AI Associate Salesforce Einstein AI Features Practice Test 20 — 15 Questions

Question 1

A call center manager wants to analyze recorded sales calls to identify keywords, measure talk-time, and capture follow-up tasks. Which Einstein feature provides these capabilities?

Accepted Answer

Einstein Conversation Insights. Einstein Conversation Insights is the correct answer because it is specifically designed to analyze recorded sales calls by transcribing conversations, identifying keywords and topics, measuring talk-time, and capturing follow-up tasks. It uses natural language processing (NLP) to extract actionable insights from voice and text interactions, directly matching the requirements in the question.

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Einstein Discovery

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Einstein Activity Capture

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Einstein Email Insights

Question 2

A company wants to use generative AI to automatically draft case summaries and knowledge article drafts from case details. Which Einstein GPT feature should they enable?

Accepted Answer

Service GPT. Service GPT is the correct Einstein GPT feature because it is specifically designed for service use cases, such as automatically drafting case summaries and knowledge article drafts from case details. It leverages generative AI to analyze case data and produce structured, relevant content tailored to service workflows, unlike other Einstein GPT features that focus on sales or general assistance.

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Agentforce

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Einstein Copilot

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Sales GPT

Question 3

A marketing team wants to identify which leads are most likely to convert, based on historical lead data. They need a score from 1-99 visible on lead records. Which feature should they implement?

Accepted Answer

Einstein Lead Scoring. Einstein Lead Scoring is the correct feature because it is specifically designed to assign a score from 1 to 99 to leads based on historical conversion data and predictive models. This score is automatically calculated and displayed on lead records, enabling the marketing team to prioritize leads most likely to convert.

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Einstein Prediction Builder

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Einstein Opportunity Scoring

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Einstein Discovery

Question 4

A sales operations manager wants to use Einstein Forecasting to improve forecast accuracy. Which TWO capabilities does Einstein Forecasting provide beyond traditional manager rollups? (Select two.)

Accepted Answer

Comparison of AI forecast to the rep's commit amount. Einstein Forecasting provides a direct comparison between the AI-generated forecast and the sales rep's manually entered commit amount. This allows managers to see where human judgment and AI predictions diverge, enabling data-driven coaching and more accurate forecasting. Traditional manager rollups only aggregate rep commits without this AI-based validation layer.

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Automated opportunity scoring for each deal

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Generation of call scripts for sales reps

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Automatic adjustment of quota targets based on AI predictions

Question 5

A company building an Einstein Bot for customer support wants to ensure that when the bot cannot resolve an issue, the conversation is seamlessly transferred to a human agent. Which THREE steps are required to enable this handoff? (Select three.)

Accepted Answer

Assign the bot to a Service Cloud user who can accept chat transfers. Assigning the bot to a Service Cloud user who can accept chat transfers is correct because the Einstein Bot must be linked to a Service Cloud user with the appropriate permissions and presence status to receive and handle transferred conversations. This ensures the user is available in the Omni-Channel routing system and can accept the chat when the bot escalates.

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Create a custom field on the case object to store escalation reason

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Enable Einstein GPT for Bots to generate handoff scripts

Question 6

A company wants to use Einstein Vision and Language Platform to automatically classify images of products and extract text from labels. Which TWO capabilities of the platform can be used for this requirement? (Select two.)

Accepted Answer

Image classification. Image classification is the correct capability because it allows the platform to automatically assign predefined labels (e.g., product categories) to images based on their visual content. This directly meets the requirement to classify images of products using the Einstein Vision and Language Platform.

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Sentiment analysis

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Text extraction (OCR)

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Named Entity Recognition (NER)

Question 7

A sales manager wants to automatically prioritize leads based on their likelihood to convert, using historical data on won/lost opportunities. Which Salesforce Einstein feature should they use?

Accepted Answer

Einstein Lead Scoring. Einstein Lead Scoring is the correct feature because it specifically uses historical data on won/lost opportunities to assign a score to leads, indicating their likelihood to convert. This directly matches the sales manager's need to prioritize leads based on conversion probability, leveraging predictive models trained on past opportunity outcomes.

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Einstein Opportunity Scoring

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Einstein Discovery

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Einstein Prediction Builder

Question 8

A service manager wants to auto-classify incoming cases into Type, Priority, and Reason fields to streamline routing. Which Einstein feature should they use?

