AI Associate Practice Test 44 — 15 Questions

Question 1

A service manager wants to use Einstein for case deflection. Which TWO features can help automatically resolve or route cases without agent involvement? (Choose two.)

Accepted Answer

Einstein Case Classification. Einstein Case Classification (A) is correct because it uses predictive AI to automatically categorize and route incoming cases based on historical data, enabling cases to be assigned to the right queue or agent without manual triage, and it can also power automated case deflection by surfacing relevant self-service content. Einstein Bots (D) is correct because it provides automated conversational self-service on web, SMS, and messaging channels, allowing customers to resolve common issues or be routed appropriately without any agent involvement. Einstein Next Best Action (B) is not correct here because it recommends actions to agents or customers within a guided flow but does not itself automatically resolve or route cases. Einstein Discovery (C) is not correct because it focuses on predictive analytics and model insights rather than automated case resolution or routing. Einstein Article Recommendations (E) is not correct because it suggests knowledge articles to agents or customers but does not automatically resolve or route cases on its own.

Answer

Einstein Next Best Action

Answer

Einstein Discovery

Answer

Einstein Article Recommendations

Question 2

A customer service team wants to automatically log all Outlook emails to Salesforce. They have enabled Einstein Activity Capture. However, some emails from a specific external domain are not being captured. What is the most likely cause?

Accepted Answer

The external domain has been added to the Excluded Email Domains list in Activity Capture settings.. Einstein Activity Capture uses an Excluded Email Domains list in its settings to filter out emails from specified domains. If emails from a particular external domain are not being captured, the most likely cause is that the domain has been added to this exclusion list, either intentionally or accidentally. This setting overrides the general capture behavior, so even if all other conditions are met, emails from that domain will be ignored.

Answer

The email's subject line contains special characters.

Answer

The users have not installed the Einstein Activity Capture Outlook add-in.

Answer

The email addresses are not in Salesforce as Contacts or Leads.

Question 3

A company wants to use Einstein Prediction Builder to predict whether a support case will be escalated within the first 24 hours. Which field should be selected as the prediction field?

Accepted Answer

A checkbox field named 'Escalated within 24 hours'. Einstein Prediction Builder requires the prediction field to be a binary outcome (e.g., true/false, yes/no) that the model will learn to predict. A checkbox field named 'Escalated within 24 hours' directly represents the binary target (checked = escalated, unchecked = not escalated) needed for supervised classification.

Answer

A date field for the escalation date

Answer

A text field with case escalation notes

Answer

A numeric field representing escalation time in hours

Question 4

A company wants to build an autonomous AI agent that can handle customer inquiries and perform actions like updating records or creating orders without human intervention. Which Salesforce solution should they use?

Accepted Answer

Agentforce. Agentforce is the correct solution because it is designed to build autonomous AI agents that can handle complex customer inquiries and perform actions like updating records or creating orders without human intervention. It leverages large language models and integrates with Salesforce Data Cloud to enable reasoning, planning, and execution of multi-step tasks autonomously.

Answer

Einstein Copilot

Answer

Einstein Bots

Answer

Einstein Prediction Builder

Question 5

A sales manager wants to understand why certain opportunities are predicted to close won while others are not. They need a visual breakdown of the key factors influencing the prediction. Which Einstein feature provides this automatically?

Accepted Answer

Einstein Discovery. Einstein Discovery is the correct feature because it automatically analyzes historical data to identify and visualize the key factors (drivers) that influence prediction outcomes, such as why certain opportunities close won. Unlike scoring features that provide a single score, Einstein Discovery offers a visual breakdown of influential factors, making it ideal for understanding the 'why' behind predictions.

Answer

Einstein Lead Scoring

Answer

Einstein Forecasting

Answer

Einstein Opportunity Scoring

Question 6

A sales manager notices that Einstein Lead Scoring assigns lower scores to leads from a specific region. After investigation, they find that the historical conversion data for that region is sparse and unrepresentative. What should the manager do to improve the model's fairness?

Accepted Answer

Collect more data from that region to provide a representative sample for retraining. The core issue is data sparsity and unrepresentative historical conversion data for that region. By collecting more data from that region, the model can be retrained on a balanced dataset, which directly addresses the root cause of the biased lead scoring. This aligns with the principle of fairness in AI, where models must be trained on representative data to avoid systematic discrimination.

Answer

Adjust the lead scoring formula manually to increase scores for that region

Answer

Remove the region field from the model

Answer

Accept the scores as-is because the model is certified

Question 7

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.

Answer

Einstein Prediction Builder

Answer

Einstein Next Best Action

Answer

Einstein Vision and Language Platform

Question 8

A sales manager wants to use Einstein Lead Scoring to prioritize leads. Which TWO capabilities are part of Einstein Lead Scoring?

