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Question 1:
Universal Containers (UC) plans to send one of three different emails to its customers based on the customer‘s lifetime value score and their market segment.
Considering that UC are required to explain why an e-mail was selected, which AI model should UC use to achieve this?
A. Predictive model and generative model
B. Generative model
C. Predictive model
Answer: A
Explanation:
A. Predictive model and generative model .
A predictive model is needed to determine the customer‘s lifetime value score and market segment, which are the criteria for selecting the email. A generative model is then required to generate the email content and provide an explanation of why that specific email was chosen based on the customer‘s profile. Therefore, both models are necessary to meet UC‘s requirements.
B. Generative model
While a generative model can create the email content and explanations, it cannot determine the customer‘s lifetime value score or market segment. A predictive model is required for that.
C. Predictive model
A predictive model can determine the customer‘s lifetime value score and market segment, but it cannot generate the email content or explain why a specific email was chosen. A generative model is needed for that part of the process.
Question 2:
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing autolaunched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should an AI Specialist apply the power of conversational AI to this use case?
A. Create a Flex prompt template in Prompt Builder.
B. Create a custom copilot action which calls a flow,
C. Configure the Integration Flow Standard Action in Einstein Copilot.
Answer: B
Explanation:
B. Create a custom copilot action which calls a flow. .
Creating a custom copilot action that calls the existing autolaunched flow is the most appropriate solution. This approach allows service agents to use natural language to trigger the flow and retrieve the fulfillment status from Oracle ERP. The flow handles the integration and data retrieval, while the copilot action provides the conversational interface.
A. Create a Flex prompt template in Prompt Builder.
Flex prompt templates are designed for generating text based on data, not for triggering actions or querying external systems. While they can include data from external systems, they are not the correct mechanism to call an existing flow that queries Oracle ERP.
C. Configure the Integration Flow Standard Action in Einstein Copilot.
While Einstein Copilot has standard actions, “Integration Flow Standard Action“ is not a standard, recognized action within Einstein Copilot. The correct approach is to create a custom copilot action that specifically calls the existing flow, which is the proper way to integrate with existing flows.
Question 3:
Universal Containers (UC) wants to offer personalized service experiences and reduce agent handling time with Al-generated email responses, grounded in Knowledge base.
Which Al capability should UC use?
A. Einstein Email Replies
B. Einstein Service Replies for Email
C. Einstein Generative Service Replies for Email
Answer: B
Explanation:
B. Einstein Service Replies for Email .
Einstein Service Replies for Email is designed to generate AI-powered email responses grounded in knowledge base articles. This capability directly addresses the requirement of offering personalized service experiences and reducing agent handling time by providing relevant, context-aware replies.
A. Einstein Email Replies
While “Einstein Email Replies“ might sound plausible, the precise and correct terminology for this specific capability within the Salesforce ecosystem, especially when tied to knowledge bases within service cloud, is “Einstein Service Replies for Email.“ Therefore, this option is not the most accurate.
C. Einstein Generative Service Replies for Email
This option is a slightly modified version of the correct answer, but it is not the officially named and supported capability. While the term “generative“ is accurate in describing the AI‘s functionality, “Einstein Service Replies for Email“ is the standard product name. Therefore, this option is incorrect in the context of the exam.
Question 4:
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.
Answer: B
Explanation:
B. The Prompt Template Manager permission set was not assigned correctly. .
To create and manage prompt templates in Prompt Builder, the AI Specialist needs the Prompt Template Manager permission set. Without this permission, they will not have access to Prompt Builder in the Setup menu.
A. The Prompt Template User permission set was not assigned correctly.
The Prompt Template User permission set only allows users to use prompt templates, not create or manage them. The AI Specialist needs the Prompt Template Manager permission set for creating templates.
C. The large language model (LLM) was not configured correctly in Data Cloud.
While LLM configuration in Data Cloud is essential for generative AI functionality, it does not directly affect access to Prompt Builder in the Setup menu. The Prompt Template Manager permission set is specifically required for accessing and using Prompt Builder.
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
Answer: A
Explanation:
A. Service Replies and Case Summaries .
Service Replies and Case Summaries are specifically designed to enhance service center productivity. Service Replies provide AI-generated responses based on Knowledge articles, while Case Summaries offer concise overviews of case records, both of which improve agent efficiency and reduce handling time.
B. Service Replies and Work Summaries
While Service Replies is a valid feature, “Work Summaries“ is not a standard Einstein Generative AI feature. Case Summaries are the correct feature for summarizing case records in a service context.
C. Reply Recommendations and Sales Summaries
Reply Recommendations might be a feature, but it is not the correct terminology, and the function is best described as Service Replies. Sales Summaries are not relevant to service center operations. They are designed for sales-related data. Therefore, this option is incorrect within the service center context.
For a full set of 639 questions. Go to
https://skillcertpro.com/product/salesforce-certified-agentforce-specialist-exam-questions/
SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
SkillCertPro updates exam questions every 2 weeks.
