Salesforce AI-201 Study Group | AI-201 Passguide

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Salesforce Certified Agentforce Specialist Sample Questions (Q293-Q298):

NEW QUESTION # 293
A sales manager needs to contact leads at scale with hyper-relevant solutions and customized communications in the most efficient manner possible. Which Salesforce solution best suits this need?

Answer: B

Explanation:
The question specifies a sales manager's need to:
Contact leads at scale: Handle a large volume of leads simultaneously.
Hyper-relevant solutions: Deliver tailored solutions based on lead-specific data (e.g., CRM data, behavior).
Customized communications: Personalize outreach (e.g., emails, messages) for each lead.
Most efficient manner possible: Minimize manual effort and maximize automation.
This suggests a solution that leverages AI for personalization and automation for scale, ideally within the Salesforce ecosystem.


NEW QUESTION # 294
Universal Containers has grounded a prompt template with a related list. During user acceptance testing (UAT), users are not getting the correct responses. What is causing this issue?

Answer: A

Explanation:
UC has grounded a prompt template with a related list, but the responses are incorrect during UAT. Grounding with related lists in Agentforce allows the AI to access data from child records linked to a parent object.


NEW QUESTION # 295
A data science team has trained an XGBoost classification model for product recommendations on Databricks. The Agentforce Specialist is tasked with bringing inferences for product recommendations from this model into Data Cloud as a stand-alone data model object (DMO).
How should the Agentforce Specialist set this up?

Answer: B

Explanation:
To integrate inferences from an XGBoost model into Salesforce's Data Cloud as a stand-alone Data Model Object (DMO):
Create the Serving Endpoint in Databricks:
The serving endpoint is necessary to make the trained model available for real-time inference.
Databricks provides tools to host and expose the model via an endpoint.
Configure the Model Using Model Builder:
After creating the endpoint, the Agentforce Specialist should configure it within Einstein Studio's Model Builder, which integrates external endpoints with Salesforce Data Cloud for processing and storing inferences as DMOs.


NEW QUESTION # 296
A company wants to retrieve patient history details to augment the AI agent response and plans to use the Data Cloud search index feature. What is best practice when considering retrieval- augmented generation (RAG) for information that may contain personally identifiable information (PII)?

Answer: A


NEW QUESTION # 297
Universal Containers has PDF maintenance guides in an external folder, not yet in Salesforce.
The team wants a standard, clicks-only setup for the Service Agent to use these documents.
Which approach should the Agentforce Specialist implement?

Answer: C

Explanation:
According to the AgentForce Data Library and Retrieval Configuration Guide, when organizations have external PDF or text documents that need to be used by an AI agent, the recommended clicks-only approach is to upload the documents as a File Source in the AgentForce Data Library.
The system automatically processes the uploaded files, chunks their content, builds a Search Index, and allows you to create a retriever to ground agent responses from those indexed documents.
This method requires no code or manual integration and ensures that all document content becomes queryable through retrieval-augmented generation (RAG).


NEW QUESTION # 298
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