SALESFORCE CERTIFIED AI SPECIALIST EXAMLATEST TEST QUESTIONS & SALESFORCE-AI-SPECIALIST RELIABLE BRAINDUMPS & SALESFORCE CERTIFIED AI SPECIALIST EXAMFREE PRACTICE DUMPS

Salesforce Certified AI Specialist Examlatest test questions & Salesforce-AI-Specialist reliable braindumps & Salesforce Certified AI Specialist Examfree practice dumps

Salesforce Certified AI Specialist Examlatest test questions & Salesforce-AI-Specialist reliable braindumps & Salesforce Certified AI Specialist Examfree practice dumps

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Salesforce Certified AI Specialist Exam Sample Questions (Q150-Q155):

NEW QUESTION # 150
Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. Thegoal is to enhance the team'sperformance by identifying areas for improvement and competitive intelligence.
Which feature provides insights about competitor mentions and coaching opportunities?

  • A. Einstein Sales Insights
  • B. Call Explorer
  • C. Call Summaries

Answer: B

Explanation:
For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information,Call Exploreris the most suitable feature.Call Explorer, a part ofEinstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentionsand moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls.
* Call Summariesoffer a quick overview of a call but do not delve deep into competitor mentions or coaching insights.
* Einstein Sales Insightsfocuses more on pipeline and forecasting insights rather than call-based analysis.
References:
* Salesforce Einstein Conversation Insights Documentation:https://help.salesforce.com/s/articleView?
id=einstein_conversation_insights.htm


NEW QUESTION # 151
An AI Specialist implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in Salesforce. The AI Specialist needs to configure the system to use the most accurate and up-to-date information for email generation.
Which grounding technique should the AI Specialist use?

  • A. Ground with Record Merge Fields
  • B. Automatic grounding using Draft with Einstein feature
  • C. Ground with Apex Merge Fields

Answer: B

Explanation:
ForEinstein Sales Emailsto generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real- time data. The most appropriate technique in this case isGround with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
* Record Merge Fieldsensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
* Apex Merge Fieldsare typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
* Automatic grounding using Draft with Einsteinis a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data likeRecord Merge Fields.
References:
* Salesforce Einstein Sales Emails Documentation:https://help.salesforce.com/s/articleView?id=release- notes.rn_einstein_sales_emails.htm


NEW QUESTION # 152
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. Select the latest Opportunities related list as a merge field.
  • B. Select the Account Opportunity object as a resource when creating the prompt template.
  • C. Create a flow to retrieve the opportunity information.

Answer: C

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 # 153
When configuring a prompt template, an AI Specialist previews the results of the prompt template they've written. They see two distinct text outputs: Resolution and Response.
Which information does the Resolution text provide?

  • A. It shows the full text that is sent to the Trust Layer.
  • B. It shows the response from the LLM based on the sample record.
  • C. It shows which sensitive data is masked before it is sent to the LLM.

Answer: B

Explanation:
When previewing a prompt template in Salesforce, the Resolution text provides the response from the LLM (Large Language Model) based on the data from a sample record. This output shows what the AI model generated in response to the prompt, giving the AI Specialist a chance to review and adjust the response before finalizing the template.
Option B is correct because Resolution displays the actual response generated by the LLM.
Option A refers to sending the text to the Trust Layer, but that's not what Resolution represents.
Option C relates to data masking, which is shown elsewhere, not under Resolution.
Reference:
Salesforce Prompt Builder Overview: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm


NEW QUESTION # 154
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. Write a response scrip for the chatbot.
  • B. Design universal product recommendations.
  • C. Collect and analyze browsing data.

Answer: C

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 # 155
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