SALESFORCE-AI-SPECIALIST RELIABLE TEST OBJECTIVES, DUMPS SALESFORCE-AI-SPECIALIST DOWNLOAD

Salesforce-AI-Specialist Reliable Test Objectives, Dumps Salesforce-AI-Specialist Download

Salesforce-AI-Specialist Reliable Test Objectives, Dumps Salesforce-AI-Specialist Download

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Topic 2
  • Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.
Topic 3
  • Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Topic 4
  • Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.
Topic 5
  • Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.

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Salesforce Certified AI Specialist Exam Sample Questions (Q152-Q157):

NEW QUESTION # 152
Which business requirement presents a good use case for leveraging Einstein Prompt Builder?

  • A. Send reply to a request for proposal via a personalized email.
  • B. Forecast future sales trends based on historical data.
  • C. Identify potential high-value leads for targeted marketing campaigns.

Answer: A

Explanation:
* Context of the Question
* Einstein Prompt Builder is a Salesforce feature that helps generate text (summaries, email content, responses) using AI models.
* The question presents three potential use cases, asking which one best fits the capabilities of Einstein Prompt Builder.
* Einstein Prompt Builder Typical Use Cases
* Text Generation & Summaries: Great for writing or summarizing content, like responding to an email or generating text for a record field.
* Why Not Forecast Future Sales Trends or Identify Potential High-Value Leads?
* (Option A) Forecasting trends typically involves predictive analytics and modeling capabilities found in Einstein Discovery or standard reporting, not generative text solutions.
* (Option B) Identifying leads for marketing campaigns involves lead scoring or analytics, again an Einstein Discovery or Lead Scoring scenario.
* Sending a Personalized RFP Email(Option C) is a classic example of using generative AI to compose well-structured, context-aware text.
* ConclusionOption C(Send reply to a request for proposal via a personalized email) is the best match for Einstein Prompt Builder's generative text functionality.
Salesforce AI Specialist References & Documents
* Salesforce Documentation:Einstein Prompt Builder OverviewHighlights how to use Prompt Builder to create and customize text-based responses, especially for email or record fields.
* Salesforce AI Specialist Study GuideExplains that generative AI features in Salesforce are designed for creating or summarizing text, not for advanced predictive use cases (like forecasting or lead scoring).


NEW QUESTION # 153
Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page.
After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO?

  • A. Turn on Einstein Copilot.
  • B. Turn on Einstein Generative AI.
  • C. Turn on Prompt Builder.

Answer: B

Explanation:
For Northern Trail Outfitters (NTO) to configure the Einstein Trust Layer, the Einstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.
Option A (Turning on Einstein Copilot) is unrelated to the setup of the Einstein Trust Layer, which focuses more on generative AI interactions and data handling.
Option C (Turning on Prompt Builder) is used for configuring and building AI-driven prompts, but it does not enable the Einstein Trust Layer.
Salesforce AI Specialist Reference:
For more details on the Einstein Trust Layer and setup steps: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm


NEW QUESTION # 154
An AI Specialist is setting up a new org and needs to ensure that users can create and execute prompt templates. The AI Specialist is unsure which roles are necessary for these tasks.
Which permission sets should the AI Specialist assign to users who need to create and execute prompt templates?

  • A. Data Cloud Admin for creating templates and Prompt Template User for executing templates
  • B. Prompt Template Manager for creating templates and Data Cloud Admin for executing templates
  • C. Prompt Template Manager for creating templates and Prompt Template User for executing templates

Answer: C

Explanation:
To effectively manage and use prompt templates, two distinct permission sets are required:
* Prompt Template Manager: This permission set allows users to create prompt templates. It provides the necessary access to define templates, which can be shared and utilized across the organization.
* Prompt Template User: This permission set is designed for users who need to execute the templates. It provides the ability to interact with pre-designed prompts and generate outcomes based on these templates.
TheData Cloud Adminpermission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.


NEW QUESTION # 155
An AI Specialist built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors.
What is the cause of the random nature of this error?

  • A. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
  • B. The number of tokens that can be processed by the LLM varies with total user demand.
  • C. The number of tokens generated by the dynamic nature of the prompt template will vary by record.

Answer: C

Explanation:
The reason behind the token limit errors lies in the dynamic nature of the prompt template used in Field Generation. In Salesforce's AI generative models, each prompt and its corresponding output are subject to a token limit, which encompasses both the input and output of the large language model (LLM). Since the prompt template dynamically adjusts based on the specific data of each record, the number of tokens varies per record. Some records may generate longer outputs based on their data attributes, pushing the token count beyond the allowable limit for the LLM, resulting in token limit errors.
This behavior explains why users experience random failures-it is dependent on the specific data used in each case. For certain records, the combined input and output may fall within the token limit, while for others, it may exceed it. This variation is intrinsic to how dynamic templates interact with large language models.
Salesforce provides guidance in their documentation, stating that prompt template design should take into account token limits and suggests testing with varied records to avoid such random errors. It does not mention switching to Flex template type as a solution, nor does it suggest that token limits fluctuate with user demand.
Token limits are a constant defined by the model itself, independent of external user load.
References:
* Salesforce Developer Documentation onToken Limits for Generative AI Models
* Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources)


NEW QUESTION # 156
A Salesforce Administrator is exploring the capabilities of Einstein Copilot to enhance user interaction within their organization. They are particularly interested in how Einstein Copilot processes user requests and the mechanism it employs to deliver responses. The administrator is evaluating whether Einstein Copilot directly interfaces with a large language model (LLM) to fetch and display responses to user inquiries, facilitating a broad range of requests from users.
How does Einstein Copilot handle user requests In Salesforce?

  • A. Einstein Copilot analyzes the user's request and LLM technology is used to generate and display the appropriate response.
  • B. Einstein Copilot will perform an HTTP callout to an LLM provider.
  • C. Einstein Copilot will trigger a flow that utilizes a prompt template to generate the message.

Answer: A

Explanation:
Einstein Copilot is designed to enhance user interaction within Salesforce by leveraging Large Language Models (LLMs) to process and respond to user inquiries. When a user submits a request, Einstein Copilot analyzes the input using natural language processing techniques. It then utilizes LLM technology to generate an appropriate and contextually relevant response, which is displayed directly to the user within the Salesforce interface.
Option C accurately describes this process. Einstein Copilot does not necessarily trigger a flow (Option A) or perform an HTTP callout to an LLM provider (Option B) for each user request. Instead, it integrates LLM capabilities to provide immediate and intelligent responses, facilitating a broad range of user requests.
Reference:
Salesforce AI Specialist Documentation - Einstein Copilot Overview: Details how Einstein Copilot employs LLMs to interpret user inputs and generate responses within the Salesforce ecosystem.
Salesforce Help - How Einstein Copilot Works: Explains the underlying mechanisms of how Einstein Copilot processes user requests using AI technologies.


NEW QUESTION # 157
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