Accepted Answer

Einstein Case Classification. Einstein Case Classification is the correct feature because it uses machine learning to automatically predict and populate the Type, Priority, and Reason fields for incoming cases based on historical case data. This directly addresses the service manager's need to auto-classify cases for streamlined routing, without requiring manual rules or human intervention.

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Einstein Next Best Action

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Einstein Article Recommendations

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Einstein Email Insights

Question 9

An admin wants to use Einstein GPT to generate personalized sales emails for reps. They need to ensure the emails include the latest product inventory data from an external system. Which approach should they take?

Accepted Answer

Create a Prompt Template in Prompt Builder that calls an Apex class to fetch inventory data, then use it in Sales GPT. It leverages Prompt Builder to create a custom prompt template that calls an Apex class, enabling real-time retrieval of external inventory data via an API callout. This ensures the personalized sales emails generated by Einstein Sales GPT always include the latest product inventory without manual intervention or stale data.

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Embed a report snapshot in the email using Einstein Analytics

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Use Einstein Sales GPT with a standard template and manually update the inventory data weekly

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Use Einstein Copilot to ask the rep to check inventory before sending each email

Question 10

A company uses Einstein Lead Scoring but notices that many leads with high scores are not converting. The admin wants to understand which factors are influencing the score. Where can the admin find this information?

Accepted Answer

On the lead record, in the Einstein Lead Score component, by clicking 'Score Factors'. The Einstein Lead Score component on the lead record includes a 'Score Factors' link that, when clicked, displays the top positive and negative factors influencing the lead score. This is the designated UI element for admins to gain transparency into which attributes (e.g., source, industry, behavior) are driving the score, without needing to access setup menus or external support.

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In the Einstein Setup menu under Lead Scoring Models

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By contacting Salesforce support for a model explanation

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By running a report on the Lead object with the Einstein Score field

Question 11

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.

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Einstein GPT

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Einstein Analytics

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Einstein Prediction Builder

Question 12

A company wants to build a custom AI model that predicts whether a customer will churn within the next 30 days, using data from multiple Salesforce objects. The prediction should output a score from 0 to 100. Which Einstein feature is most appropriate?

Accepted Answer

Einstein Prediction Builder. Einstein Prediction Builder is the correct choice because it allows users to build custom predictive models using data from multiple Salesforce objects without writing code, and it outputs a score (0–100) representing the likelihood of a specific outcome, such as customer churn within 30 days. This feature is designed for point-and-click creation of binary classification models that generate a probability score, directly matching the requirement.

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Einstein Discovery

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Einstein Case Classification

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Einstein Next Best Action

Question 13

An admin is configuring Einstein Bots for a service center. They want the bot to understand when a customer says 'I want to return my order' and route to a return flow. What must the admin create to enable this understanding?

Accepted Answer

A new intent with training phrases such as 'I want to return my order'. In Einstein Bots, intents represent the customer's goal (e.g., 'Return Order'), and entities capture details (e.g., order number). The admin must create an intent with training phrases like 'I want to return my order' so the NLP model recognizes it. Actions are separate from intent definition.

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A new action in Bot Builder

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A new dialogue flow linked to a 'Return Order' topic

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A new entity for 'return order'

Question 14

A sales rep wants to automatically log emails from Microsoft Outlook to Salesforce without manual forwarding. Which feature should the admin enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (EAC) is the correct feature because it automatically syncs emails and events from Microsoft Outlook (or Google) into Salesforce without requiring manual forwarding or BCC. It uses a background synchronization service that captures email metadata and content based on configured rules, enabling automatic logging directly to related Salesforce records.

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Einstein GPT for Sales

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Einstein Conversation Insights

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Einstein Email Insights

Question 15

A company uses Einstein Forecasting and notices that the AI forecast is consistently lower than the rep commit for the same period. The sales director wants to rely on the more accurate prediction. What should they do?

Accepted Answer

Use the AI forecast as the primary forecast after reviewing its accuracy against past periods. The recommended approach is to validate the AI forecast's accuracy by comparing it against historical actuals before adopting it as the primary forecast. Einstein Forecasting uses machine learning to analyze historical data and trends, and if it consistently underperforms rep commits, the sales director should first verify its accuracy over past periods to ensure it is reliable. This aligns with best practices for AI-driven forecasting, where trust is built through evidence rather than manual overrides or disabling human input.

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Disable rep commit entries to force reliance on AI forecast

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Retrain the Einstein Forecasting model with manual adjustments

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Override the AI forecast with the rep commit values in the forecast grid