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

Question 1

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.

Answer

Einstein Opportunity Scoring

Answer

Einstein Discovery

Answer

Einstein Prediction Builder

Question 2

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.

Answer

Einstein Next Best Action

Answer

Einstein Article Recommendations

Answer

Einstein Email Insights

Question 3

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. Option D is correct because 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.

Answer

Embed a report snapshot in the email using Einstein Analytics

Answer

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

Answer

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

Question 4

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'. Option C is correct because 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.

Answer

In the Einstein Setup menu under Lead Scoring Models

Answer

By contacting Salesforce support for a model explanation

Answer

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

Question 5

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 6

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.

Answer

Einstein Discovery

Answer

Einstein Case Classification

Answer

Einstein Next Best Action

Question 7

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.

Answer

A new action in Bot Builder

Answer

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

Answer

A new entity for 'return order'

Question 8

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.

Answer

Einstein GPT for Sales

Answer

Einstein Conversation Insights

Answer

Einstein Email Insights

Question 9

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. Option D is correct because 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.

Answer

Disable rep commit entries to force reliance on AI forecast

Answer

Retrain the Einstein Forecasting model with manual adjustments

Answer

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

Question 10

A user wants to use Einstein GPT to automatically generate a case summary after a service call is logged. Which feature should they use?

Accepted Answer

Service GPT. Service GPT is the correct feature because it is specifically designed to automate service-related tasks within Salesforce, such as generating case summaries after a service call. It leverages generative AI to analyze call logs and produce concise summaries, directly addressing the user's need for post-call documentation.

Answer

Einstein Discovery

Answer

Sales GPT

Answer

Einstein Copilot

Question 11

An admin wants to deploy an autonomous AI agent that can handle order cancellations end-to-end without human intervention. The agent needs to execute specific actions like querying order status and updating records. Which tool should they use?

Accepted Answer

Agentforce with Agent Builder. Agentforce with Agent Builder is the correct tool because it is specifically designed to build autonomous AI agents that can execute end-to-end workflows, including querying order status and updating records, without human intervention. It uses a combination of large language models, deterministic actions, and guardrails to handle complex, multi-step tasks like order cancellations autonomously.

Answer

Einstein Bots

Answer

Einstein Next Best Action

Answer

Einstein GPT with Prompt Builder

Question 12

A marketing team wants to recommend products to customers in an Experience Cloud community using AI. Which feature should they implement?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is the correct feature because it allows marketers to create and deploy AI-powered product recommendations specifically within Experience Cloud communities, using customer behavior and profile data to personalize the community experience. Unlike other Einstein features, Recommendation Builder is designed for community sites and can be configured without code to recommend products, articles, or custom records.

Answer

Einstein GPT for Sales

Answer

Einstein Article Recommendations

Answer

Einstein Next Best Action

Question 13

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 14

An admin is using Einstein Prediction Builder to create a model predicting whether a support case will be escalated. Which THREE steps are required during the prediction creation process?

Accepted Answer

Select features (input fields) for the model. Option B is correct because selecting features (input fields) is a fundamental step in building a prediction model with Einstein Prediction Builder. These features are the independent variables that the model uses to learn patterns and make predictions about the target field (e.g., case escalation). Without selecting relevant features, the model cannot be trained effectively.

Answer

Run Einstein Discovery to validate the model

Answer

Configure Einstein Copilot to trigger the prediction

Question 15

A service team wants to implement Einstein Article Recommendations to help agents find knowledge articles faster. Which TWO prerequisites must be met for this feature to work?

Accepted Answer

Knowledge base must contain at least 1,000 published articles. Option B is correct because Einstein Article Recommendations requires a minimum of 1,000 published articles in the Knowledge base to generate statistically significant recommendations. This threshold ensures the machine learning model has enough data to identify patterns and suggest relevant articles based on case context.

Answer

Agents must use the Service Console with the article recommendations component

Answer

Admin must manually enable Einstein Article Recommendations in Setup

Answer

Organization must purchase an additional Einstein license