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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Available Languages: | French, English, Japanese |
| Passing Score: | 72%-73% |
| Exam Price: | USD 200 |
| Related Certifications: | Salesforce AI Associate (retired) Salesforce AI Specialist (retired) Salesforce Platform Administrator Salesforce Platform App Builder |
| Exam Duration: | 105 minutes |
| Exam Format: | Multiple Choice, Multiple Select, Scenario-based Questions |
| Real Exam Qty: | 60 multiple-choice questions + up to 5 unscored questions |
| Recommended Training: | Salesforce Trailhead Agentforce Learning Paths Agentforce Specialist Exam Prep |
| Exam Registration: | Salesforce Certification Registration Certification Exam Guide |
| Sample Questions: | Salesforce Agentforce-Specialist Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | None |
| Official Syllabus URL: | https://help.salesforce.com/s/articleView?id=005298924&type=1 |
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NEW QUESTION # 274
Choose 1 option.
Universal Containers needs to create Data Cloud reports to understand agent behavior.
Which data lake object (DLO) represents an overarching container capturing contiguous interactions with one or more Al agents?
Answer: C
Explanation:
Per the AgentForce Data Cloud Integration Guide, the AI Agent Session (AIAGENTSESSION) object represents an overarching container that tracks a continuous interaction between one or more AI agents and a user. The document describes: "AI Agent Session is the parent container for a contiguous set of AI Agent interactions. It captures metadata, start and end times, and the relationship to individual messages exchanged during the session." Option A, AIAGENTINTERACTION, represents a single step or event within the session, while AIAGENTINTERACTIONMESSAGE (Option B) represents individual messages or exchanges within that interaction. Therefore, AIAGENTSESSION is the correct DLO for reporting on broader agent behavior and performance across an entire engagement.
References (AgentForce Documents / Study Guide):
AgentForce Data Cloud Reporting Guide: "Understanding Agent DLO Hierarchy" AgentForce Study Notes: "AI Agent Session, Interaction, and Message Object Relationships" Salesforce Data Cloud for AI Agents: "AI Agent Session Overview"
NEW QUESTION # 275
Universal Containers wants to reduce overall customer support handling time by minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields. Which combination of Agentforce for Service features enables this effort?
Answer: B
Explanation:
Universal Containers (UC) aims to streamline customer support by addressing two goals: reducing in-chat typing time for routine answers and minimizing post-chat analysis by auto-suggesting case field values. In Salesforce Agentforce for Service, Einstein Reply Recommendations and Case Classification (Option A) are the ideal combination to achieve this.
Einstein Reply Recommendations: This feature uses AI to suggest pre-formulated responses based on chat context, historical data, and Knowledge articles. By providing agents with ready-to-use replies for common questions, it significantly reduces the time spent typing routine answers, directly addressing UC's first goal.
Case Classification: This capability leverages AI to analyze case details (e.g., chat transcripts) and suggest values for case fields (e.g., Subject, Priority, Resolution) during or after the interaction. By automating field population, it reduces post-chat analysis time, fulfilling UC's second goal.
Option B: While "Einstein Reply Recommendations" is correct for the first part, "Case Summaries" generates a summary of the case rather than suggesting specific field values. Summaries are useful for documentation but don't directly reduce post-chat field entry time.
Option C: "Einstein Service Replies" is not a distinct, documented feature in Agentforce (possibly a distractor for Reply Recommendations), and "Work Summaries" applies more to summarizing work orders or broader tasks, not case field suggestions in a chat context.
Option A: This combination precisely targets both in-chat efficiency (Reply Recommendations) and post-chat automation (Case Classification).
Thus, Option A is the correct answer for UC's needs.
Salesforce Agentforce Documentation: "Einstein Reply Recommendations" (Salesforce Help: https://help.
salesforce.com/s/articleView?id=sf.einstein_reply_recommendations.htm&type=5) Salesforce Agentforce Documentation: "Case Classification" (Salesforce Help: https://help.salesforce.com/s
/articleView?id=sf.case_classification.htm&type=5)
Trailhead: "Agentforce for Service" (https://trailhead.salesforce.com/content/learn/modules/agentforce-for- service)
NEW QUESTION # 276
A company needs to ensure customers always receive answers based on the most current version of support documentation.
What should an Agentforce Specialist recommend?
Answer: C
Explanation:
The correct answer is B because Salesforce Knowledge is the correct source when the business requirement depends on governed support documentation, publishing state, and current article versions. A knowledge-based Agentforce Data Library uses Knowledge as the managed content source, allowing the agent to ground responses in approved Knowledge content instead of static uploaded files.
Option A is wrong because a file-based library does not provide the same native Knowledge publishing and version governance; uploaded documents can become stale unless actively maintained. Option C is wrong because the two library types are not equivalent for content lifecycle management. Salesforce guidance for Knowledge-based libraries and service grounding emphasizes using published Knowledge content and data category or library configuration to control what the agent can search and use.
NEW QUESTION # 277
A Service Agent at Universal Containers (UC) is designed to help customers resolve issues by searching against knowledge articles.
Knowledge articles have PDF attachments that add critical details. UC reports that the agent provides excellent summaries of the knowledge articles, but seems completely unaware of the PDF attachments.
How should an Agentforce Specialist configure the Data Cloud search index to include the content of these attached files?
Answer: C
Explanation:
The AgentForce Data Cloud Indexing Guide clearly states that to include content from attached files such as PDFs in Knowledge articles, the correct configuration is to enable "Include Attachments" and map the ContentDocumentVersion unstructured data model object (UDMO). The documentation specifies:
"When indexing Knowledge or Case data, enabling the 'Include Attachments' option allows the Data Cloud index to extract and embed content from linked ContentDocumentVersion records, ensuring the agent retrieves relevant information from attachments." Option A (increasing chunk size) does not enable attachment ingestion. Option B (ContentDocumentLink mapping) only establishes a relationship, not content extraction. Therefore, Option C ensures attachment content becomes searchable within AgentForce retrieval.
References (AgentForce Documents / Study Guide):
* AgentForce Data Cloud Indexing and Retrieval Guide: "Including Attachments in Knowledge Indexes"
* AgentForce Implementation Handbook: "Mapping UDMO for ContentDocumentVersion"
* AgentForce Study Guide: "Attachment Content Inclusion for Knowledge Articles"
NEW QUESTION # 278
Choose 1 option.
Universal Containers (UC) is preparing to use the Agentforce Testing Center to ensure the reliability of a new agent. UC has a CSV file with test cases and is reviewing the documentation to understand best practices and limitations.
Which best practice should the company follow to avoid modifying CRM data while running tests in the Testing Center?
Answer: A
Explanation:
According to the AgentForce Testing and Validation Guidelines, all automated or large-scale test runs in Testing Center should be executed in a sandbox environment to prevent any unintended modifications to live CRM data.
Running tests in production can trigger record updates, create cases, or call actions that alter live data, violating best practice standards for safe validation. Testing in a sandbox ensures the environment mirrors production logic while maintaining data isolation.
Option A contradicts this best practice, as production testing risks data integrity. Option B does not prevent data changes - limiting test volume does not safeguard against unintended record modifications.
Therefore, the correct approach is Option C - Use the Testing Center only in the sandbox environment to maintain data safety and compliance.
Reference: AgentForce Testing Center Documentation - "Running Safe and Isolated Tests in Sandbox Environments."
NEW QUESTION # 279
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