リアルなSalesforce-AI-Specialistは100%カバー試験問題をゲット [2025年05月]
問題集まとめ概要はSalesforce-AI-Specialist試験問題集はここ
Salesforce Salesforce-AI-Specialist 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
| トピック 5 |
|
質問 # 43
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. Create a flow to retrieve the opportunity information.
- C. Select the Account Opportunity object as a resource when creating the prompt template.
正解：B
解説：
To gather the necessary data for populating the Latest Opportunities Summary custom field on the Account object with information from the three most recently opened opportunities, the AI Specialist should create a flow. A flow can 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 a prompt template or other automation processes to populate the custom field on the Account record.
Option A is correct because creating a flow allows for dynamic data retrieval and control over the logic for selecting the most recent opportunities.
Option B and Option C do not provide sufficient control or data retrieval capabilities needed for this scenario.
Reference:
Salesforce Flow Documentation: https://help.salesforce.com/s/articleView?id=sf.flow.htm
質問 # 44
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. Ground with Apex Merge Fields
- C. Automatic grounding using Draft with Einstein feature
正解：C
解説：
For Einstein Sales Emails to 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 is Ground 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 Fields ensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
Apex Merge Fields are typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
Automatic grounding using Draft with Einstein is a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data like Record Merge Fields.
Reference:
Salesforce Einstein Sales Emails Documentation: https://help.salesforce.com/s/articleView?id=release-notes.rn_einstein_sales_emails.htm
質問 # 45
Universal Containers implemented Einstein Copilot for its users.
One user complains that Einstein Copilot is not deleting activities from the past 7 days.
What is the reason for this issue?
- A. Einstein Copilot Delete Record Action permission is not associated to the user.
- B. Einstein Copilot does not have the permission to delete the user's records.
- C. Einstein Copilot does not support the Delete Record action.
正解：C
解説：
Einstein Copilot currently supports various actions like creating and updating records but does not support the Delete Recordaction. Therefore, the user's request to delete activities from the past 7 days cannot be fulfilled using Einstein Copilot.
* Unsupported Action:The inability to delete records is due to the current limitations of Einstein Copilot's supported actions. It is designed to assist with tasks like data retrieval, creation, and updates, but for security and data integrity reasons, it does not facilitate the deletion of records.
* User Permissions:Even if the user has the necessary permissions to delete records within Salesforce, Einstein Copilot itself does not have the capability to execute delete operations.
References:
* Salesforce AI Specialist Documentation -Einstein Copilot Supported Actions:
* Lists the actions that Einstein Copilot can perform, noting the absence of delete operations.
* Salesforce Help -Limitations of Einstein Copilot:
* Highlights current limitations, including unsupported actions like deleting records.
質問 # 46
An AI Specialist wants to use the related lists from an account in a custom prompt template.
Whatshould the AI Specialist considerwhen configuring the prompt template?
- A. The text encoding (for example, UTF-8, ASCII) option
- B. The choice between XML and JSON rendering formats for the list
- C. The maximum number of related list merge fields
正解：C
解説：
When configuring acustom prompt templateto use related lists, the AI Specialist must be aware of the maximum number of related list merge fieldsthat can be included. Salesforce enforces limits to ensure prompt templates perform efficiently and do not overload the system with too much data. As a best practice, it's important to monitor and optimize the number of merge fields used.
* Option Bis correct because there is a limit on how many related list merge fields can be included in a prompt template.
* Option A(text encoding) andOption C(XML/JSON rendering) are not key considerations in this context.
References:
* Salesforce Prompt Builder Documentation:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder.htm
質問 # 47
The sales team at a hotel resort would like to generate a guest summary about the guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page.
Which AI capability should the team use?
- A. Prompt Builder
- B. Model Builder
- C. Einstein Copilot
正解：A
解説：
The sales team at a hotel resort wants to generate a guest summary about guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They require the summary to be availableonly on the contact record page.
Solution:
* UsePrompt Builderto create a prompt template that generates the desired summary and displays it on the contact record page.
* Prompt Builder:
* Purpose:Allows the creation of custom prompt templates that leverage AI to generate content based on Salesforce data.
* Functionality:
* Field Generation Templates:Can be used to populate fields on records with AI-generated summaries.
* Customization:Enables the AI Specialist to design prompts that utilize data from the guest profiles to produce personalized summaries and recommendations.
* Relevance to the Use Case:
* The sales team wants the summary to be available on the contact record page, which aligns with the capabilities of Prompt Builder to generate and display content on specific record pages.
* Implementation Steps:
* Create a Field Generation Prompt Template:
* Use Prompt Builder to create a new prompt template of typeField Generation.