You will get life time access and life time free updates
SkillCertPro assures 100% pass guarantee in first attempt.
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
Answer: C
Explanation:
C. Einstein Work Summaries .
Einstein Work Summaries are specifically designed to provide concise summaries of work items, including support cases. This feature allows new support reps to quickly understand the details of a case without having to read through all the comments, improving their efficiency and reducing onboarding time.
A. Einstein Copilot
While Einstein Copilot can assist with various tasks, it is not specifically designed for summarizing case details in the same way as Einstein Work Summaries. Copilot is a more general-purpose AI assistant.
B. Einstein Sales Summaries
Einstein Sales Summaries are designed for summarizing sales-related data, such as opportunities and accounts. They are not relevant to support cases and would not provide the necessary information for new support reps. Therefore, this option is incorrect.
Question 7:
An AI Specialist is considering using a Fleld 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
Answer: C
Explanation:
C. That the Lightning page layout where the field will reside has been upgraded to Dynamic Forms .
Field Generation prompt templates require the field to be on a Lightning page layout that has been upgraded to Dynamic Forms. This allows for the dynamic generation of field content using generative AI.
A. That the field chosen must be a rich text field with 255 characters or more.
While rich text fields can be used with Field Generation prompts, it is not a requirement. Other text-based field types can also be used. Also, 255 charactors is not a requirement. The dynamic forms requirement is the core part of this answer.
B. That the org is set to API version 59 or higher.
While API versions are important for Salesforce functionality, they are not directly related to the requirement for Field Generation prompt templates. Dynamic Forms on the Lightning page layout is the essential requirement. Therefore, this option is incorrect in this context.
Question 8:
Universal Containers plans to enhance the customer support team‘s productivity using AI. Which specific use case necessitates the use of Prompt Builder?
A. Creating a draft of a support bulletin post for new product patches
B. Creating an Al-generated customer support agent performance score
C. Estimating support ticket volume based on historical data and seasonal trends
Answer: A
Explanation:
A. Creating a draft of a support bulletin post for new product patches .
Prompt Builder is specifically designed for generating textual content based on prompts. Creating a draft of a support bulletin post requires the generation of human-readable text, making Prompt Builder the appropriate tool.
B. Creating an AI-generated customer support agent performance score
Generating a performance score involves analyzing data and calculating a metric, which is typically done using reporting and analytics tools or predictive models, not Prompt Builder. Prompt Builder is for generating text.
C. Estimating support ticket volume based on historical data and seasonal trends
Estimating support ticket volume involves statistical analysis and forecasting, which are typically done using predictive analytics or forecasting tools, not Prompt Builder. Prompt Builder is for generating text, not statistical calculations.
Question 9:
What is best practice when refining Einstein Copilot custom action instructions?
A. Provide examples of user messages that are expected to trigger the action.
B. Use consistent introductory phrases and verbs across multiple action instructions.
C. Specify the persona who will request the action.
Answer: A
Explanation:
A. Provide examples of user messages that are expected to trigger the action. .
Providing examples of user messages that should trigger the custom action is a best practice. This helps the LLM understand the intent behind user requests and accurately determine when to invoke the action. Clear examples improve the reliability and accuracy of the action triggering.
B. Use consistent introductory phrases and verbs across multiple action instructions.
While consistency is generally good in UI design, it is not a primary best practice for refining Einstein Copilot custom action instructions. The focus should be on clear examples and context, not just consistent phrasing.
C. Specify the persona who will request the action.
While specifying the persona might add some context, it is not the most critical or effective practice for refining action instructions. Examples of user messages are far more effective in guiding the LLM to trigger the action correctly. Also, copilot should be able to work with different personas, making this option less flexible.
Question 10:
An AI Specialist configured Data Masking within the Einstein Trust Layer. How should the AI Specialist begin validating that the correct fields are being masked?
A. Use a Flow-based resource in Prompt Builder to debug the fields merge values using Flow Debugger.
B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
C. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
Answer: C
Explanation:
C. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page. .
Enabling the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page is the correct first step. This allows the AI Specialist to review the audit logs and verify which fields are being masked. These audit logs provide the necessary information to validate the data masking configuration.
A. Use a Flow-based resource in Prompt Builder to debug the fields merge values using Flow Debugger.
While Flow Debugger is a useful tool, it‘s not the correct method for validating data masking within the Einstein Trust Layer. Flow Debugger is used for debugging flows, not for auditing data masking. It also wouldn‘t show the data as it passes through the trust layer.
B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
The Einstein Generative AI Audit Data is not directly requested from the Security section of the Setup menu. It‘s configured and accessed through the Einstein Feedback setup page. While security is involved, the correct setup location is the Einstein feedback page.
For a full set of 639 questions. Go to
https://skillcertpro.com/product/salesforce-certified-agentforce-specialist-exam-questions/
SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
SkillCertPro updates exam questions every 2 weeks.
You will get life time access and life time free updates
SkillCertPro assures 100% pass guarantee in first attempt.