AI Associate Salesforce Einstein AI Features Practice Test 6 — 15 Questions

Question 1

A business wants to build a custom AI model to classify images of products and also create a chatbot that answers customer queries about those products. Which THREE Einstein features would they likely use? (Choose 3)

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

Accepted Answer

Einstein Bots. Einstein Bots (A) is correct because it is the Salesforce feature for building conversational chatbots that can answer customer queries, exactly the chatbot requirement in the scenario. Einstein Article Recommendations (D) is correct because it surfaces relevant knowledge articles to customers and service agents, which supports answering product-related questions in a self-service or support context. Einstein Vision and Language Platform (E) is correct because it provides the image classification and natural language processing APIs needed to build a custom AI model that classifies product images. Einstein Forecasting (B) is not appropriate because it predicts business metrics like sales or revenue rather than classifying images or powering a chatbot. Einstein Lead Scoring (C) is not appropriate because it ranks sales leads by conversion likelihood, which is unrelated to image classification or customer query answering.

Answer

Einstein Forecasting

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Einstein Lead Scoring

Question 2

A retail company wants to recommend products to website visitors based on their browsing behavior and purchase history stored in Experience Cloud. Which Einstein feature should they implement?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is the correct feature because it is specifically designed to analyze browsing behavior and purchase history stored in Experience Cloud to generate personalized product recommendations. It uses collaborative filtering and deep learning models to surface relevant items, directly addressing the retail use case of recommending products to website visitors.

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Einstein Prediction Builder

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Einstein Lead Scoring

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Einstein Next Best Action

Question 3

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 4

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. Option A is correct because the Einstein Bot must be associated with a Service Cloud user (often a dedicated bot user) that has the appropriate chat and transfer permissions so the bot can route conversations to a human agent. Option B is correct because a handoff action must be explicitly configured in the bot's dialog flow (for example, a Transfer to Agent or escalation action) to trigger the transition from bot to human. Option D is correct because Omni-Channel routing requires a queue to receive and distribute the transferred chat to available human agents. Option C is not required because storing an escalation reason in a custom case field is optional metadata, not a prerequisite for handoff. Option E is not required because Einstein GPT for Bots is unrelated to enabling the transfer mechanism.

Answer

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

Answer

Enable Einstein GPT for Bots to generate handoff scripts

Question 5

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 (C) is correct because Einstein Vision provides classification models that assign images to predefined product categories, which is exactly what is needed to automatically classify product images. Object detection (E) is correct because Einstein Vision's object detection capability locates and identifies multiple distinct objects within an image, allowing individual products to be detected and categorized within a photo. Together these two vision capabilities cover the image-classification half of the requirement. Text extraction (OCR) (B) is not marked correct here even though OCR exists in the platform, because the two answers the question expects are the vision classification capabilities. Sentiment analysis (A) and Named Entity Recognition (D) are natural language processing features of Einstein Language that operate on text, not images, so they do not satisfy the image classification and label-processing requirement.

Answer

Sentiment analysis

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Text extraction (OCR)

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Named Entity Recognition (NER)

Question 6

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 7

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

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Einstein Case Classification

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Einstein Next Best Action

Question 8

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

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Sales GPT

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Einstein Copilot

Question 9

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

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Einstein Article Recommendations

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Einstein Next Best Action

Question 10

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 volume of published knowledge articles (at least 1,000) to train its machine-learning model and generate meaningful recommendations. Option D is correct because the feature also needs sufficient historical case data—specifically at least 1,000 resolved cases with an article attached—so the model can learn which articles are relevant to which case characteristics. Option A is not a prerequisite because the recommendations component is delivered through standard Lightning Service Console functionality and does not require a specific console configuration to be enabled for the feature itself to work. Option C is incorrect because Einstein Article Recommendations is enabled automatically once the data thresholds are met; there is no separate manual Setup toggle required. Option E is incorrect because Einstein Article Recommendations is included with Salesforce Knowledge and does not require an additional Einstein license purchase.

Answer

Agents must use the Service Console with the article recommendations component

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Admin must manually enable Einstein Article Recommendations in Setup

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Organization must purchase an additional Einstein license

Question 11

A service organization wants to deploy an Einstein Bot to handle common support inquiries. They need to define the bot's conversational flow and train it to understand user requests. Which THREE components must be configured in the bot builder?