* Design the prompt to instruct the AI to generate a summary based on the guest's interests and activity preferences.
* Include Relevant Data:
* Use merge fields to include data from the guest profile in the prompt.
* Ensure that the prompt accesses the necessary fields to generate accurate recommendations.
* Configure the Contact Page Layout:
* Add the field that will display the AI-generated summary to the contact record page layout.
* Ensure that the field is only visible where appropriate, adhering to the requirement of availability only on the contact record page.
* Why Not Einstein Copilot or Model Builder:
* Option A (Einstein Copilot):
* Purpose:Einstein Copilot is a conversational AI assistant designed to interact with users through natural language.
* Mismatch with Requirements:
* The team wants a static summary displayed on the contact record page, not an interactive conversational experience.
* Option C (Model Builder):
* Purpose:Model Builder is used to create custom AI models for predictions and classifications.
* Inapplicability:
* Building a custom model is unnecessary for generating text summaries based on existing data.
* Model Builder does not directly provide functionality to generate and display summaries on record pages.
References:
* Salesforce AI Specialist Documentation -Prompt Builder Overview:
* Provides an introduction to Prompt Builder and its capabilities.
* Salesforce Help -Creating Field Generation Prompt Templates:
* Guides on creating prompt templates that generate content for fields on records.
* Salesforce Trailhead -Customize AI Content with Prompt Builder:
* Offers hands-on experience in building and customizing prompt templates.
Conclusion:
By utilizing Prompt Builder, the sales team can create a customized prompt template that generates personalized guest summaries and recommendations based on activity preferences. This solution meets the requirement of displaying the summary only on the contact record page, enhancing the team's ability to engage with guests effectively.
質問 # 48
An Al Specialist is tasked with configuring a generative model to create personalized sales emails using customer data stored in Salesforce. The AI Specialist has already fine-tuned a large language model (LLM) on the OpenAI platform. Security and data privacy are critical concerns for the client.
How should the AI Specialist integrate the custom LLM into Salesforce?
- A. Create an application of the custom LLM and embed it in Sales Cloud via iFrame.
- B. Add the fine-tuned LLM in Einstein Studio Model Builder.
- C. Enable model endpoint on OpenAl and make callouts to the model to generate emails.
正解：B
解説：
Since security and data privacy are critical, the best option for the AI Specialist is to integrate the fine-tuned LLM (Large Language Model)into Salesforce by adding it toEinstein Studio Model Builder.Einstein Studioallows organizations to bring their own AI models (BYOM), ensuring the model is securely managed within Salesforce's environment, adhering to data privacy standards.
* Option A(embedding via iFrame) is less secure and doesn't integrate deeply with Salesforce's data and security models.
* Option C(making callouts to OpenAI) raises concerns about data privacy, as sensitive Salesforce data would be sent to an external system.
Einstein Studioprovides the most secure and seamless way to integrate custom AI models while maintaining control over data privacy and compliance. More details can be found inSalesforce's Einstein Studio documentationon integrating external models.
質問 # 49
Which feature in the Einstein Trust Layer helps to minimize the risks of jailbreaking and prompt injection attacks?
- A. Secure Data Retrieval and Grounding
- B. Data Masking
- C. Prompt Defense
正解：C
解説：
Prompt Defenseis a feature in theEinstein Trust Layerthat helps minimize the risks ofjailbreakingand prompt injection attacks. These attacks occur when malicious users try to manipulate the AI model by providing unintended inputs.Prompt Defenseensures that the prompts are processed securely, protecting the system from such vulnerabilities.
* Option A(Secure Data Retrieval and Grounding) relates to ensuring that data used by AI is securely retrieved but does not address prompt security.
* Option B(Data Masking) focuses on protecting sensitive information but does not prevent injection attacks.
For more information, refer toSalesforce's Einstein Trust Layer documentationonPrompt Defenseand security features.
質問 # 50
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 response from the LLM based on the sample record.
- B. It shows the full text that is sent to the Trust Layer.
- C. It shows which sensitive data is masked before it is sent to the LLM.
正解：A
解説：
When previewing aprompt templatein Salesforce, theResolutiontext provides theresponse 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 Bis correct becauseResolutiondisplays the actual response generated by the LLM.
* Option Arefers to sending the text to theTrust Layer, but that's not whatResolutionrepresents.
* Option Crelates to data masking, which is shown elsewhere, not underResolution.
References:
* Salesforce Prompt Builder Overview:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_overview.htm
質問 # 51
Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes.
What is a consideration for this requirement?
- A. Storing this data requires Data Cloud to be provisioned.
