FREE PDF HIGH HIT-RATE SALESFORCE - SALESFORCE-AI-SPECIALIST LATEST CRAM MATERIALS

Free PDF High Hit-Rate Salesforce - Salesforce-AI-Specialist Latest Cram Materials

Free PDF High Hit-Rate Salesforce - Salesforce-AI-Specialist Latest Cram Materials

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Tags: Salesforce-AI-Specialist Latest Cram Materials, Salesforce-AI-Specialist Updated Dumps, Salesforce-AI-Specialist Valid Test Simulator, Salesforce-AI-Specialist Valid Exam Test, New Salesforce-AI-Specialist Test Questions

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 5
  • 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.

Salesforce Certified AI Specialist Exam Sample Questions (Q89-Q94):

NEW QUESTION # 89
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.
In the score of 1 indicate?

  • A. The response is the least toxic Einstein Generative AI Toxicity Scoring system, what does a toxicity category.
  • B. The response is the most toxic.
  • C. The response is not toxic.

Answer: B

Explanation:
Einstein Trust Layer's Toxicity Scoring categorizes content on a scale of 0 to 1, where 1 indicates the highest level of toxicity (e.g., harmful, biased, or inappropriate language). This scoring helps organizations filter unsafe AI-generated content. A score of 1 triggers mitigation actions, such as blocking the response or alerting administrators.
* A score of 0 would indicate no toxicity (B is incorrect).
* The scoring system does not use "least toxic" as a category (A is misleading).


NEW QUESTION # 90
Universal Containers (UC) is discussing its AI strategy in an agile Scrum meeting.
Which business requirement would lead an AI Specialist to recommend connecting to an external foundational model via Einstein Studio (Model Builder)?

  • A. UC wants to fine-tune model temperature.
  • B. UC wants a model fine-tuned using company data.
  • C. UC wants to change the frequency penalty of the model.

Answer: B

Explanation:
Einstein Studio (Model Builder) allows organizations to connect and utilize external foundational models while fine-tuning them with company-specific data. This capability is particularly suited to businesses like Universal Containers (UC) that require customization of foundational models to better align with their unique data and use cases.
* Option A: Adjusting model temperature is a parameter-level setting for controlling randomness in AI- generated responses but does not necessitate connecting to an external foundational model.
* Option B: This is the correct answer because Einstein Studio supports fine-tuning external models with proprietary company data, enabling a tailored and more accurate AI solution for UC.
* Option C: Changing frequency penalties is another parameter-level adjustment and does not require external foundational models or Einstein Studio.


NEW QUESTION # 91
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 Generative AI.
  • B. Turn on Prompt Builder.
  • C. Turn on Einstein Copilot.

Answer: A

Explanation:
For Northern Trail Outfitters (NTO) to configure theEinstein Trust Layer, theEinstein 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 References: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 # 92
An AI 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 AI Specialist gather the necessary data for the prompt template?

  • A. Create a flow to retrieve the opportunity information.
  • B. Select the Account Opportunity object as a resource when creating the prompt template.
  • C. Select the latest Opportunities related list as a merge field.

Answer: A

Explanation:
To gather the necessary data for populating theLatest Opportunities Summarycustom field on theAccount object with information from the three most recently opened opportunities, the AI Specialist shouldcreate a flow. Aflowcan be configured to query and retrieve the required opportunity records based on criteria such as their open date. Once the flow has gathered the necessary data, it can be used in aprompt templateor other automation processes to populate the custom field on the Account record.
* Option Ais correct because creating a flow allows for dynamic data retrieval and control over the logic for selecting the most recent opportunities.
* Option BandOption Cdo not provide sufficient control or data retrieval capabilities needed for this scenario.
References:
* Salesforce Flow Documentation:https://help.salesforce.com/s/articleView?id=sf.flow.htm


NEW QUESTION # 93
Universal Containers (UC) is implementing generative AI and wants to leverage a prompt template to provide responses to customers that gives personalized product recommendations to website visitors based on their browsing history.
Which initial step should UC take to ensure the chatbot can deliver accurate recommendations'

  • A. Collect and analyze browsing data.
  • B. Design universal product recommendations.
  • C. Write a response scrip for the chatbot.

Answer: A

Explanation:
To enable personalized product recommendations using generative AI, the foundational step for Universal Containers (UC) is collecting and analyzing browsing data (Option C). Personalized recommendations depend on understanding user behavior, which requires structured data about their browsing history. Without this data, the AI model lacks the context needed to generate relevant suggestions.
* Data Collection: UC must first aggregate browsing data (e.g., pages visited, products viewed, session duration) to build a dataset that reflects user preferences.
* Data Analysis: Analyzing this data identifies patterns (e.g., frequently viewed categories) that inform how prompts should be structured to retrieve relevant recommendations.
* Grounding in Data: Salesforce's Prompt Templates rely on grounding data to generate accurate outputs. Without analyzing browsing data, the prompt template cannot reference meaningful insights for personalization.
Options A and D are incorrect because:
* Universal recommendations (A) ignore personalization, which is the core requirement.
* Writing a response script (D) addresses chatbot interaction design, not the accuracy of recommendations.
References:
* Salesforce AI Specialist Certification Guide: Highlights the importance of grounding prompts in relevant data sources to ensure accuracy.
* Trailhead Module: "Einstein for Developers" emphasizes data preparation as a prerequisite for effective AI-driven personalization.
* Salesforce Help Documentation: Recommends analyzing user behavior data to tailor generative AI outputs in commerce use cases.


NEW QUESTION # 94
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