SALESFORCE AGENTFORCE-SPECIALIST EXAM QUESTION | VALID DUMPS AGENTFORCE-SPECIALIST SHEET

Salesforce Agentforce-Specialist Exam Question | Valid Dumps Agentforce-Specialist Sheet

Salesforce Agentforce-Specialist Exam Question | Valid Dumps Agentforce-Specialist Sheet

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Salesforce Certified Agentforce Specialist Sample Questions (Q119-Q124):

NEW QUESTION # 119
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

Answer: C

Explanation:
The key reason for implementingEinstein Copilotis its ability tostreamline workflowsandautomate 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.
SalesforceAgentforce SpecialistReferences:More details can be found in the Salesforce documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_copilot_overview.htm


NEW QUESTION # 120
Universal Containers (UC) is Implementing Service AI Grounding to enhance its customer service operations.
UC wants to ensure that its AI- generated responses are grounded in the most relevant data sources. The team needs to configure the system to include all supported objects for grounding.
Which objects should UC select to configure Service AI Grounding?

  • A. Case, Knowledge, and Case Notes
  • B. Case, Case Emails, and Knowledge
  • C. Case and Knowledge

Answer: C

Explanation:
Universal Containers (UC) is implementing Service AI Grounding to enhance its customer service operations.
They aim to ensure that AI-generated responses are grounded in the most relevant data sources and need to configure the system to include all supported objects for grounding.
Supported Objects for Service AI Grounding:
* Case
* Knowledge
* Case Object:
* Role in Grounding:Provides contextual data about customer inquiries, including case details, status, and history.
* Benefit:Grounding AI responses in case data ensures that the information provided is relevant to the specific customer issue being addressed.
* Knowledge Object:
* Role in Grounding:Contains articles and documentation that offer solutions and information related to common issues.
* Benefit:Utilizing Knowledge articles helps the AI provide accurate and helpful responses based on verified information.
* Exclusion of Other Objects:
* Case Notes and Case Emails:
* Not Supported for Grounding:While useful for internal reference, these objects are not included in the supported objects for Service AI Grounding.
* Reason:They may contain sensitive or unstructured data that is not suitable for AI grounding purposes.
Why Options A and C are Incorrect:
* Option A (Case, Knowledge, and Case Notes):
* Case Notes Not Supported:Case Notes are not among the supported objects for grounding in Service AI.
* Option C (Case, Case Emails, and Knowledge):
* Case Emails Not Supported:Case Emails are also not included in the list of supported objects for grounding.
References:
* SalesforceAgentforce SpecialistDocumentation -Service AI Grounding Configuration:Details the objects supported for grounding AI responses in Service Cloud.
* Salesforce Help -Implementing Service AI Grounding:Provides guidance on setting up grounding with Case and Knowledge objects.
* Salesforce Trailhead -Enhance Service with AI Grounding:Offers an interactive learning path on using AI grounding in service scenarios.


NEW QUESTION # 121
How does the AI Retriever function within Data Cloud?

