매달, 우리는 1000명 이상의 사람들이 시험 준비를 잘하고 시험을 잘 통과할 수 있도록 도와줍니다.
Salesforce Certified AI Specialist Exam 온라인 연습
최종 업데이트 시간: 2025년06월06일
당신은 온라인 연습 문제를 통해 Salesforce Salesforce AI Specialist 시험지식에 대해 자신이 어떻게 알고 있는지 파악한 후 시험 참가 신청 여부를 결정할 수 있다.
시험을 100% 합격하고 시험 준비 시간을 35% 절약하기를 바라며 Salesforce AI Specialist 덤프 (최신 실제 시험 문제)를 사용 선택하여 현재 최신 92개의 시험 문제와 답을 포함하십시오.
정답:
Explanation:
To monitor Einstein Copilot's usability and the assignment of actions, the AI Specialist should run Einstein Copilot Analytics. This feature provides insights into how often Copilot is used, the types of actions it is handling, and overall user engagement with the system. It’s the most effective way to track Copilot's performance and usage patterns.
Platform Debug Logs are not relevant for tracking user behavior or the assignment of Copilot actions. Querying the Copilot log data via the Metadata API would not provide the necessary insights in a structured manner.
For more details, refer to Salesforce's Copilot Analytics documentation for tracking AI-driven interactions.
정답:
Explanation:
When Universal Containers uses the Draft with Einstein feature in Sales Cloud to create a personalized email, the predefined adjustment to Make Less Formal is the correct option to revise the draft with a more casual tone. This option adjusts the wording of the draft to sound less formal, making the communication more approachable while still maintaining professionalism. Enhance Friendliness would make the tone more positive, but not necessarily more casual.
Optimize for Clarity focuses on making the draft clearer but doesn't adjust the tone.
For more details, see Salesforce documentation on Einstein-generated email drafts and tone adjustments.
정답:
Explanation:
When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
Option B is incorrect because person accounts do not limit the availability of merge fields for the Account object.
Option C is irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields.
For more information, refer to Salesforce documentation on supported fields and limitations in Prompt Builder.
정답:
Explanation:
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 to Einstein Studio Model Builder. Einstein Studio allows 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 Studio provides the most secure and seamless way to integrate custom AI models while maintaining control over data privacy and compliance. More details can be found in Salesforce's Einstein Studio documentation on integrating external models.
정답:
Explanation:
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 available only on the contact record page.
Solution:
Use Prompt Builder to 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 type Field 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.
Reference: 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.
정답:
Explanation:
To create a digest of account action plans using the generative API feature, Universal Containers should use the REST API. The REST API is 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 API is used for retrieving and deploying metadata, not for data operations like generating summaries.
SOAP API is an older API used for integration but is less flexible compared to REST for this specific use case.
For more details, refer to Salesforce REST API documentation regarding using REST for data integration and generating content.
정답:
Explanation:
An AI Specialist wants to include data from the response of an external service invocation (REST API callout) into a prompt template. The goal is to incorporate dynamic data retrieved from an external API into the AI-generated content.
Solution:
Use External Service Record Merge Fields
External Service Integration:
Definition: External Services in Salesforce allow the integration of external REST APIs into Salesforce without custom code.
Registration: The external service must be registered in Salesforce, defining the API's schema and methods.
External Service Record Merge Fields:
Purpose: Enables the inclusion of data from external service responses directly into prompt templates using merge fields.
Functionality:
Dynamic Data Inclusion: Allows prompt templates to access and use data returned from REST API callouts.
Merge Fields Syntax: Use merge fields in the prompt template to reference specific data points from the API response.
Implementation Steps:
Register the External Service:
Use External Services to register the REST API in Salesforce. Define the API's schema, including methods and data structures. Create a Named Credential:
Configure authentication and endpoint details for the external API.
Use External Service in Flow:
Build a Flow that invokes the external service and captures the response. Ensure the flow outputs the necessary data for use in the prompt template.
Configure the Prompt Template:
Use External Service Record merge fields in the prompt template to reference data from the flow's output.
Syntax Example: {{flowOutputVariable.fieldName}}
Why Other Options are Less Suitable:
Option A (Convert the JSON to an XML merge field):
Irrelevance: Converting JSON to XML merge fields is unnecessary and complicates the process. Unsupported Method: Salesforce prompt templates do not support direct inclusion of XML merge fields from JSON conversion.
