Exam Questions For Salesforce AI-201 With 1 year Of Updates

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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Reasoning Engine & AI Actions		- Workflow mastery 1. Standard Agent actions 2. Custom Agent actions (Flows) 3. Custom Agent actions (Apex)
Topic 2: Agent Force Concepts	30%	- Einstein GPT Integration 1. Advanced implementation strategies - Data Cloud & Grounding Techniques 1. Real-world applications
Topic 3: Prompt Engineering	30%	- Prompt Builder & Template Creation 1. Best practices - Agentforce AI Setup & Configuration 1. Advanced implementation strategies
Topic 4: Einstein Trust Layer & Security		- Trust Layer & Security Features 1. Enterprise-grade deployment - Data Masking 1. Configuration of privacy data entities

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Salesforce Certified Agentforce Specialist Sample Questions (Q126-Q131):

NEW QUESTION # 126
Universal Containers (UC) implements a custom retriever to improve the accuracy of AI- generated responses. UC notices that the retriever is returning too many irrelevant results, making the responses less useful. What should UC do to ensure only relevant data is retrieved?

A. Define filters to narrow the search results based on specific conditions.
B. Increase the maximum number of results returned to capture a broader dataset.
C. Change the search index to a different data model object (DMO).

Answer: A

Explanation:
In Salesforce Agentforce, a custom retriever is used to fetch relevant data (e.g., from Data Cloud's vector database or Salesforce records) to ground AI responses. UC's issue is that their retriever returns too many irrelevant results, reducing response accuracy. The best solution is to define filters (Option A) to refine the retriever's search criteria. Filters allow UC to specify conditions (e.g., "only retrieve documents from the `Policy' category" or "records created after a certain date") that narrow the dataset, ensuring the retriever returns only relevant results. This directly improves the precision of AI-generated responses by excluding extraneous data, addressing UC's problem effectively.

NEW QUESTION # 127
Universal Containers (UC) wants to assess Salesforce's generative features but has concerns over its company data being exposed to third- party large language models (LLMs). Specifically, UC wants the following capabilities to be part of Einstein's generative AI service.
- No data is used for LLM training or product improvements by third-
party LLMs.
- No data is retained outside of UC's Salesforce org.
- The data sent cannot be accessed by the LLM provider.
Which property of the Einstein Trust Layer should the Agentforce Specialist highlight to UC that addresses these requirements?

A. Data Masking
B. Prompt Defense
C. Zero-Data Retention Policy

Answer: C

Explanation:
Universal Containers (UC) has concerns about data privacy when using Salesforce's generative AI features, particularly around preventing third-party LLMs from accessing or retaining their data.
The Zero-Data Retention Policy in the Einstein Trust Layer is designed to address these concerns by ensuring that:
No data is used for training or product improvements by third-party LLMs.
No data is retained outside of the customer's Salesforce organization.
The LLM provider cannot access any customer data.
This policy aligns perfectly with UC's requirements for keeping their data safe while leveraging generative AI capabilities.
Prompt Defense and Data Masking are also security features, but they do not directly address the concerns related to third-party data access and retention.

NEW QUESTION # 128
What is an appropriate use case for leveraging Agentforce Sales Agent in a sales context?

A. Enable a sates team to use natural language to invoke defined sales tasks grounded in relevant data and be able to ensure company policies are applied. conversationally and in the now or work.
B. Instantly review and read incoming messages or emails that are then logged to the correct opportunity, contact, and account records to provide a full view of customer interactions and communications.
C. Enable a sales team by providing them with an interactive step-by-step guide based on business rules to ensure accurate data entry into Salesforce and help close deals fatter.

Answer: A

Explanation:
Agentforce Sales Agent is designed to let sales teams perform tasks via natural language commands, leveraging Salesforce data while adhering to policies. For example, agents can ask the AI to "update the opportunity stage to Closed Won" or "generate a quote," with the system enforcing validations and data security. This use case aligns with Salesforce's vision of conversational AI streamlining workflows without compromising compliance.

NEW QUESTION # 129
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)?

A. Mask sensitive fields and index only non-PII data
B. Depend on the agent's prompt to avoid exposing PII
C. Encrypt embeddings, but still index PII records

Answer: A

NEW QUESTION # 130
Universal Containers (UC) noticed an increase in customer contract cancellations in the last few months. UC is seeking ways to address this issue by implementing a proactive outreach program to customers before they cancel their contracts and is asking the Salesforce team to provide suggestions. Which use case functionality of Model Builder aligns with UC's request?

A. Contract Renewal Date prediction
B. Customer churn prediction
C. Product recommendation prediction

Answer: B

Explanation:
Customer churn prediction is the best use case for Model Builder in addressing Universal Containers' concerns about increasing customer contract cancellations. By implementing a model that predicts customer churn, UC can proactively identify customers who are at risk of canceling and take action to retain them before they decide to terminate their contracts. This functionality allows the business to forecast churn probability based on historical data and initiate timely outreach programs.

NEW QUESTION # 131
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