AI Associate Salesforce Einstein AI Features Practice Test 13 — 15 Questions

Question 1

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?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

There is insufficient interaction data for the product category. Einstein Recommendation Builder relies on historical interaction data (such as purchases, views, etc.) to generate personalized recommendations. If users who frequently purchase from one category are not getting relevant recommendations, it is likely because there is insufficient interaction data for that category to train the model effectively. Without enough data, the model cannot learn patterns to make accurate suggestions.

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 2

A service agent needs to quickly find a relevant knowledge article while working on a case. Which Einstein feature can automatically suggest articles based on the case details?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations is the correct answer because it is the specific Einstein feature designed to automatically surface relevant knowledge articles based on the context of a case, such as subject, description, and product. It uses natural language processing (NLP) to match case details against article content, providing agents with immediate, relevant suggestions without manual search.

Answer

Einstein Prediction Builder

Answer

Einstein Case Classification

Answer

Einstein Next Best Action

Question 3

A company wants to implement an autonomous AI agent using Agentforce. Which TWO components are essential for building the agent in Agent Builder?

Accepted Answer

Topics. In Agent Builder, Topics are the essential organizational units that define the scope of what an agent can handle — each Topic groups related instructions, and the agent uses topic classification to route a user's request to the right area of expertise, so option B is correct. Actions are equally essential because they define the specific tasks the agent can perform within a Topic (for example, calling a Flow, Apex, or prompt template), giving the agent its executable capabilities, so option C is correct. Users (A) are the people who interact with the agent and are not a build component, Profiles (D) are Salesforce permission sets of settings that govern access rather than agent construction, and Apex triggers (E) are database event-driven automation and are not required to define an agent's topics or actions.

Answer

Users

Answer

Profiles

Answer

Apex triggers

Question 4

An admin is training an Einstein Prediction Builder model for binary classification (lead conversion). The model performance is poor. Which THREE actions should the admin take to improve it?

Accepted Answer

Increase the number of records in the training dataset. Option A is correct because Einstein Prediction Builder learns from historical data, so increasing the number of records in the training dataset gives the model more examples to detect meaningful patterns and improves accuracy, provided the data is relevant and clean. Option C is correct because removing features with little correlation to conversion reduces noise and irrelevant inputs, which helps the model focus on the variables that actually influence the predicted outcome. Option E is correct because the prediction field (e.g., converted) must be well-represented in the data; if one class is severely imbalanced or the field has many blanks, the model cannot learn the binary classification reliably. Option B is not correct because using fewer records generally reduces the model's ability to learn and can worsen performance rather than prevent overfitting. Option D is not correct because adding unrelated features introduces noise and can degrade model quality instead of improving it.

Answer

Use fewer records to avoid overfitting

Answer

Add more features, even if they are not related

Question 5

A sales operations manager wants to automatically log all emails and events from sales reps' Outlook accounts to Salesforce without manual setup. Which feature should they enable?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (D) is the correct feature because it automatically syncs emails and events from Microsoft 365 or Google Workspace into Salesforce without requiring manual setup or user-installed add-ins. It uses a server-side integration that logs activities directly to Salesforce records, meeting the requirement for automatic logging of Outlook emails and events.

Answer

Einstein Conversation Insights

Answer

Einstein Lead Scoring

Answer

Einstein Email Insights

Question 6

A support agent needs to quickly find a relevant knowledge article while handling a case. Which Einstein feature suggests articles automatically?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations is a Salesforce Einstein feature that automatically suggests relevant knowledge articles to support agents based on the case subject, description, and other data. It uses natural language processing and machine learning to analyze the case and match it with the most pertinent articles, helping agents resolve issues faster. This directly addresses the need to quickly find a relevant knowledge article while handling a case.

Answer

Einstein Next Best Action

Answer

Einstein Recommendation Builder

Answer

Einstein Case Classification

Question 7

A company wants to create a custom AI model that predicts whether a support case will be escalated (Yes/No) based on historical case data. They have fields like Case Origin, Priority, and Description. Which Einstein feature should they use?

Accepted Answer

Einstein Prediction Builder. Einstein Prediction Builder is the correct feature because it allows users to create custom binary classification models (e.g., Yes/No predictions) using their own historical data fields such as Case Origin, Priority, and Description. Unlike pre-built models, Prediction Builder is designed for custom objectives like predicting case escalation without requiring data science expertise.