- B. Storing this data requires Salesforce big objects.
- C. Storing this data requires a custom object for data to be configured.
正解：A
解説：
When implementingEinstein Generative AIfor improved customer insights and interactions, theData Cloud is a key consideration for storing and managing large-scale audit and feedback data. TheSalesforce Data Cloud(formerly known asCustomer 360 Audiences) is designed to handle and unify massive datasets from various sources, making it ideal for storing data required for AI-powered insights and reporting. By provisioningData Cloud, organizations likeUniversal Containers (UC)can gain real-time access to customer data, making it a central repository for unified reporting across various systems.
* Audit and feedback datagenerated by Einstein Generative AI needs to be stored in a scalable and accessible environment, and theData Cloudprovides this capability, ensuring that data can be easily accessed for reporting, analytics, and further model improvement.
* Custom objectsorSalesforce Big Objectsare not designed for the scale or the specific type of real- time, unified data processing required in such AI-driven interactions.Big Objectsare more suited for archival data, whereasData Cloudensures more robust processing, segmentation, and analysis capabilities.
References:
* Salesforce Data Cloud Documentation:https://www.salesforce.com/products/data-cloud/overview/
* Salesforce Einstein AI Overview:https://www.salesforce.com/products/einstein/overview/
質問 # 52
Universal Containers (UC) has a legacy system that needs to integrate with Salesforce. UC wishes to create a digest of account action plans using the generative API feature.
Which API service should UC use to meet this requirement?
- A. SOAP API
- B. Metadata API
- C. REST API
正解：C
解説：
To create a digest of account action plans using the generative API feature,Universal Containersshould use theREST API. TheREST APIis ideal for integrating Salesforce with external systems and enabling interaction with Salesforce data, including generative capabilities like creating summaries or digests. It supports modern web standards and is suitable for flexible, lightweight interactions between Salesforce and legacy systems.
* Metadata APIis used for retrieving and deploying metadata, not for data operations like generating summaries.
* SOAP APIis an older API used for integration but is less flexible compared to REST for this specific use case.
For more details, refer toSalesforce REST API documentationregarding using REST for data integration and generating content.
質問 # 53
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 Prompt Builder.
- B. Turn on Einstein Generative AI.
- C. Turn on Einstein Copilot.
正解：B
解説：
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 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
質問 # 54
Universal Containers wants to reduce overall agent handling time minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields.
Which combination of Einstein for Service features enables this effort?
- A. Einstein Reply Recommendations and Case Classification
- B. Einstein Service Replies and Work Summaries
- C. Einstein Reply Recommendations and Case Summaries
正解：A
解説：
Universal Containers aims to reduce overall agent handling time by minimizing the time agents spend typing routine answers for common questions during chats and by reducing post-chat analysis through suggesting values for case fields.
To achieve these objectives, the combination of Einstein Reply Recommendations and Case Classification is the most appropriate solution.
1. Einstein Reply Recommendations:
Purpose: Helps agents respond faster during live chats by suggesting the best responses based on historical chat data and common customer inquiries.
Functionality:
Real-Time Suggestions: Provides agents with a list of recommended replies during a chat session, allowing them to quickly select the most appropriate response without typing it out manually.
Customization: Administrators can configure and train the model to ensure the recommendations are relevant and accurate.
Benefit: Significantly reduces the time agents spend typing routine answers, thus improving efficiency and reducing handling time.
2. Case Classification:
Purpose: Automatically suggests or populates values for case fields based on historical data and patterns identified by AI.
Functionality:
Field Predictions: Predicts values for picklist fields, checkbox fields, and more when a new case is created.
Automation: Can be set to auto-populate fields or provide suggestions for agents to approve.
Benefit: Reduces the time agents spend on post-chat analysis and data entry by automating the classification and field population process.
Why Options A and B are Less Suitable:
Option A (Einstein Service Replies and Work Summaries):
Einstein Service Replies: Similar to Reply Recommendations but typically used for email and not live chat.
Work Summaries: Provides summaries of customer interactions but does not assist in field value suggestions.
Option B (Einstein Reply Recommendations and Case Summaries):
Case Summaries: Generates a summary of the case details but does not help in suggesting field values.
Reference:
Salesforce AI Specialist Documentation - Einstein Reply Recommendations:
Details how Reply Recommendations assist agents in providing quick responses during live chats.
Salesforce AI Specialist Documentation - Einstein Case Classification:
Explains how Case Classification predicts and suggests field values to streamline case management.
Salesforce Trailhead - Optimize Service with AI:
Provides an overview of AI features that enhance service efficiency.
