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Salesforce Certified AI Specialist Exam Sample Questions (Q50-Q55):

NEW QUESTION # 50
An AI Specialist at Universal Containers is trying to set up a new Field Generation prompt template. They take the following steps.
1. Create a new Field Generation prompt template.
2. Choose Case as the object type.
3. Select the custom field AI_Analysis_c as the target field.
After creating the prompt template, the AI Specialist saves, tests, and activates it. Howsoever, when they go to a case record, the AI Analysis field does not show the (Sparkle) icon on the Edit pencil. When the AI Specialist was editing the field, it was behaving as a normal field.
Which critical step did the AI Specialist miss?

A. They forgot to reactivate the Lightning page layout for the Case object after activating their Field Generation prompt template.
B. They forgot to edit the Lightning page layout and associate the field to a prompt template
C. They forgot that the Case Object is not supported for Add generation as Feinstein Service Replies should be used instead.

Answer: B

Explanation:
For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the templatewill result in the field behaving as a standard field. Salesforce documentation emphasizes that page layout configuration is mandatory to enable AI-driven field interactions.
* Reactivating the layout (A) is unnecessary unless the layout itself was modified after activation.
* Case objects are supported for Field Generation (B is incorrect).

NEW QUESTION # 51
How does the Einstein Trust Layer ensure that sensitive data is protected while generating useful and meaningful responses?

A. Masked data will be de-masked during request journey.
B. Masked data will be de-masked during response journey.
C. Responses that do not meet the relevance threshold will be automatically rejected.

Answer: B

Explanation:
The Einstein Trust Layer ensures that sensitive data is protected while generating useful and meaningful responses by masking sensitive data before it is sent to the Large Language Model (LLM) and then de-masking it during the response journey.
How It Works:
Data Masking in the Request Journey:
Sensitive Data Identification: Before sending the prompt to the LLM, the Einstein Trust Layer scans the input for sensitive data, such as personally identifiable information (PII), confidential business information, or any other data deemed sensitive.
Masking Sensitive Data: Identified sensitive data is replaced with placeholders or masks. This ensures that the LLM does not receive any raw sensitive information, thereby protecting it from potential exposure.
Processing by the LLM:
Masked Input: The LLM processes the masked prompt and generates a response based on the masked data.
No Exposure of Sensitive Data: Since the LLM never receives the actual sensitive data, there is no risk of it inadvertently including that data in its output.
De-masking in the Response Journey:
Re-insertion of Sensitive Data: After the LLM generates a response, the Einstein Trust Layer replaces the placeholders in the response with the original sensitive data.
Providing Meaningful Responses: This de-masking process ensures that the final response is both meaningful and complete, including the necessary sensitive information where appropriate.
Maintaining Data Security: At no point is the sensitive data exposed to the LLM or any unintended recipients, maintaining data security and compliance.
Why Option A is Correct:
De-masking During Response Journey: The de-masking process occurs after the LLM has generated its response, ensuring that sensitive data is only reintroduced into the output at the final stage, securely and appropriately.
Balancing Security and Utility: This approach allows the system to generate useful and meaningful responses that include necessary sensitive information without compromising data security.
Why Options B and C are Incorrect:
Option B (Masked data will be de-masked during request journey):
Incorrect Process: De-masking during the request journey would expose sensitive data before it reaches the LLM, defeating the purpose of masking and compromising data security.
Option C (Responses that do not meet the relevance threshold will be automatically rejected):
Irrelevant to Data Protection: While the Einstein Trust Layer does enforce relevance thresholds to filter out inappropriate or irrelevant responses, this mechanism does not directly relate to the protection of sensitive data. It addresses response quality rather than data security.
Reference:
Salesforce AI Specialist Documentation - Einstein Trust Layer Overview:
Explains how the Trust Layer masks sensitive data in prompts and re-inserts it after LLM processing to protect data privacy.
Salesforce Help - Data Masking and De-masking Process:
Details the masking of sensitive data before sending to the LLM and the de-masking process during the response journey.
Salesforce AI Specialist Exam Guide - Security and Compliance in AI:
Outlines the importance of data protection mechanisms like the Einstein Trust Layer in AI implementations.
Conclusion:
The Einstein Trust Layer ensures sensitive data is protected by masking it before sending any prompts to the LLM and then de-masking it during the response journey. This process allows Salesforce to generate useful and meaningful responses that include necessary sensitive information without exposing that data during the AI processing, thereby maintaining data security and compliance.

NEW QUESTION # 52
Anadministrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM data. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?

A. Dynamic grounding with secure data retrieval
B. Zero-data retention policy
C. Data masking

Answer: A

Explanation:
Dynamic grounding with secure data retrieval is a key feature in Salesforce'sEinstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allowsrelevant Salesforce datato be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
* Data maskingrefers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
* Zero-data retention policyensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.
References:
* Salesforce Developer Documentation onEinstein Trust Layer
* Salesforce Security Documentation for AI andData Privacy

NEW QUESTION # 53
An AI Specialist is setting up a new org and needs to ensure that users can create and execute prompt templates. The AI Specialist is unsure which roles are necessary for these tasks.
Which permission sets should the AI Specialist assign to users who need to create and execute prompt templates?

A. Data Cloud Admin for creating templates and Prompt Template User for executing templates
B. Prompt Template Manager for creating templates and Prompt Template User for executing templates
C. Prompt Template Manager for creating templates and Data Cloud Admin for executing templates

Answer: B

Explanation:
To effectively manage and use prompt templates, two distinct permission sets are required:
* Prompt Template Manager: This permission set allows users to create prompt templates. It provides the necessary access to define templates, which can be shared and utilized across the organization.
* Prompt Template User: This permission set is designed for users who need to execute the templates. It provides the ability to interact with pre-designed prompts and generate outcomes based on these templates.
TheData Cloud Adminpermission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.

NEW QUESTION # 54
Universal Containers (UC) wants to offer personalized service experiences and reduce agent handling time with Al-generated email responses, grounded in Knowledge base.
Which AI capability should UC use?

A. Einstein Generative Service Replies for Email
B. Einstein Email Replies
C. Einstein Service Replies for Email

Answer: C

Explanation:
For Universal Containers (UC) to offer personalized service experiences and reduce agent handling time using AI-generated responses grounded in the Knowledge base, the best solution is Einstein Service Replies for Email. This capability leverages AI to automatically generate responses to service-related emails based on historical data and the Knowledge base, ensuring accuracy and relevance while saving time for service agents.
Einstein Email Replies (option A) is more suited for sales use cases.
Einstein Generative Service Replies for Email (option C) could be a future offering, but as of now, Einstein Service Replies for Email is the correct choice for grounded, knowledge-based responses.
Reference:
Einstein Service Replies Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm

NEW QUESTION # 55
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