Answer

Einstein Case Classification

Answer

Einstein Next Best Action

Answer

Einstein Discovery

Question 8

An admin wants to provide a conversational AI assistant within the CRM that can answer user questions about records, generate summaries, and create tasks. Which feature should they enable?

Accepted Answer

Einstein Copilot. Einstein Copilot is Salesforce's conversational AI assistant embedded in the CRM that can answer natural-language questions about records, generate summaries, and take actions such as creating tasks. It is purpose-built for the in-CRM conversational assistant use case described.

Answer

Einstein GPT

Answer

Einstein Bots

Answer

Agentforce

Question 9

A sales manager wants to see how AI-predicted forecast amounts compare to sales reps' committed amounts. Which feature provides this comparison?

Accepted Answer

Einstein Forecasting. Einstein Forecasting is the correct feature because it directly compares AI-predicted forecast amounts against sales reps' committed amounts. This allows sales managers to see discrepancies between the AI's data-driven predictions and the reps' manual commitments, enabling more accurate pipeline management.

Answer

Einstein Discovery

Answer

Einstein Lead Scoring

Answer

Einstein Opportunity Scoring

Question 10

A company uses Einstein Bots for customer support. They want the bot to understand when a customer says 'I want to return a product' and trigger a return flow. What must be configured to recognize this intent?

Accepted Answer

Train the bot's NLP with sample utterances for the 'Return_Product' intent. Einstein Bots rely on Natural Language Processing (NLP) to interpret user intent from free-form text. To recognize the intent 'Return_Product', you must train the bot's NLP model by providing sample utterances (phrases) that represent that intent. This allows the bot to generalize and match variations like 'I need to send this back' or 'How do I return an item?' without requiring exact phrase matching.

Answer

Add a dialogue step that matches the phrase exactly

Answer

Create an entity for 'product' and map it to return flow

Answer

Use Einstein Article Recommendations to surface return policy

Question 11

A data analyst wants to understand why a particular opportunity win rate dropped last quarter. They need automated statistical analysis with natural language explanations and improvement suggestions. Which tool should they use?

Accepted Answer

Einstein Discovery. Einstein Discovery provides automated statistical analysis, stories, and improvement suggestions.

Answer

Einstein Prediction Builder

Answer

Einstein Conversation Insights

Answer

Einstein Next Best Action

Question 12

An admin wants to create a prompt template that dynamically pulls the case subject and description to generate a knowledge article draft. Which prompt template type should they use in Prompt Builder?

Accepted Answer

Field Generation. Field Generation prompt templates in Prompt Builder are designed to pull values from record fields (such as Case Subject and Case Description) and generate content into a target field, which is exactly what is needed to draft a knowledge article from case data. This template type supports dynamic merge fields tied to the object's schema.

Answer

Sales Email

Answer

Service GPT Reply Recommendation

Answer

Flex Prompt

Question 13

A service manager wants AI to automatically generate a summary of a phone call recording and capture follow-up tasks. Which Einstein feature should they use?

Accepted Answer

Einstein Conversation Insights. Einstein Conversation Insights is the Salesforce feature designed to transcribe and analyze voice and video calls (including phone calls via Einstein Conversation Insights or Sales/Service Cloud Voice), automatically generating summaries, extracting key topics, and surfacing follow-up tasks. It directly matches the requirement to summarize a phone call recording and capture action items.

Answer

Einstein Email Insights

Answer

Service GPT

Answer

Einstein Activity Capture

Question 14

A service manager wants to automatically classify incoming cases into Type, Priority, and Reason fields to reduce manual data entry. Which Einstein feature best meets this requirement?

Accepted Answer

Einstein Case Classification. Einstein Case Classification is specifically designed to automatically predict and populate fields like Type, Priority, and Reason for incoming cases using machine learning models trained on historical case data. This reduces manual data entry by suggesting or auto-filling these fields based on the case's subject, description, and other attributes.

Answer

Einstein Discovery

Answer

Einstein Next Best Action

Answer

Einstein Article Recommendations

Question 15

A company needs to build a custom AI model that predicts whether a support case will be escalated based on account history, case description, and product category. The output should be a binary yes/no. Which tool should they use?

Accepted Answer

Einstein Prediction Builder. Einstein Prediction Builder is the correct tool because it is specifically designed for binary classification (yes/no) predictions using structured data from Salesforce objects, such as account history, case description, and product category. It allows admins to create custom predictive models without code, directly within the Salesforce platform, making it ideal for predicting case escalation.

Answer

Einstein Vision and Language Platform

Answer

Einstein Discovery

Answer

Einstein GPT