Salesforce SALESFORCE-AI-SPECIALIST Online Practice Questions and Exam Preparation

Salesforce SALESFORCE-AI-SPECIALIST Online Questions & Answers

• Question 151:

  Universal Containers is interested in using Call Explorer to quickly gain insights from meetings recorded by its sales team.

  What should the AI Specialist be aware of before enabling this feature?

  A. Call Explorer operates independently of Salesforce Knowledge, requiring no prior setup.
  B. Custom Call Explorer actions need to be built before it can be configured.
  C. Call Explorer requires the Einstein Conversation Insights permission set to be enabled.
  C. Call Explorer requires the Einstein Conversation Insights permission set to be enabled.

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  Explanation

  Before enabling Call Explorer, the Salesforce AI Specialist must ensure that the Einstein Conversation Insights permission set is assigned to users (Option C). Call Explorer is a feature within Einstein Conversation Insights (ECI) that analyzes

  meeting recordings to surface trends, keywords, and actionable insights.

  Key Considerations:

  Permission Set Requirement:

  Why Other Options Are Incorrect:

  References:

  Salesforce Einstein Conversation Insights Guide: Explicitly states that the Einstein Conversation Insights permission set is required to access Call Explorer. Trailhead Module: "Einstein Conversation Insights Basics" outlines permission

  prerequisites for enabling call analytics.

  Salesforce Help Documentation: Confirms that Call Explorer functionality is governed by ECI permissions.

• Question 152:

  Which Salesforce feature allows service agents to automatically generate summaries of case details?

  A. Case Summaries
  B. Prompt Builder
  C. Model Builder
  D. Einstein Copilot
  A. Case Summaries

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  Explanation

  Case Summaries automatically create overviews of case details, helping agents quickly understand the context.

• Question 153:

  Universal Containers wants to be able to detect with a high level confidence if content generated by a large language model (LLM) contains toxic language. Which action should an Al Specialist take in the Trust Layer to confirm toxicity is being appropriately managed?

  A. Access the Toxicity Detection log in Setup and export all entries where isToxicityDetected is true.
  B. Create a flow that sends an email to a specified address each time the toxicity score from the response exceeds a predefined threshold.
  C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores.
  C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores.

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  Explanation

  To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the AI Specialist should create a Trust Layer audit report within Data Cloud. By using the toxicity detector type filter, the report

  can display toxic responses along with their respective toxicity scores, allowing Universal Containers to monitor and manage any toxic content generated with a high level of confidence.

  Option C is correct because it enables visibility into toxic language detection within the Trust Layer and allows for auditing responses for toxicity. Option A suggests checking a toxicity detection log, but Salesforce provides more

  comprehensive options via the audit report.

  Option B involves creating a flow, which is unnecessary for toxicity detection monitoring.

  References:

  Salesforce Trust Layer Documentation:

  https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm

• Question 154:

  Universal Containers wants to reduce overall agent handling time minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields.

  Which combination of Einstein for Service features enables this effort?

  A. Einstein Service Replies and Work Summaries
  B. Einstein Reply Recommendations and Case Summaries
  C. Einstein Reply Recommendations and Case Classification
  C. Einstein Reply Recommendations and Case Classification

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  Explanation

  Universal Containers aims to reduce overall agent handling time by minimizing the time agents spend typing routine answers for common questions during chats and by reducing post-chat analysis through suggesting values for case fields. To achieve these objectives, the combination of Einstein Reply Recommendations and Case Classification is the most appropriate solution.

  1.Einstein Reply Recommendations:

  Purpose: Helps agents respond faster during live chats by suggesting the best responses based on historical chat data and common customer inquiries.

  Functionality:

  Benefit: Significantly reduces the time agents spend typing routine answers, thus improving efficiency and reducing handling time.

  2.Case Classification:

  Purpose: Automatically suggests or populates values for case fields based on historical data and patterns identified by AI.

  Functionality:

  Benefit: Reduces the time agents spend on post-chat analysis and data entry by automating the classification and field population process.

  Why Options A and B are Less Suitable:

  Option A (Einstein Service Replies and Work Summaries):

  Option B (Einstein Reply Recommendations and Case Summaries):

  References:

  Salesforce AI Specialist Documentation - Einstein Reply Recommendations:

  Salesforce AI Specialist Documentation - Einstein Case Classification:

  Salesforce Trailhead - Optimize Service with AI:

• Question 155:

  Universal Containers wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template.

  What should the AI Specialist recommend?

  A. Create a Flex template to add resources with standard and custom objects as inputs.
  B. Create a prompt template passing in a special custom object that connects the records temporarily,
  C. Create a prompt template-triggered flow to access the data from standard and custom objects.
  A. Create a Flex template to add resources with standard and custom objects as inputs.

  ---

  Explanation

  Universal Containers needs to generate a sales proposal using data from multiple unrelated standard and custom objects within a prompt template. The most effective way to achieve this is by using a Flex template. Flex templates in

  Salesforce allow AI specialists to create prompt templates that can accept inputs from multiple sources, including various standard and custom objects. This flexibility enables the direct use of data from unrelated objects without the need to

  create intermediary custom objects or complex flows.

  References:

  Salesforce AI Specialist Documentation - Flex Templates: Explains how Flex templates can be utilized to incorporate data from multiple sources, providing a flexible solution for complex data requirements in prompt templates.

• Question 156:

  Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses.

  Which solution should UC consider?

  A. fine-tune the Einstein AI model with CBM data.
  B. Build Al model with Einstein discovery and deploy to sales users.
  C. Enable Agentforce and deploy to sales users.
  A. fine-tune the Einstein AI model with CBM data.

