AI Associate Salesforce Einstein AI Features Practice Test 7 — 15 Questions

Question 1

A developer needs to use the Einstein Vision and Language Platform to classify images and extract named entities from text. Which THREE API capabilities should they use?

Accepted Answer

Named Entity Recognition (NER). The scenario requires classifying images and extracting named entities from text using the Einstein Vision and Language Platform, so the developer needs the platform's image classification capability (option D), which assigns labels/categories to images via the Einstein Image Classification API, and Named Entity Recognition (option A), which is the Einstein Language API service that identifies and extracts entities such as people, places, and organizations from text. Object detection (option B) is also correct because it is a core Einstein Vision capability that locates and classifies multiple objects within an image, extending the image-classification requirement for scenarios where objects must be identified by bounding box. Fine-tuning BERT models (option C) is not a capability exposed by the Einstein Vision and Language Platform, and deploying custom models on edge devices (option E) is unrelated to the platform's hosted classification and language APIs, so neither belongs here.

Answer

Fine-tuning BERT models

Answer

Deploying custom models on edge devices

Question 2

A service manager wants to implement Einstein Case Classification to automatically classify incoming cases. Which THREE objects are suitable for case classification?

Accepted Answer

Case.Priority. Einstein Case Classification predicts values for specific picklist fields on the Case object, so the suitable targets are Case.Priority (A), Case.Reason (B), and Case.Type (D), all of which are standard picklist fields that can be configured as classification fields. Case.Priority is commonly used to auto-predict urgency, Case.Reason captures why the customer contacted support, and Case.Type identifies the nature of the case — all valid picklist targets for the model. Case.Status (C) is excluded because it is a lifecycle/state field driven by support processes rather than a predictive classification target. Case.OwnerId (E) is excluded because it is a lookup/user reference field, not a picklist, and cannot be predicted by Einstein Case Classification.

Answer

Case.Status

Answer

Case.OwnerId

Question 3

A company is using Einstein Discovery to improve customer retention. The data scientist wants to understand the key drivers of churn and receive actionable recommendations. Which THREE capabilities of Einstein Discovery support this goal?

Accepted Answer

Improvement suggestions. Option A (Improvement suggestions) is correct because Einstein Discovery generates prescriptive, actionable recommendations that show how changing specific predictor values would improve the predicted outcome, directly supporting the goal of acting on churn drivers. Option C (Waterfall charts) is correct because they visually decompose each prediction into the individual predictors' positive and negative contributions, revealing the key drivers behind a customer's churn risk. Option D (Automated statistical analysis) is correct because Einstein Discovery automatically performs the statistical modeling, feature ranking, and significance testing needed to identify which variables most influence churn. Option B (Chatbot integration) is not part of Einstein Discovery's analytics capabilities—it relates to Einstein Bots for conversational interfaces. Option E (Story creation) is not a distinct Einstein Discovery capability for this purpose; insights are delivered through stories/models, but 'story creation' is not one of the three analytical capabilities that identify drivers and recommendations.

Answer

Chatbot integration

Answer

Story creation

Question 4

A support agent needs to quickly summarize a long case history and draft a knowledge article from the case. Which TWO Einstein GPT features can help?

Accepted Answer

Service GPT – Knowledge Article Draft. Service GPT – Case Summary (A) is correct because it is purpose-built to generate a concise summary of a case's history, including its interactions and activity, which directly addresses the agent's need to quickly summarize a long case history. Service GPT – Knowledge Article Draft (C) is also correct because it uses case data to automatically draft a knowledge article, matching the requirement to create a knowledge article from the case. Einstein Copilot – Field Generation (B) only populates individual record fields and does not summarize case history or draft articles. Sales GPT – Call Summaries (D) is designed for sales call summarization, not service case histories or knowledge articles. Einstein Recommendation Builder (E) generates recommendations for offers or next best actions, not case summaries or article drafts.

Answer

Einstein Copilot – Field Generation

Answer

Sales GPT – Call Summaries

Answer

Einstein Recommendation Builder

Question 5

An administrator wants to automatically log emails from a specific domain to Salesforce using Einstein Activity Capture. Which TWO settings must be configured?

Accepted Answer

Add the domain to the excluded addresses list. Option E is correct because Einstein Activity Capture must first be enabled for the org before any email logging behavior can occur; without turning on the feature in Setup, no automatic capture of emails or events happens. Option B is correct because adding the specific domain to the excluded addresses list prevents Einstein Activity Capture from logging emails from that domain, which is exactly how an administrator controls which emails are automatically captured versus excluded. Option A is incorrect because email-to-Salesforce addresses are used for the Email-to-Salesforce feature, not for Einstein Activity Capture's automatic logging. Option C is incorrect because a Flow is not required to process emails for Einstein Activity Capture; the service handles capture natively. Option D is incorrect because Einstein Bots API is unrelated to email activity capture and is used for bot interactions.

Answer

Configure email-to-Salesforce address

Answer

Create a flow to process emails

Answer

Set up Einstein Bots API

Question 6

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 surfaces Next step capture (A), automatically detecting and displaying action items or follow-up commitments made during a sales call so reps can act on them. It also provides Talk-time metrics (B), quantifying how much each participant spoke (e.g., rep vs. customer talk ratio) to help coach balanced conversations. Keyword tracking (C) is included as well, letting teams define and monitor specific terms or competitor mentions across calls. Full transcript generation (D) is not a Conversation Insights capability — transcription is handled by Einstein Conversation Insights' underlying speech-to-text only as input, and the feature itself does not deliver full verbatim transcripts as an output. Sentiment analysis of the call (E) is likewise not a listed Conversation Insights output; while related Einstein features may surface sentiment elsewhere, it is not one of the three capabilities this feature provides.

