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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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.
Topic 4	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 5	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.

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Salesforce Certified AI Specialist Exam Sample Questions (Q97-Q102):

NEW QUESTION # 97
Universal Containers (UC) is using Einstein Generative AI to generate an account summary. UC aims to ensure the content is safe and inclusive, utilizing the Einstein Trust Layer's toxicity scoring to assess the content's safety level.
What does a safety category score of 1 indicate in the Einstein Generative Toxicity Score?

A. Safe
B. Not safe
C. Moderately safe

Answer: A

Explanation:
In theEinstein Trust Layer, thetoxicity scoringsystem is used to evaluate the safety level of content generated by AI, particularly to ensure that it is non-toxic, inclusive, and appropriate for business contexts. A toxicity score of 1indicates that the content is deemedsafe.
The scoring system ranges from 0 (unsafe) to 1 (safe), with intermediate values indicating varying degrees of safety. In this case, a score of 1 means that the generated content is fully safe and meets the trust and compliance guidelines set by theEinstein Trust Layer.
For further reference, check Salesforce's officialEinstein Trust Layer documentationregardingtoxicity scoringfor AI-generated content.

NEW QUESTION # 98
An AI Specialist at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time. UC wants to help prep the sales team for the calls by summarizing past purchases, interests in products shown by the Contact captured via Data Cloud, and a recap of past email and phone conversations for which there are transcripts.
Which approach should the AI Specialist recommend to achieve this use case?

A. Deploy UC's own custom foundational model on this data first.
B. Fine-Tune the standard foundational model due to the complexity of the data.
C. Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.

Answer: C

Explanation:
For no-code implementations, Prompt Builder allows AI Specialists to create prompt templates that dynamically ground responses in Salesforce CRM data (e.g., past purchases) and Data Cloud insights (e.g., product interests) without custom coding. The standard foundation model (e.g., Einstein GPT) can synthesize this data into summaries, leveraging structured and unstructured sources (e.g., email/phone transcripts). Fine- tuning (B) or custom models (C) require code and are unnecessary here, as the use case does not involve unique data patterns requiring model retraining.

NEW QUESTION # 99
Based on the user utterance, "Show me all the customers in New York", which standard Einstein Copilot action will the planner service use?

A. Select Records
B. Query Records
C. Fetch Records

Answer: B

Explanation:
Thestandard Einstein Copilot actionthat would be used in response to the user utterance, "Show me all the customers in New York," isQuery Records. This action is responsible for retrieving a set of records from Salesforce based on a specified condition - in this case, filtering customers by location (New York).
* Query Recordsis the action that fetches relevant data based on the criteria provided in the user's input.
* Select Recordsis more about picking specific records from an already presented list.
* Fetch Recordsis not a standard term used in this context for the action.
Refer toEinstein Copilot documentationon how Copilot actions work with natural language queries and data retrieval.

NEW QUESTION # 100
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. App Builder
C. Copilot 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.
Option B, App Builder, is primarily used to build and configure applications in Salesforce, not to integrate AI models.
Option C, Copilot Builder, focuses on building assistant-like tools rather than integrating external AI models.
Model Builder enables seamless integration with external systems and models, allowing Salesforce users to use external LLMs for generating AI-driven insights and automation.
Salesforce AI Specialist Reference:
For more details, check the Model Builder guide here: https://help.salesforce.com/s/articleView?id=sf.model_builder_external_models.htm

NEW QUESTION # 101
Universal Containers (UC) wants to leverage Generative AI Salesforce functionality to reduce Service Agent handling time by providing recommended replies based on the existing Knowledge articles.
On which AI capability should UC train the service agents?

A. Service Replies
B. Knowledge Replies
C. Case Replies

Answer: B

Explanation:
Knowledge Replies is the Einstein Generative AI capability that generates recommended responses for service agents by grounding responses in the organization's Knowledge articles. This reduces handling time by providing contextually accurate suggestions sourced directly from approved content. Salesforce documentation states that Knowledge Replies leverage natural language processing (NLP) to match customer inquiries with relevant articles and draft replies, ensuring consistency and compliance.
* Case Replies (A) focus on generating responses based on case data (e.g., case fields, history) but do not explicitly ground responses in Knowledge articles.
* Service Replies (C) is not a standard Einstein capability tied to Knowledge-driven responses.

NEW QUESTION # 102
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Salesforce Salesforce-AI-Specialist Exam Prep Material Are Available In Multiple Formats​

Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

Salesforce-AI-Specialist Reliable Practice Questions | Salesforce-AI-Specialist Reliable Dumps

Salesforce Certified AI Specialist Exam Sample Questions (Q97-Q102):

Salesforce Salesforce-AI-Specialist Exam Prep Material Are Available In Multiple Formats