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Salesforce Certified Agentforce Specialist Sample Questions (Q138-Q143):

NEW QUESTION # 138
After a successful implementation of Agentforce Sates Agent with sales users. Universal Containers now aims to deploy it to the service team.
Which key consideration should theAgentforce Specialistkeep in mind for this deployment?

A. Assign the Agentforce for Service permission to the Service Cloud users.
B. Assign the standard service actions to Agentforce Service Agent.
C. Review and test standard and custom Agent topics and actions for Service Center use cases.

Answer: C

Explanation:
When deploying Einstein Agent (formerly Agentforce) from Sales to Service Cloud:
* Agent Topics and Actions are context-specific. Service Cloud use cases (e.g., case resolution, knowledge retrieval) require validation of existing topics/actions to ensure alignment with service workflows.
* Option A: Permissions like "Agentforce for Service" are necessary but secondary to functional compatibility.
* Option B: Standard service actions must be mapped to Agentforce, but testing ensures they function as intended.
References:
* Salesforce Help: Einstein Agent Setup
* Emphasizes reviewing "topics and actions for different user groups (Sales vs. Service)."

NEW QUESTION # 139
Universal Containers would like to route a service agent conversation to a human agent queue. Which tool connects the service agent to the human agent queue for escalation?

A. Screen Flow
B. Outbound Omni-Channel Flow
C. Prompt Flow

Answer: B

Explanation:
Why is Outbound Omni-Channel Flow the Correct Answer?
In Agentforce, when a service agent's conversation needs to be escalated to a human agent queue, Outbound Omni-Channel Flow is the appropriate tool to facilitate this process.
Key Features of Outbound Omni-Channel Flow in Agentforce:
* Automates Escalation to a Human Agent Queue
* It ensures that service requests are dynamically routed to the most appropriate human agent, based on availability, skills, and predefined business logic.
* Seamless Transition from AI to Human Agents
* When Einstein Copilot or another AI-powered assistant identifies a case that requires human intervention, Omni-Channel Flow automatically routes the conversation.
* Ensures Proper Prioritization & Load Balancing
* By leveraging Omni-Channel routing rules, the system assigns conversations efficiently, avoiding delays in customer service.
* Integration with Agentforce and Service Cloud
* Works directly with Salesforce Service Cloud to route cases to the appropriate agent queue.
Why Not the Other Options?
# B. Screen Flow
* Screen Flow is used for interactive guided processes where users manually enter data in predefined steps.
* It does not support automated case routing to human agents in real time.
# C. Prompt Flow
* Prompt Flow is designed to enhance AI-generated responses and workflows rather than routing service agent interactions to human agents.
* It lacks Omni-Channel integration, which is necessary for real-time queue management.
Agentforce Specialist References
The importance of using Omni-Channel Flow for routing AI-generated interactions to human agents is supported in the Agentforce Specialist exam objectives and documentation:
* Salesforce AI Specialist Material: Covers the importance of Omni-Channel routing for managing AI and human agent interactions.
* Salesforce Instructions for the Certification: Mentions routing AI-driven cases to human agents using automated flows.
* Agentforce Tools Documentation: Highlights Omni-Channel capabilities in Service AI.

NEW QUESTION # 140
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?

A. Enable data masking for sandbox refreshes.
B. Add new data masking rules in LLM setup.
C. Configure data masking in the Einstein Trust Layer setup.

Answer: C

Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, theAgentforce Specialistshould configure thedata maskingrules within theEinstein Trust Layer.
TheEinstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
SalesforceAgentforce SpecialistReferences:For more information, refer to:https://help.salesforce.com/s
/articleView?id=sf.einstein_trust_layer_data_masking.htm

NEW QUESTION # 141
What is the importance of Action Instructions when creating a custom Agent action?

A. Action Instructions tell the user how to call this action in a conversation.
B. Action Instructions tell the large language model (LLM) which action to use.
C. Action Instructions define the expected user experience of an action.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Salesforce Agentforce, custom Agent actions are designed to enable AI-driven agents to perform specific tasks within a conversational context.Action Instructionsare a critical component when creating these actions because they define the expected user experience by outlining how the action should behave, what it should accomplish, and how it interacts with the end user. These instructions act as a blueprint for the action's functionality, ensuring that it aligns with the intended outcome and provides a consistent, intuitive experience for users interacting with the agent. For example, if the action is to "schedule a meeting," the Action Instructions might specify the steps (e.g., gather date and time, confirm with the user) and the tone (e.g., professional, concise), shaping the user experience.
* Option B: While Action Instructions might indirectly influence how a user invokes an action (e.g., by making it clear what inputs are needed), they are not primarily about telling the user how to call the action in a conversation. That's more related to user training or interface design, not the instructions themselves.
* Option C: The large language model (LLM) relies on prompts, parameters, and grounding data to determine which action to execute, not the Action Instructions directly. The instructions guide the action's design, not the LLM's decision-making process at runtime.
Thus, Option A is correct as it emphasizes the role of Action Instructions in defining the user experience, which is foundational to creating effective custom Agent actions in Agentforce.
References:
* Salesforce Agentforce Documentation: "Create Custom Agent Actions" (Salesforce Help:https://help.
salesforce.com/s/articleView?id=sf.agentforce_custom_actions.htm&type=5)
* Trailhead: "Agentforce Basics" module (https://trailhead.salesforce.com/content/learn/modules
/agentforce-basics)

NEW QUESTION # 142
An Agentforce configured Data Masking within the Einstein Trust Layer.
How should theAgentforce Specialistbegin validating that the correct fields are being masked?

A. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
B. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.
C. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.

Answer: A

Explanation:
To begin validating that the correct fields are being masked inEinstein Trust Layer, theAgentforce Specialistshould request theEinstein Generative AI Audit Datafrom theSecurity sectionof the Salesforce Setup menu. This audit data allows theAgentforce Specialistto see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected.
* Option Bis correct because it allows for the retrieval of audit data that can be used to validate data masking.
* Option A(Flow Debugger) andOption C(Einstein Feedback) do not relate to validating field masking in the context of theEinstein Trust Layer.
References:
* Salesforce Einstein Trust Layer Documentation:https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_audit.htm

NEW QUESTION # 143
......

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