質問 # 55
Universal Containers (UC) wants to enable its sales team to use Al to suggest recommended products from its catalog.
Which type of prompt template should UC use?
- A. Flex prompt template
- B. Email generation prompt template
- C. Record summary prompt template
正解：A
解説：
Universal Containers (UC) wants to enable its sales team to leverage AI to recommend products from its catalog. The best option for this use case is a Flex prompt template.
A Flex prompt template is designed to provide flexible, customizable AI-driven recommendations or responses based on specific data points, such as product information, customer needs, or sales history. This template type allows the AI to consider various inputs and parameters, making it ideal for generating product recommendations dynamically.
In contrast:
* A Record summary prompt template (Option A) is used to summarize data related to a specific record, such as generating a quick summary of a sales opportunity or account, but not for recommending products.
* An Email generation prompt template (Option B) is tailored for crafting email content and is not suitable for suggesting products based on a catalog.
Given the need for dynamic recommendations that pull from a product catalog and potentially other sales data, the Flex prompt template is the correct approach.
Salesforce References:
* Salesforce Prompt Templates Overview: https://help.salesforce.com/s/articleView?
id=000391407&type=1
* Flex Prompt Template Usage: https://developer.salesforce.com/docs/atlas.en-us.salesforce_ai.meta
/salesforce_ai/prompt_flex_template
質問 # 56
Universal Containers has an active standard email prompt template that does not fully deliver on the business requirements.
Which steps should an AI Specialist take to use the content of the standard prompt email template in question andcustomize it to fully meet thebusiness requirements?
- A. Save as New Version and edit as needed.
- B. Clone the existing template and modify as needed.
- C. Save as New Template and edit as needed.
正解：B
解説：
When an active standard email prompt template doesn't meet the business requirements, the best approach is toclone the existing templateand modify it as needed. Cloning allows the AI Specialist to preserve the original template while making adjustments to fit specific business needs. This ensures that any customizations are applied without altering the original standard template.
Saving as a new versionis typically used for versioning changes in the same template, whileSave as New Templatecreates a brand-new template without linking to the existing one.Cloningprovides a balance, allowing modifications while retaining the original structure for future reference.
For more details, refer toSalesforce Prompt Builder documentationfor guidance on cloning and modifying templates.
質問 # 57
Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes.
What is a consideration for this requirement?
- A. Storing this data requires Data Cloud to be provisioned.
- B. Storing this data requires Salesforce big objects.
- C. Storing this data requires a custom object for data to be configured.
正解：A
解説：
When implementing Einstein Generative AI for improved customer insights and interactions, the Data Cloud is a key consideration for storing and managing large-scale audit and feedback data. The Salesforce Data Cloud (formerly known as Customer 360 Audiences) is designed to handle and unify massive datasets from various sources, making it ideal for storing data required for AI-powered insights and reporting. By provisioning Data Cloud, organizations like Universal Containers (UC) can gain real-time access to customer data, making it a central repository for unified reporting across various systems.
Audit and feedback data generated by Einstein Generative AI needs to be stored in a scalable and accessible environment, and the Data Cloud provides this capability, ensuring that data can be easily accessed for reporting, analytics, and further model improvement.
Custom objects or Salesforce Big Objects are not designed for the scale or the specific type of real-time, unified data processing required in such AI-driven interactions. Big Objects are more suited for archival data, whereas Data Cloud ensures more robust processing, segmentation, and analysis capabilities.
Reference:
Salesforce Data Cloud Documentation: https://www.salesforce.com/products/data-cloud/overview/ Salesforce Einstein AI Overview: https://www.salesforce.com/products/einstein/overview/
質問 # 58
What is the role of the large language model (LLM) in executing an Einstein Copilot Action?
- A. Identify the best matching actions and correct order of execution
- B. Find similar requests and provideactions that need to be executed
- C. Determine a user's access and sort actions by priority to be executed
正解：A
解説：
In Einstein Copilot, the role of the Large Language Model (LLM) is to analyze user inputs and identify the best matching actions that need to be executed. It uses natural language understanding to break down the user' s request and determine the correct sequence of actions that should be performed.
By doing so, the LLM ensures that the tasks and actions executed are contextually relevant and are performed in the proper order. This process provides a seamless, AI-enhanced experience for users by matching their requests to predefined Salesforce actions or flows.
The other options are incorrect because:
A mentions finding similar requests, which is not the primary role of the LLM in this context.
C focuses on access and sorting by priority, which is handled more by security models and governance than by the LLM.
References:
Salesforce Einstein Documentation on Einstein Copilot Actions
Salesforce AI Documentation on Large Language Models
質問 # 59
An Al Specialist is tasked with creating a prompt template for a sales team. The template needs to generate a summary of all related opportunities for a given Account.