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  Explanation

  Context of the Question: Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses. Why Fine-Tune an Einstein AI Model with CRM Data? Why Not Build an AI Model with Einstein Discovery (Option B)? Why Not Enable Agentforce (Option C)? Outcome: Fine-tuning the Einstein AI model with UC's CRM data (Answer A) is the most direct, Salesforce-native solution to provide generative AI responses that are aligned with UC's context, driving productivity gains and ensuring data privacy. Salesforce AI Specialist References and Documents Salesforce Official: Einstein GPT Overview Salesforce Trailhead: Get Started with Salesforce Einstein Salesforce Documentation: Einstein Discovery Salesforce AI Specialist Study Guide

• Question 157:

  Universal Containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, Competitor Analysis. All sales users have the same profile but one user cannot see the generative AlI-enabled field icon next to the summary field.

  What is the most likely cause of the issue?

  A. The user does not have the Prompt Template User permission set assigned.
  B. The prompt template associated with summary field is not activated for that user.
  C. The user does not have the field Generative AI User permission set assigned.
  C. The user does not have the field Generative AI User permission set assigned.

  ---

  Explanation

  In Salesforce, Generative AI capabilities are controlled by specific permission sets. To use features such as generating summaries with AI, users need to have the correct permission sets that allow access to these functionalities. Generative

  AI User Permission Set: This is a key permission set required to enable the generative AI capabilities for a user. In this case, the missing Generative AI User permission set prevents the user from seeing the generative AI-enabled field icon.

  Without this permission, the generative AI feature in the Competitor Analysis custom object won't be accessible. Why not A? The Prompt Template User permission set relates specifically to users who need access to prompt templates for

  interacting with Einstein GPT, but it's not directly related to the visibility of AI-enabled field icons. Why not B? While a prompt template might need to be activated, this is not the primary issue here. The question states that other users with the

  same profile can see the icon, so the problem is more likely to be permissions-based for this particular user.

  For more detailed information, you can review Salesforce documentation on permission sets related to AI capabilities at Salesforce AI Documentation and Einstein GPT permissioning guidelines.

• Question 158:

  A sales manager is using Agent Assistant to streamline their daily tasks. They ask the agent to Show me a list of my open opportunities.

  How does the large language model (LLM) in Agentforce identify and execute the action to show the sales manager a list of open opportunities?

  A. The LLM interprets the user's request, generates a plan by identifying the apcMopnete topics and actions, and executes the actions to retrieve and display the open opportunities
  B. The LLM uses a static set of rules to match the user's request with predefined topics and actions, bypassing the need for dynamic interpretation and planning.
  C. Using a dialog pattern. the LLM matches the user query to the available topic, action and steps then performs the steps for each action, such as retrieving a fast of open opportunities.
  A. The LLM interprets the user's request, generates a plan by identifying the apcMopnete topics and actions, and executes the actions to retrieve and display the open opportunities

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  Explanation

  Agentforce's LLM dynamically interprets natural language requests (e.g., "Show me open opportunities"), generates an execution plan using the planner service, and retrieves data via actions (e.g., querying Salesforce records). This contrasts

  with static rules (B) or rigid dialog patterns (C), which lack contextual adaptability. Salesforce documentation highlights the planner's role in converting intents into actionable steps while adhering to security and business logic.

  Salesforce Help Article: Agentforce Planner Service ("Dynamic Request Interpretation" section).

  Einstein AI Specialist Trailhead: "How Agentforce Processes User Requests."

• Question 159:

  An AI Specialist turned on Einstein Generative AI in Setup. Now, the AI Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu.

  What is causing the problem?

  A. The Prompt Template User permission set was not assigned correctly.
  B. The Prompt Template Manager permission set was not assigned correctly.
  C. The large language model (LLM) was not configured correctly in Data Cloud.
  B. The Prompt Template Manager permission set was not assigned correctly.

  ---

  Explanation

  In order to access and create custom prompt templates in Prompt Builder, the AI Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the

  Setup menu, even though Einstein Generative AI is enabled.

  Option B is correct because the Prompt Template Manager permission set is required to use Prompt Builder.

  Option A (Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them. Option C (LLM configuration in Data Cloud) is unrelated to the ability to access Prompt

  Builder.

  References:

  Salesforce Prompt Builder Permissions:

  https://help.salesforce.com/s/articleView?id=sf.prompt_builder_permissions.htm

• Question 160:

  Universal Containers (UC) wants to enable its sales team to use Al to suggest recommended products from its catalog.

  Which type of prompt template should UC use?

  A. Record summary prompt template
  B. Email generation prompt template
  C. Flex prompt template
  C. Flex prompt template

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  Explanation

  Universal Containers (UC) wants to enable its sales team to leverage AI to recommend products from its catalog. The best option for this use case is a Flex prompt template.

  A Flex prompt template is designed to provide flexible, customizable AI-driven recommendations or responses based on specific data points, such as product information, customer needs, or sales history. This template type allows the AI to

  consider various inputs and parameters, making it ideal for generating product recommendations dynamically.

  In contrast:

  A Record summary prompt template (Option A) is used to summarize data related to a specific record, such as generating a quick summary of a sales opportunity or account, but not for recommending products.

  An Email generation prompt template (Option B) is tailored for crafting email content and is not suitable for suggesting products based on a catalog. Given the need for dynamic recommendations that pull from a product catalog and potentially

  other sales data, the Flex prompt template is the correct approach.

  Salesforce

  References:

  Salesforce Prompt Templates Overview:

  https://help.salesforce.com/s/articleView?id=000391407andtype=1 Flex Prompt Template Usage: https://developer.salesforce.com/docs/atlas.en- us.salesforce_ai.meta/salesforce_ai/prompt_flex_template