein Prediction Builder

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Einstein Conversation Insights

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Einstein Next Best Action

Question 12

A service manager wants to automatically classify incoming cases into Type, Priority, and Reason fields based on the case description. Which Einstein feature should they configure?

Accepted Answer

Einstein Case Classification. Einstein Case Classification is the correct feature because it is specifically designed to automatically predict and populate standard case fields—such as Type, Priority, and Reason—by analyzing the unstructured text in the case description using natural language processing (NLP) and machine learning models. This eliminates manual data entry and ensures consistent categorization across incoming cases.

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Einstein Recommendation Builder

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Einstein Next Best Action

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Einstein Article Recommendations

Question 13

A company wants to automatically log emails and calendar events from a sales rep's Office 365 account to Salesforce. Which feature should they enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture is the correct feature because it automatically logs emails and calendar events from a sales rep's Office 365 account to Salesforce without requiring manual data entry or complex integrations. It uses a background sync process that captures activities from connected email and calendar systems and maps them to the appropriate Salesforce records, ensuring a seamless flow of communication data into the CRM.

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Einstein Email Insights

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Einstein Discovery

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Einstein Conversation Insights

Question 14

An admin wants to create a prompt template that will be used by sales reps to generate emails in Sales GPT. They need to include dynamic fields from the lead record. Which tool should they use?

Accepted Answer

Prompt Builder. Prompt Builder is the correct tool because it allows admins to create reusable prompt templates that can include dynamic fields from Salesforce records, such as lead data, for use in Sales GPT. This tool is specifically designed for building and managing prompts that integrate with Einstein GPT services to generate personalized email content.

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Einstein Studio

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Einstein Discovery

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Einstein Copilot

Question 15

A company wants to offer personalized product recommendations to customers on their Experience Cloud site. Which Einstein feature should they implement?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is the correct feature because it is specifically designed to deliver personalized product recommendations on Experience Cloud sites by analyzing customer behavior and purchase history. It uses AI to surface the most relevant products to each individual user, directly matching the requirement for personalized recommendations.

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Einstein Prediction Builder

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Einstein Next Best Action

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Einstein Vision and Language Platform