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Salesforce Salesforce-AI-Specialist Exam Sample Questions

Question # 1

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. Model Builder

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.

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Question # 2

An AI Specialist is creating a custom action in Einstein Copilot. Which option is available for the AI Specialist to choose for the custom copilot action?

A. Apex trigger

B. SOQL

C. Flows

Answer

C. Flows

Explanation: When creating acustom actionin Einstein Copilot, one of the available options is to useFlows. 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.
WhileApex triggersandSOQLare important Salesforce tools,Flowsare the recommended method for creating custom actions within Einstein Copilot because they are declarative and highly adaptable.
For further guidance, refer toSalesforce Flow documentationandEinstein Copilot customization resources.

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Question # 3

An AI Specialist wants to include data from the response ofexternal service invocation (REST API callout) into the prompt template. How should the AI Specialist meet this requirement?

A. Convert the JSON to an XML merge field.

B. Use External Service Record merge fields.

C. Use “Add Prompt Instructions” flow element.

Answer

B. Use External Service Record merge fields.

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:
External Service Record Merge Fields:
Implementation Steps:
Register the External Service:
Create a Named Credential:
Use External Service in Flow:
Configure the Prompt Template:
Why Other Options are Less Suitable:
Option A (Convert the JSON to an XML merge field):
Option C (Use “Add Prompt Instructions” flow element):
References:
Salesforce AI Specialist Documentation -Integrating External Services with Prompt Templates:
Salesforce Help -Using Merge Fields with External Data:
Salesforce Trailhead -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.

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Question # 4

An AI Specialist configured Data Masking within the Einstein Trust Layer. How should the AI Specialist begin validating that the correct fields are being masked?

A. Use a Flow-based resource in Prompt Builder to debug the fields’ merge values using Flow Debugger.

B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.

C. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.

Answer

B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.

Explanation:

To begin validating that the correct fields are being masked in Einstein Trust Layer, the AI Specialist should request the Einstein Generative AI Audit Data from the Security section of the Salesforce Setup menu. This audit data allows the AI Specialist to see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected.

Option B is correct because it allows for the retrieval of audit data that can be used to validate data masking.

Option A (Flow Debugger) and Option C (Einstein Feedback) do not relate to validating field masking in the context of the Einstein Trust Layer.

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Question # 5

Before activating a custom copilot action, an AI Specialist would like is to understand multiple real-world user utterances to ensure the action being selected appropriately. Which tool should the AI Specialist recommend?

A. Model Playground

B. Einstein Copilot

C. Copilot Builder

Answer

C. Copilot Builder

Explanation: To understand multiple real-world user utterances and ensure the correct action is selected before activating acustom copilot action, the recommended tool is Copilot Builder. This tool allows AI Specialists to design and test conversational actions in response to user inputs, helping ensure the copilot can accurately handle different user queries and phrases.Copilot Builderprovides the ability to test, refine, and improve actions based on real-world utterances.
Option Cis correct asCopilot Builderis designed for configuring and testing conversational actions. Option A(Model Playground) is used for testing models, not user utterances. Option B(Einstein Copilot) refers to the conversational interface but isn't the right tool for designing and testing actions.

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