Quiz 2026 Salesforce AI-201: Salesforce Certified Agentforce Specialist First-grade Test Registration

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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Governance & Observability	10%	- AI governance 1. Trust layer and compliance concepts 2. Monitoring agent behavior
AI Agents	35%	- Agent behavior configuration 1. Agent reasoning engine concepts 2. Filters and variables for deterministic behavior - Agent setup and orchestration 1. Standard and custom topics 2. Standard and custom agent actions
Testing, Deployment & Lifecycle	15%	- Agent lifecycle management 1. Testing and validation strategies 2. Sandbox to production deployment
Data Cloud & Grounding	20%	- Data integration for AI agents 1. Connecting external data sources 2. Using Data Cloud for retrieval augmentation
Prompt Engineering	20%	- Grounding techniques 1. Data grounding for reducing hallucinations 2. Best practices for prompt design - Prompt Builder usage 1. Field generation and flex templates 2. Prompt templates and configuration

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Salesforce Certified Agentforce Specialist Sample Questions (Q87-Q92):

NEW QUESTION # 87
Universal Containers (UC) needs to improve the agent productivity in replying to customer chats.
Which generative AI feature should help UC address this issue?

A. Case Escalation
B. Service Replies
C. Case Summaries

Answer: B

Explanation:
Service Replies: This generative AI feature automates and assists in generating accurate, contextual, and efficient replies for customer service agents. It uses past interactions, case data, and the context of the conversation to provide draft responses, thereby enhancing productivity and reducing response times.
Case Summaries: Summarizes case information but does not assist directly in replying to customer chats.
Case Escalation: Refers to moving cases to higher-level support teams but does not address the need to improve chat response productivity.
Thus, Service Replies is the best feature for this requirement as it directly aligns with improving agent efficiency in replying to chats.

NEW QUESTION # 88
Universal Containers deploys a new Agentforce Service Agent into the company's website but is getting feedback that the Service Agent is not providing answers to customer questions that are found in the company's Salesforce Knowledge articles. What is the likely issue?

A. The Agentforce Service Agent user was not given the Allow View Knowledge permission set.
B. The Agentforce Service Agent user needs to be created under the standard Agent Knowledge profile.
C. The Agentforce Service Agent user is not assigned the correct Agent Type License.

Answer: A

Explanation:
According to the AgentForce Knowledge Integration and Access Configuration Guide, a Service Agent retrieves and grounds its responses using data from Salesforce Knowledge when the correct permissions are assigned. If customers report that the agent cannot access or provide answers from Knowledge articles, the most common root cause is that the AgentForce Service Agent user lacks the "Allow View Knowledge" permission.
This permission enables the agent to retrieve and read published articles from Salesforce Knowledge for grounding responses. Without it, the agent cannot access the content repository, resulting in incomplete or generic answers.

NEW QUESTION # 89
Universal Containers' data science team is hosting a generative large language model (LLM) on Amazon Web Services (AWS). What should the team use to access externally-hosted models in the Salesforce Platform?

A. Model Builder
B. Copilot Builder
C. App Builder

Answer: A

Explanation:
To access externally-hosted models, such as a large language model (LLM) hosted on AWS, the Model Builder in Salesforce is the appropriate tool. Model Builder allows teams to integrate and deploy external AI models into the Salesforce platform, making it possible to leverage models hosted outside of Salesforce infrastructure while still benefiting from the platform's native AI capabilities.

NEW QUESTION # 90
Universal Containers (UC) is rolling out an AI-powered support assistant to help customer service agents quickly retrieve relevant troubleshooting steps and policy guidelines. The assistant relies on a search index in Data Cloud that contains product manuals, policy documents, and past case resolutions. During testing, UC notices that agents are receiving too many irrelevant results from older product versions that no longer apply. How should UC address this issue?

A. Modify the search index to only store documents from the last year and remove older records.
B. Create a custom retriever in Einstein Studio, and apply filters for publication date and product line.
C. Use the default retriever, as it already searches the entire search index and provides broad coverage.

Answer: C

Explanation:
UC's support assistant uses a Data Cloud search index for grounding, but irrelevant results from outdated product versions are an issue.

NEW QUESTION # 91
Universal Containers, dealing with a high volume of chat inquiries, implements Einstein Work Summaries to boost productivity. After an agent-customer conversation, which additional information does Einstein generate and fill, apart from the "summary"'

A. Sentiment Analysis and Emotion Detection
B. Issue and Revolution
C. Draft Survey Request Email

Answer: B

Explanation:
Einstein Work Summaries automatically generate concise summaries of customer interactions (e.g., chat transcripts). Beyond the "summary" field, it extracts and populates Issue (key problem discussed) and Resolution (action taken to resolve the issue). These fields help agents and upervisors quickly grasp the conversation's context without reviewing the full transcript.

NEW QUESTION # 92
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