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Salesforce-AI-Specialist Practice Questions

Question # 1
Universal Containers (UC) is looking to enhance its operational efficiency. UC has recently adopted Salesforce and is considering implementing Einstein Copilot to improve its processes.
What is a key reason for implementing Einstein Copilot?
A. Improving data entry and data cleansing
B. Allowing AI to perform tasks without user interaction
C. Streamlining workflows and automating repetitive tasks


C. Streamlining workflows and automating repetitive tasks

Explanation: The key reason for implementing Einstein Copilot is its ability to streamline work flows and automate repetitive tasks. By leveraging AI, Einstein Copilot can assist users in handling mundane, repetitive processes, such as automatically generating insights, completing actions, and guiding users through complex processes, all of which significantly improve operational efficiency.
Option A(Improving data entry and cleansing) is not the primary purpose of Einstein Copilot, as its focus is on guiding and assisting users through workflows.
Option B(Allowing AI to perform tasks without user interaction) does not accurately describe the role of Einstein Copilot, which operates interactively to assist users in real time.

Question # 2
Universal Containers implements Custom Copilot Actions to enhance its customer service operations. The development team needs to understand the core components of a Custom Copilot Action to ensure proper configuration and functionality.
What should the development team review in the Custom Copilot Action configuration to identify one of the core components of a Custom Copilot Action?
A. Instructions
B. Output Types
C. Action Triggers


B. Output Types

Explanation: Universal Containers is enhancing its customer service operations with Custom Copilot Actions. The development team needs to understand the core components of a Custom Copilot Action to ensure proper configuration and functionality. One of these core components is the Output Types.
Core Components of a Custom Copilot Action:
Focus on Output Types:
Why Output Types are a Core Component:
Integration with Copilot:
Data Consistency:
User Experience:
Why Other Options are Less Suitable: Option A (Instructions):
Option C (Action Triggers):

Question # 3
Universal Containers wants support agents to use Agentforce to ask questions about its product tutorials and product guides.
What should the AI Specialist do to meet this requirement?
A. Create a prompt template for product tutorials and guides.
B. Add an Answer Questions custom field in the product object for tutorial instructions.
C. Publish product tutorials and guides as Knowledge articles.


C. Publish product tutorials and guides as Knowledge articles.


Question # 4
An AI Specialist is considering using a Field Generation prompt template type. What should the AI Specialist check before creating the Field Generation prompt to ensure it is possible for the field to be enabled for generative AI?
A. That the field chosen must be a rich text field with 255 characters or more.
B. That the org is set to API version 59 or higher
C. That the Lightning page layout where the field will reside has been upgraded to Dynamic Forms


B. That the org is set to API version 59 or higher

Explanation:

Before creating a Field Generation prompt template, the AI Specialist must ensure that the Salesforce org is set to API version 59 or higher. This version of the API introduces support for advanced generative AI features, such as enabling fields for generative AI outputs. This is a critical technical requirement for the Field Generation prompt template to function correctly.

Option A (rich text field requirement) is not necessary for generative AI functionality.

Option C (Dynamic Forms) does not impact the ability of a field to be generative AI-enabled, although it might enhance the user interface.

Question # 5
Universal Containers is evaluating Einstein Generative AI features to improve the productivity of the service center operation.
Which features should the AI Specialist recommend?
A. Service Replies and Case Summaries
B. Service Replies and Work Summaries
C. Reply Recommendations and Sales Summaries


A. Service Replies and Case Summaries

Explanation: To improve the productivity of the service center, the AI Specialist should recommend the Service Replies and Case Summaries features.
Service Replies helps agents by automatically generating suggested responses to customer inquiries, reducing response time and improving efficiency.
Case Summaries provide a quick overview of case details, allowing agents to get up to speed faster on customer issues.
Work Summaries are not as relevant for direct customer service operations, and Sales Summaries are focused on sales processes, not service center productivity.
For more information, see Salesforce's Einstein Service Cloud documentation on the use of generative AI to assist customer service teams.

Question # 6
Universal Containers (UC) has recently received an increased number of support cases. As a result, UC has hired more customer support reps and has started to assign some of the ongoing cases to newer reps. Which generative AI solution should the new support reps use to understand the details of a case without reading through each case comment?
A. Einstein Copilot
B. Einstein Sales Summaries
C. Einstein Work Summaries


C. Einstein Work Summaries

Explanation:

New customer support reps at Universal Containers can use Einstein Work Summaries to quickly understand the details of a case without reading through each case comment. Work Summaries leverage generative AI to provide a concise overview of ongoing cases, summarizing all relevant information in an easily digestible format.

Einstein Copilot can assist with a variety of tasks but is not specifically designed for summarizing case details.

Einstein Sales Summaries are focused on summarizing sales-related activities, which is not applicable for support cases.

For more details, refer to Salesforce documentation on Einstein Work Summaries.

Question # 7
Universal Containers (UC) wants to create a new Sales Email prompt template in Prompt Builder using the "Save As" function. However, UC notices that the new template produces different results compared to the standard Sales Email prompt due to missing hyperparameters.
What should UC do to ensure the new prompt template produces results comparable to the standard Sales Email prompts?
A. Use Model Playground to create a model configuration with the specified parameters.
B. Manually add the hyperparameters to the new template.
C. Revert to using the standard template without modifications.


B. Manually add the hyperparameters to the new template.

Explanation: WhenUniversal Containerscreates a new Sales Email prompt template using the"Save As"function, missing hyperparameters can result in different outputs. To ensure the new prompt produces comparable results to the standard Sales Email prompt, the AI Specialist shouldmanually add the necessary hyperparametersto the new template.
Hyperparameters likeTemperature,Frequency Penalty, andPresence Penaltydirectly affect how the AI generates responses. Ensuring that these are consistent with the standard template will result in similar outputs.
Option A (Model Playground)is not necessary here, as it focuses on fine-tuning models, not adjusting templates directly.
Option C (Reverting to the standard template)does not solve the issue of customizing the prompt template.
For more information, refer toPrompt Builder documentationon configuring hyperparameters in custom templates.

Question # 8
Universal Containers (UC) wants to enable its sales reps to explore opportunities that are similar to previously won opportunities by entering the utterance, "Show me other opportunities like this one." How should UC achieve this in Einstein Copilot?
A. Use the standard Copilot action.
B. Create a custom Copilot action calling a flow.
C. Create a custom Copilot action calling an Apex class.


A. Use the standard Copilot action.

Explanation:

Universal Containers can achieve the request to explore similar opportunities by using the standard Copilot action. Einstein Copilot has built-in actions to handle natural language queries, such as “Show me other opportunities like this one.” The standard action will process the query and return results based on predefined matching criteria like opportunity details and past Closed Won deals.

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