  • A. It monitors and aggregates data quality metrics across various data pipelines to ensure only high- integrity data is used for strategic decision-making.
  • B. It automatically extracts and reformats raw data from diverse sources into standardized datasets for use in historical trend analysis and forecasting.
  • C. It performs contextual searches over an indexed repository to quickly fetch the most relevant documents, enabling grounding AI responses with trustworthy, verifiable information.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:The AI Retriever is a key component in Salesforce Data Cloud, designed to support AI-driven processes like Agentforce by retrieving relevant data. Let's evaluate each option based on its documented functionality.
* Option A: It performs contextual searches over an indexed repository to quickly fetch the most relevant documents, enabling grounding AI responses with trustworthy, verifiable information.
The AI Retriever in Data Cloud uses vector-based search technology to query an indexed repository (e.
g., documents, records, or ingested data) and retrieve the most relevant results based on context. It employs embeddings to match user queries or prompts with stored data, ensuring AI responses (e.g., in Agentforce prompt templates) are grounded in accurate, verifiable information from Data Cloud. This enhances trustworthiness by linking outputs to source data, making it the primary function of the AI Retriever. This aligns with Salesforce documentation and is the correct answer.
* Option B: It monitors and aggregates data quality metrics across various data pipelines to ensure only high-integrity data is used for strategic decision-making.Data quality monitoring is handled by other Data Cloud features, such as Data Quality Analysis or ingestion validation tools, not the AI Retriever. The Retriever's role is retrieval, not quality assessment or pipeline management. This option is incorrect as it misattributes functionality unrelated to the AI Retriever.
* Option C: It automatically extracts and reformats raw data from diverse sources into standardized datasets for use in historical trend analysis and forecasting.Data extraction and standardization are part of Data Cloud's ingestion and harmonization processes (e.g., via Data Streams or Data Lake), not the AI Retriever's function. The Retriever works with already-indexed data to fetch results, not to process or reformat raw data. This option is incorrect.
Why Option A is Correct:The AI Retriever's core purpose is to perform contextual searches over indexed data, enabling AI grounding with reliable information. This is critical for Agentforce agents to provide accurate responses, as outlined in Data Cloud and Agentforce documentation.
References:
* Salesforce Data Cloud Documentation: AI Retriever- Describes its role in contextual searches for grounding.
* Trailhead: Data Cloud for Agentforce- Explains how the AI Retriever fetches relevant data for AI responses.
* Salesforce Help: Grounding with Data Cloud- Confirms the Retriever's search functionality over indexed repositories.


NEW QUESTION # 122
An Agentforce at Universal Containers is working on a prompt template to generate personalized emails for product demonstration requests from customers. It is important for the Al-generated email to adhere strictly to the guidelines, using only associated opportunity information, and to encourage the recipient to take the desired action.
How should theAgentforce Specialistinclude these instructions on a new line in the prompt template?

  • A. Make sure merged fields are defined.
  • B. Use curly brackets {} to encapsulate instructions.
  • C. Surround them with triple quotes (""").

Answer: C

Explanation:
In Salesforce prompt templates, instructions that guide how the Large Language Model (LLM) should generate content (in this case, personalized emails) can be included by surrounding the instruction text with triple quotes ("""). This formatting ensures that the LLM adheres to the specific instructions while generating the email content.
The use oftriple quotesallows the AI to understand that the enclosed text is a directive for how to approach the task, such as limiting the content to associated opportunity information or encouraging a specific action from the recipient.
Refer toSalesforce Prompt Builder documentationfor detailed instructions on how to structure prompts for generative AI.


NEW QUESTION # 123
The sales team at a hotel resort would like to generate a guest summary about the guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page. Which AI capability should the team use?

  • A. Prompt Builder
  • B. Agent Builder
  • C. Model Builder

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:The hotel resort team needs an AI-generated guest summary with recommendations, displayed exclusively on the contact record page. Let's assess the options.
* Option A: Model BuilderModel Builder in Salesforce creates custom predictive AI models (e.g., for scoring or classification) using Data Cloud or Einstein Platform data. It's not designed for generating text summaries or embedding them on record pages, making it incorrect.
* Option B: Agent BuilderAgent Builder in Agentforce Studio creates autonomous AI agents for tasks like lead qualification or customer service. While agents can provide summaries, they operate in conversational interfaces (e.g., chat), not as static content on a record page. This doesn't meet the location-specific requirement, making it incorrect.
* Option C: Prompt BuilderEinstein Prompt Builder allows creation of prompt templates that generate text (e.g., summaries, recommendations) using Generative AI. The template can pull data from contact records (e.g., activity preferences) and be embedded as a Lightning component on the contact record page via a Flow or Lightning App Builder. This ensures the summary is available only where specified, meeting the team's needs perfectly and making it the correct answer.
Why Option C is Correct:Prompt Builder's ability to generate contextual summaries and integrate them into specific record pages via Lightning components aligns with the team's requirements, as supported by Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Prompt Builder > Embedding Prompts- Details placement on record pages.
* Trailhead: Build Prompt Templates in Agentforce- Covers summaries from object data.
* Salesforce Help: Customize Record Pages with AI- Confirms Prompt Builder integration.


NEW QUESTION # 124
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