Option C (Use “Add Prompt Instructions” flow element):
Purpose of Add Prompt Instructions:
Allows adding instructions to the prompt within a flow but does not facilitate including external data.
Limitation: Does not directly help in incorporating external service responses into the prompt
template.
Reference: Salesforce AI Specialist Documentation - Integrating External Services with Prompt Templates:
Explains how to use External Services and merge fields in prompt templates.
Salesforce Help - Using Merge Fields with External Data:
Provides guidance on referencing external data in templates using merge fields.
Salesforce Trailhead - External Services and Flow:
Offers a practical understanding of integrating external APIs using External Services and Flow.
Conclusion:
By using External Service Record merge fields, the AI Specialist can effectively include data from external REST API responses into prompt templates, ensuring that the AI-generated content is enriched with up-to-date and relevant external data.
정답:
Explanation:
When using Prompt Builder in a Salesforce org, the correct process involves several important steps:
Select the appropriate prompt template type based on the use case.
Develop the prompt within the prompt workspace, where the template is created and customized. Select CRM-derived grounding data to be dynamically inserted into the prompt, ensuring that the AI-generated responses are based on accurate and relevant data.
Pick the model to use for generating responses, either using Salesforce's built-in models or custom ones.
Test and validate the generated responses to ensure accuracy and effectiveness.
Option B is correct as it follows the proper steps for using Prompt Builder.
Option A and Option C do not capture the full process correctly.
Reference: Salesforce Prompt Builder Documentation:
https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm
정답:
Explanation:
Universal Containers (UC) has concerns about data privacy when using Salesforce's generative AI features, particularly around preventing third-party LLMs from accessing or retaining their data. The Zero-Data Retention Policy in the Einstein Trust Layer is designed to address these concerns by ensuring that:
No data is used for training or product improvements by third-party LLMs.
No data is retained outside of the customer's Salesforce organization.
The LLM provider cannot access any customer data.
This policy aligns perfectly with UC’s requirements for keeping their data safe while leveraging generative AI capabilities.
Prompt Defense and Data Masking are also security features, but they do not directly address the concerns related to third-party data access and retention.
Reference: Salesforce Einstein Trust Layer Documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer.htm
정답:
Explanation:
When creating a custom action in Einstein Copilot, one of the available options is to use Flows. Flows are a powerful automation tool in Salesforce, allowing the AI Specialist to define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code.
While Apex triggers and SOQL are important Salesforce tools, Flows are the recommended method for creating custom actions within Einstein Copilot because they are declarative and highly adaptable.
For further guidance, refer to Salesforce Flow documentation and Einstein Copilot customization resources.
정답:
Explanation:
To generate an email about products that closely match a customer’s expressed interests, an AI Specialist should recommend using a custom sales email template that is grounded 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 to Salesforce documentation on grounding AI-generated content and email personalization strategies.
정답:
Explanation:
Universal Containers can achieve the request to explore similar opportunities by using the standard Copilot action. Einstein Copilot has built-in actions to handle natural language queries, such as “Show me other opportunities like this one.” The standard action will process the query and return results based on predefined matching criteria like opportunity details and past Closed Won deals. This approach avoids the need to create custom flows or Apex classes, leveraging out-of-the-box functionality.
For further details, refer to Einstein Copilot for Sales documentation regarding standard actions and natural language processing.
정답:
Explanation:
When Einstein Copilot for Sales matches similar opportunities, one of the primary criteria used is whether the opportunities have a status of Closed Won within the last 12 months. This is a key factor in identifying successful patterns that could help close current deals. By focusing on opportunities that have been recently successful, Einstein Copilot can provide relevant insights and suggestions to sales reps to help them close similar deals faster.
For more information, review Salesforce Einstein Copilot documentation related to opportunity matching and sales success patterns.
정답:
Explanation:
When configuring a custom prompt template to use related lists, the AI Specialist must be aware of the maximum number of related list merge fields that 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 B is correct because there is a limit on how many related list merge fields can be included in a prompt template.
Option A (text encoding) and Option C (XML/JSON rendering) are not key considerations in this context.
Reference: Salesforce Prompt Builder Documentation:
https://help.salesforce.com/s/articleView?id=sf.prompt_builder.htm
정답:
Explanation:
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