Accepted Answer

Intents. In Einstein Bots, Intents (A) are the core building blocks that represent what a user wants to accomplish, so the bot must have defined intents to classify incoming utterances. Training phrases (C) are required because they are the sample utterances attached to each intent that teach the NLU model how users phrase that request, enabling accurate intent matching. Entities (D) must also be configured because they extract specific variable data from user input (such as order numbers, dates, or product names) that the bot needs to fulfill the request. Dialogue flows (E) are marked correct as well, since they define the actual conversational path and responses the bot follows once an intent is recognized. Prediction scores (B) are not a component to configure; they are confidence values the NLU engine generates at runtime to decide how well an utterance matches an intent.

Answer

Prediction scores

Answer

Training phrases

Question 12

An admin wants to use Einstein Activity Capture to automatically log emails and events to Salesforce. Which TWO considerations are important when setting up this feature?

Accepted Answer

Events (meetings) are automatically created as Salesforce events.. Option A is correct because Einstein Activity Capture automatically syncs calendar events from connected email/calendar systems (Outlook or Gmail) and creates them as Salesforce events tied to matching records, without requiring users to manually create them. Option D is correct because admins can configure excluded email addresses and domains in Einstein Activity Capture settings so that emails to or from those addresses are not logged to Salesforce, which is important for privacy and data hygiene. Option B is incorrect because Einstein Activity Capture is included with Salesforce licenses and does not require a separate license for each integration user. Option C is incorrect because Einstein Activity Capture logs emails automatically; users do not need to manually forward them to Salesforce. Option E is incorrect because Einstein Activity Capture supports both Microsoft Outlook and Gmail, not Outlook only.

Answer

It requires a separate license for each integration user.

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Users must manually forward emails to Salesforce.

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It only works with Outlook, not Gmail.

Question 13

An apparel retailer wants to use Einstein Recommendation Builder to show product recommendations on their Experience Cloud site. Which TWO statements are true about this feature?

Accepted Answer

It uses a collaborative filtering algorithm based on user behavior.. Option B is correct because Einstein Recommendation Builder relies on collaborative filtering algorithms that analyze aggregate user behavior—such as views, purchases, and similar-user patterns—to generate personalized product recommendations. Option C is correct because Recommendation Builder can surface both products and content articles, making it suitable for an Experience Cloud site where the retailer may want to recommend merchandise alongside relevant articles or guides. Option A is incorrect because recommendations are not restricted to the same category; cross-category recommendations are a core benefit of behavioral personalization. Option D is incorrect because Einstein licensing is at the org level, not per site visitor. Option E is incorrect because Recommendation Builder automates recommendations through machine learning rather than requiring manually curated rules.

Answer

It can only recommend items from the same category.

Answer

It requires a separate Einstein license for each site visitor.

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It requires manual curation of recommendation rules.

Question 14

An admin is building an autonomous agent using Agentforce. They need to define what the agent can do and how it responds. Which THREE components must be set up in Agent Builder?

Accepted Answer

Testing in Agent Builder to validate behavior. In Agent Builder, Topics (E) are the core building blocks that define the scope of what the agent handles — such as Order Management or Returns — and each topic groups the instructions, actions, and reasoning the agent uses to respond, so it is required. Actions (D), like Lookup Order or Create Return, are the concrete capabilities the agent can invoke within a topic to perform work, so they must be configured to define what the agent can actually do. Testing in Agent Builder (A) is also required because it lets the admin validate the agent's topics, actions, and responses against sample utterances before deployment, ensuring behavior matches intent. Data integration with external systems (B) is not a mandatory Agent Builder setup component — it is handled through separate data/connection configuration (e.g., external services or MuleSoft) rather than being one of the three core Agent Builder elements. Security settings for user permissions (C) are managed through Salesforce sharing, profiles, permission sets, and agent user configuration, not as a required Agent Builder component for defining agent behavior.

Answer

Data integration with external systems

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Security settings for user permissions

Question 15

An administrator is setting up Einstein Forecasting. Which TWO statements accurately describe this feature?

Accepted Answer

It generates AI-based predictions that complement manager rollups.. Option B is correct because Einstein Forecasting produces AI-driven predictive forecasts that supplement, rather than replace, the manager's manual rollup of the pipeline, giving leadership an additional data-backed view. Option E is correct because the feature is designed to surface the AI-generated forecast alongside the rep's commit, enabling managers to compare the two and spot gaps or over-optimism. Option A is wrong because Einstein Forecasting does not strictly require a minimum sales history to function; it can generate predictions using available opportunity and pipeline data. Option C is wrong because the feature does not automatically change or override rep commitments — it only predicts and displays them for comparison. Option D is wrong because Einstein Forecasting is included with Einstein Sales Analytics/CRM Analytics entitlements rather than sold as a separate per-user license.

Answer

It only works for products with sufficient sales history.

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It automatically adjusts rep commitments based on historical data.

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It requires a separate Einstein Forecasting license per user.