Which grounding technique should the Al Specialist use to include data from the related list of opportunities in the prompt template?
- A. Use the merge fields to reference a custom related list of opportunities.
- B. Use merge fields to reference the default related list of opportunities.
- C. Use formula fields to reference the Einstein related list of opportunities.
正解：B
解説：
In Salesforce, when creating a prompt template for the sales team, you can include data from related objects such as Opportunities that are linked to an Account. The best method to ground the AI model and provide relevant information from related records, like Opportunities, is by using merge fields.
Merge fields in Salesforce allow you to dynamically reference data from a record or related records, like Opportunities for a given Account. In this scenario, the AI Specialist needs to pull data from the default related list of Opportunities associated with the Account. This is achieved by using merge fields, which pull in data from the standard relationship Salesforce creates between Accounts and Opportunities.
Option A (referencing a custom related list) and Option C (using formula fields with Einstein-related lists) do not align with the standard, practical grounding method for this task. Custom lists would require additional configurations not typically necessary for a basic use case, and formula fields are typically not used to directly fetch related list data for prompt generation in templates. The standard and straightforward method is using merge fields tied to the default related list of opportunities.
Salesforce References:
* Merge Fields in Templates: https://help.salesforce.com/s/articleView?id=000387601&type=1
* Grounding Data in Prompts: https://developer.salesforce.com/docs/atlas.en-us.salesforce_ai.meta
/salesforce_ai/grounding_data_prompts
質問 # 60
Universal Containers wants to utilize Einstein for Sales to help sales reps reach their sales quotas by providing Al-generated plans containing guidance and steps for closing deals.
Which feature should the AI Specialist recommend to the sales team?
- A. Create Account Plan
- B. Create Close Plan
- C. Find Similar Deals
正解：B
解説：
The "Create Close Plan" feature is designed to help sales reps by providing AI-generated strategies and steps specifically focused on closing deals. This feature leverages AI to analyze the current state of opportunities and generate a plan that outlines the actions, timelines, and key steps required to move deals toward closure. It aligns directly with the sales team's need to meet quotas by offering actionable insights and structured plans.
Find Similar Deals (Option A) helps sales reps discover opportunities similar to their current deals but doesn't offer a plan for closing.
Create Account Plan (Option B) focuses on long-term strategies for managing accounts, which might include customer engagement and retention, but doesn't focus on deal closure.
Salesforce AI Specialist Reference:
For more information on using AI for sales, visit: https://help.salesforce.com/s/articleView?id=sf.einstein_for_sales_overview.htm
質問 # 61
Which use case is best supported by Salesforce Einstein Copilot's capabilities?
- A. Bring together a conversational interface for interacting with AI for all Salesforce users, such as developers and ecommerce retailers.
- B. Enable Salesforce admin users to create and train custom large language models (LLMs) using CRM data.
- C. Enable data scientists to train predictive AI models with historical CRM data using built-in machine learning capabilities
正解：A
解説：
Salesforce Einstein Copilot is designed to provide a conversational AI interface that can be utilized by different types of Salesforce users, such as developers, sales agents, and retailers. It acts as an AI-powered assistant that facilitates natural interactions with the system, enabling users to perform tasks and access data easily. This includes tasks like pulling reports, updating records, and generating personalized responses in real time.
Option A is correct because Einstein Copilot brings a conversational interface that caters to a wide range of users.
Option B and Option C are more focused on developing and training AI models, which are not the primary functions of Einstein Copilot.
Reference:
Salesforce Einstein Copilot Overview: https://help.salesforce.com/s/articleView?id=einstein_copilot_overview.htm
質問 # 62
Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests.
What should an AI Specialist recommend to generate this email?
- A. Custom sales email template which is grounded with interest and product information
- B. Standard email draft with Einstein and choose standard email template
- C. Standard email marketing template using Apex or flows for matching interest in products
正解：A
解説：
To generate an email about products that closely match a customer's expressed interests, an AI Specialist should recommend using acustom sales email templatethat isgrounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message.
Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective.
For more information, refer toSalesforce documentationon grounding AI-generated content and email personalization strategies.
質問 # 63
......
認定トレーニングはSalesforce-AI-Specialist試験問題集テストエンジン：https://www.jpntest.com/shiken/Salesforce-AI-Specialist-mondaishu
Salesforce-AI-Specialistトレーニングと認定最新のAI Associate問題をゲットせよ：https://drive.google.com/open?id=13GWSGcW8PqKtF1rYHqjlYZS8ScD4iJnm