Answer

Full transcript generation

Answer

Sentiment analysis of the call

Question 7

A developer wants to use the Einstein Vision and Language Platform to classify customer feedback text into categories. Which THREE capabilities of the platform can be used for this task?

Accepted Answer

Einstein Bots API. Einstein Bots API (B) is correct because it exposes the Einstein Language intent/classification models through a REST API, allowing customer feedback text to be sent and categorized by a trained intent model. Text classification (C) is correct because it is the core Einstein Language capability that assigns a piece of text to one or more predefined categories, exactly matching the developer's goal of classifying feedback. Named Entity Recognition (E) is correct because NER is another Einstein Language capability that extracts entities from text and can be used alongside classification to enrich and route feedback by identifying key terms. Object detection (A) and image classification (D) are not correct because both are Einstein Vision capabilities that operate on images rather than text, so they cannot classify customer feedback text.

Answer

Object detection

Answer

Image classification

Question 8

A sales operations manager wants to use Einstein Lead Scoring to prioritize leads. Where can the lead score be viewed in Salesforce?

Accepted Answer

As a field on the lead record and in list views. Einstein Lead Scoring writes the score to a standard field on the Lead object, so it is visible directly on the lead record and can be surfaced in list views, reports, and filters. This makes prioritization actionable in the rep's normal workflow rather than requiring a separate analytics tool.

Answer

Only in Einstein Analytics dashboards

Answer

Only in the Einstein Lead Scoring setup page

Answer

In the Einstein Lead Scoring mobile app only

Question 9

A service manager wants to automatically categorize incoming cases based on their description. Which Einstein feature should be used?

Accepted Answer

Einstein Case Classification. Einstein Case Classification uses natural language processing to automatically predict and populate standard case fields such as Type, Priority, and Reason based on the case description. It is purpose-built for categorizing incoming cases using historical data patterns. This directly matches the manager's goal of auto-categorizing cases from their descriptions.

Answer

Einstein Reply Recommendations

Answer

Einstein Vision

Answer

Einstein Article Recommendations

Question 10

A sales rep wants to automatically log emails and events to Salesforce without manual entry. Which feature should the admin enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture automatically syncs emails, events, and contacts between Microsoft 365 or Google Workspace and Salesforce, logging them to the correct records without manual entry. It is the feature designed specifically for automatic activity logging, matching the sales rep's requirement. Admins enable it via Setup and configure user-level sync settings.

Answer

Einstein Conversation Insights

Answer

Einstein Email Insights

Answer

Einstein Activity Capture is not available; use the standard Email-to-Salesforce

Question 11

An admin is setting up Einstein Prediction Builder to predict whether a lead will convert. The admin has selected the prediction field and data set. What is the next step in the configuration wizard?

Accepted Answer

Select features (input fields) to train the model. After selecting the prediction field and data set in Einstein Prediction Builder, the next step is to select the features (input fields) that the model will use to learn patterns and make predictions. These features are the variables that correlate with the outcome. The wizard then proceeds to train the model, but feature selection is a prerequisite. Defining prediction explanation and choosing the score field come later or are optional.

Answer

Train the model immediately

Answer

Define the prediction explanation

Answer

Choose the prediction score field

Question 12

Which Einstein feature provides AI-powered predictions for opportunity win likelihood?

Accepted Answer

Einstein Opportunity Scoring. Einstein Opportunity Scoring uses AI to analyze historical opportunity data and predict the likelihood that an open opportunity will be won. It surfaces a score (typically 1–100) on the opportunity record so reps can prioritize deals. This is distinct from Lead Scoring, which predicts conversion of leads, not opportunities.

Answer

Einstein Forecasting

Answer

Einstein Lead Scoring

Answer

Einstein Prediction Builder

Question 13

A company wants to implement an autonomous AI agent in Salesforce that can handle customer service cases end-to-end. Which feature should they use?

Accepted Answer

Agentforce. Agentforce is the correct feature because it is specifically designed to create autonomous AI agents that can handle customer service cases end-to-end in Salesforce. Unlike simpler bots or copilots, Agentforce can independently execute multi-step workflows, make decisions, and take actions across Salesforce objects without requiring human intervention for every step.

Answer

Einstein Copilot

Answer

Einstein Next Best Action

Answer

Einstein Bots

Question 14

A data scientist wants to use Einstein Vision to detect defects in product images. Which type of model should they create?

Accepted Answer

Object detection. Einstein Vision's object detection model is designed to locate and classify multiple objects within an image, returning bounding boxes with labels — which is exactly what defect detection requires when defects can appear anywhere in a product image. Image classification, by contrast, only assigns a single label to the entire image and cannot localize where the defect is. For identifying and locating defects, object detection is the correct model type.

Answer

Image classification

Answer

Named entity recognition

Answer

Text classification

Question 15

A company uses Einstein Forecasting to predict sales. What is a key difference between the AI forecast and the rep commit forecast?

Accepted Answer

AI forecast uses historical data and trends; rep commit is based on rep's manual entry. The AI forecast in Einstein Forecasting leverages historical data, trends, and machine learning models to generate predictions, while the rep commit forecast relies on manual entries made by sales representatives. This distinction is fundamental: AI forecasts are data-driven and automated, whereas rep commits are subjective and based on individual rep judgment.

Answer

AI forecast is always more accurate than rep commit

Answer

Rep commit is used for quota setting; AI forecast is not

Answer

AI forecast is only available in Enterprise Edition