Accepted Answer

Surfaces the lead score in list views and reports. Einstein Lead Scoring assigns each lead a score from 1 to 99 that reflects its likelihood of converting, so option D is correct because that numeric scoring model is the core function of the feature. Option A is also correct because the resulting score is exposed as a field that can be displayed in lead list views and used in reports, letting the sales manager sort and filter leads by priority. Option B is incorrect because generating email drafts is a capability of Einstein for Sales features like Sales Email, not Lead Scoring. Option C is incorrect because automatic email and event logging is handled by Einstein Activity Capture, not Lead Scoring. Option E is incorrect because chatbot-based lead follow-up is an Einstein Bots function, which is separate from lead scoring.

Answer

Generates email drafts for sales reps

Answer

Automatically logs emails and events to Salesforce

Answer

Uses a chatbot to follow up with leads

Question 9

Refer to the exhibit. A bot developer sees this error during Einstein Bot deployment. What is the correct action to resolve the issue?

Accepted Answer

Add at least 5 training phrases to the 'OrderStatus' intent. The error indicates that the 'OrderStatus' intent has fewer than the required minimum number of training phrases. Einstein Bot requires at least 5 training phrases per intent to ensure reliable natural language processing (NLP) model training. Adding at least 5 training phrases to the 'OrderStatus' intent satisfies this requirement and resolves the deployment error.

Answer

Reduce the minimum required phrases in bot settings

Answer

Remove the 'OrderStatus' intent from the bot

Answer

Increase the confidence threshold for all intents

Question 10

A company wants to deploy an Einstein Prediction Builder model to predict lead conversion within 30 days. They have historical data from the past 12 months. Which data preprocessing step is most critical to ensure the model learns correctly?

Accepted Answer

Ensure the target variable is computed based on conversion status at exactly 30 days from creation.. The target variable for a time-based prediction model like Einstein Prediction Builder must be computed at a precise, consistent point in time—in this case, exactly 30 days from lead creation. If the target is computed at varying intervals, the model will learn incorrect patterns, as it cannot distinguish between leads that converted at 31 days versus those that never converted, leading to biased or invalid predictions.

Answer

Normalize all numerical features to a 0-1 range.

Answer

Remove leads that converted after 30 days.

Answer

Include only leads that were assigned to a sales rep.

Question 11

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.

Answer

Einstein Prediction Builder

Answer

Einstein Bots

Answer

Einstein GPT

Question 12

A company wants to use Einstein to predict the optimal discount amount for each deal. Which type of machine learning problem does this represent?

Accepted Answer

Regression. Predicting a continuous numerical value, such as the optimal discount amount for a deal, is a regression problem. In the context of Einstein, this would use a regression model to learn from historical deal data and output a specific discount percentage or dollar amount, rather than a category or cluster.

Answer

Reinforcement learning

Answer

Classification

Answer

Clustering

Question 13

What is the primary purpose of the Einstein Trust Layer's zero data retention setting?

Accepted Answer

To ensure that customer data is not used to train or improve Salesforce's base AI models.. The Einstein Trust Layer's zero data retention setting ensures that customer data processed by Salesforce's AI models is not stored or used to train or improve the base AI models. This addresses privacy and compliance concerns by preventing data leakage into model training pipelines.

Answer

To comply with Salesforce's internal data management policies only.

Answer

To improve model accuracy by preventing old data from influencing predictions.

Answer

To reduce storage costs for the customer.

Question 14

A company uses Einstein Bots to handle customer inquiries. To comply with GDPR's right to explanation for automated decisions affecting customers, which TWO capabilities must the bot implementation include?

Accepted Answer

Provide a mechanism for customers to request an explanation of the bot's decision. Option C is correct because GDPR's right to explanation (Articles 13-15 and 22) requires that data subjects be able to obtain meaningful information about the logic involved in automated decision-making, so the bot must offer a mechanism for customers to request an explanation of its decisions. Option E is correct because logging the factors that influenced each decision provides the auditable record needed to actually deliver that explanation and demonstrate accountability under GDPR. Option A is not required by the right to explanation specifically, since consent is a separate lawful basis under Article 6 and not the mechanism that satisfies explanation rights. Option B is irrelevant because benchmark accuracy does not address transparency or explainability obligations. Option D is also irrelevant because a fixed 30-day retention period is not mandated by GDPR and does not fulfill the right to explanation.

Answer

Collect explicit consent from customers before using the bot

Answer

Use a pre-trained model with high accuracy on industry benchmarks

Answer

Retain customer data for at least 30 days after the interaction

Question 15

An administrator is setting up Einstein Next Best Action to recommend a discount offer to sales reps when an opportunity is at risk. The recommendation logic should consider the opportunity stage, amount, and close date. Which tool should the administrator use to define the recommendation strategy?

Accepted Answer

Strategy Builder with a Flow. Einstein Next Best Action uses Strategy Builder to define recommendation logic, which evaluates conditions like opportunity stage, amount, and close date to surface a discount offer. Strategy Builder allows administrators to create decision trees and rules that trigger actions, such as displaying a recommendation, without requiring code. A Flow can be embedded within Strategy Builder to execute complex logic or update records when the recommendation is accepted.

Answer

Einstein Prediction Builder

Answer

Einstein Discovery

Answer

Process Builder