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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Exam Duration: | 105 minutes |
| Real Exam Qty: | 60-65 |
| Exam Format: | Multiple Choice, Multiple Select, Scenario-Based |
| Related Certifications: | Salesforce Certified AI Specialist |
| Available Languages: | English |
| Certificate Validity Period: | 1 year (requires annual maintenance) |
| Passing Score: | 73% |
| Exam Price: | $200 USD |
| Recommended Training: | Trailhead Agentforce Specialist Certification Prep |
| Exam Registration: | Salesforce Certification Registration Pearson VUE Scheduling |
| Sample Questions: | Salesforce Agentforce-Specialist Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended: 6 months experience with Agentforce or Salesforce AI features |
| Official Syllabus URL: | https://trailhead.salesforce.com/credentials/certification-detail-print/?certificationId=286 |
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NEW QUESTION # 199
The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history.
Why should the team use Agent as the solution?
Answer: B
Explanation:
Agentis designed to assist in generating personalized, AI-driven content based on customer data such as behavior, preferences, and purchase history. For the marketing team atUniversal Containers, this is the perfect solution to create dynamic and relevant email content. By leveragingAgent, they can ensure that each customer receives tailored communications, improving engagement and conversion rates.
* Option Ais correct asAgenthelps generate real-time, personalized content based on comprehensive data about the customer.
* Option Brefers more to Einstein Analytics or
* Marketing Cloud Intelligence, andOption Cdeals with automation, which isn't the primary focus of Agent.
:
Salesforce Agent Overview:https://help.salesforce.com/s/articleView?id=einstein_copilot_overview.htm
NEW QUESTION # 200
What is the main purpose of Prompt Builder?
Answer: A
Explanation:
Prompt Builderis designed to help organizations create and configure reusable prompts for large language models (LLMs). By integratinggenerative AIresponses into workflows,Prompt Builderenables customization of AI prompts that interact with Salesforce data and automate complex processes. This tool is especially useful for creating tailored and consistent AI-generated content in various business contexts, including customer service and sales.
* It is not a tool forApex programming(as in option A).
* It is also not limited to real-time suggestions as mentioned in option C. Instead, it provides a flexible way for companies to manage and customize how AI-driven responses are generated and used in their workflows.
References:
* Salesforce Prompt Builder Overview:https://help.salesforce.com/s/articleView?id=sf.prompt_builder.
htm
NEW QUESTION # 201
When a verified customer in a help center says, "I want to upgrade my service plan," an AI agent needs to complete the following tasks:
* Verify identity and entitlement.
* Create a new quote.
* Calculate a prorated upgrade amount.
* Escalate to an Account Executive (AE) only if the reorder exceeds USD 25,000.
Which type of agent should an AgentForce Specialist build to support this use case?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the AgentForce Specialist Implementation Guide and Agent Type Configuration Reference, this scenario represents a revenue-generating interaction where the AI agent is directly handling an upsell process. The tasks include verifying the customer's entitlement, generating a new quote, and calculating a prorated amount - all of which align with the Sales Agent configuration type in AgentForce.
The Sales Agent is specifically designed to manage lead conversion, quoting, upselling, renewals, and escalation logic for higher-value opportunities. AgentForce documentation emphasizes that when an interaction involves quote generation, pricing calculations, or escalations to an Account Executive for large deal handling, the correct design is a Sales Agent.
In contrast, a Service Agent (Option A) is primarily used for resolving support cases, troubleshooting, and service request management, not for handling quote creation or pricing. Similarly, an Employee Agent (Option C) focuses on internal coordination tasks like HR or finance workflows, not customer-facing sales activities.
Therefore, based on the defined use case and AgentForce best practices, the correct agent type to implement is Option B - Sales Agent, as it is optimized for handling sales-driven customer interactions, quote management, and escalation thresholds.
Reference: AgentForce Specialist Guide - "Configuring Sales Agents for Upsell and Quote Management."
NEW QUESTION # 202
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?
Answer: A
Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable 'Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable 'Show Sources' so the agent links the specific articles or data records used to ground its response." Option A correctly reflects these two documented configuration steps.
Option B is incorrect because Salesforce explicitly supports source display for transparency through the
"Show Sources" setting.
Option C incorrectly assumes that Data Categories control indexing visibility and source linking, which is handled by explicit Knowledge Settings, not categorization.
References (AgentForce Documents / Study Guide):
* AgentForce Data Library Configuration Guide: "Knowledge Settings for Public Article Indexing"
* AgentForce Transparency and Source Attribution Notes: "Show Sources Option"
* AgentForce Study Guide: "Configuring Knowledge Visibility and Source Display"
NEW QUESTION # 203
An Agentforce Specialist needs to create a prompt template to fill a custom field named Latest Opportunities Summary on the Account object with information from the three most recently opened opportunities. How should the Agentforce Specialist gather the necessary data for the prompt template?
Answer: A
Explanation:
In Salesforce Agentforce, a prompt template designed to populate a custom field (like "Latest Opportunities Summary" on the Account object) requires dynamic data to be fed into the template for AI to generate meaningful output. Here, the task is to gather data from the three most recently opened opportunities related to an account. The most robust and flexible way to achieve this is by using a Flow (Option B). Salesforce Flows allow the Agentforce Specialist to define logic to query the Opportunity object, filter for the three most recent opportunities (e.g., using a Get Records element with a sort by CreatedDate descending and a limit of
3), and pass this data as variables into the prompt template. This approach ensures precise control over the data retrieval process and can handle complex filtering or sorting requirements.
Option A: Selecting the "latest Opportunities related list as a merge field" is not a valid option in Agentforce prompt templates. Merge fields can pull basic field data (e.g., {!Account.Name}), but they don't natively support querying or aggregating related list data like the three most recent opportunities.
Option C: There is no "Account Opportunity object" in Salesforce; this seems to be a misnomer (perhaps implying the Opportunity object or a junction object). Even if interpreted as selecting the Opportunity object as a resource, prompt templates don't directly query related objects without additional logic (e.g., a Flow), making this incorrect.
Option B: Flows integrate seamlessly with prompt templates via dynamic inputs, allowing the Specialist to retrieve and structure the exact data needed (e.g., Opportunity Name, Amount, Close Date) for the AI to summarize.
Thus, Option B is the correct method to gather the necessary data efficiently and accurately.
Salesforce Agentforce Documentation: "Integrate Flows with Prompt Templates" (Salesforce Help:
https://help.salesforce.com/s/articleView?id=sf.agentforce_flow_prompt_integration.htm&type=5) Trailhead: "Build Flows for Agentforce" (https://trailhead.salesforce.com/content/learn/modules/flows-for- agentforce)
NEW QUESTION # 204
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