Question # 1
Universal Containers’ current AI data masking rules do not align with organizational privacy
and security policies and requirements.
What should an AI Specialist recommend to resolve the issue? | | A. Enable data masking for sandbox refreshes. | | B. Configure data masking in the Einstein Trust Layer setup. | | C. Add new data masking rules in LLM setup. |
B. Configure data masking in the Einstein Trust Layer setup.
Explanation: WhenUniversal Containers' AI data masking rulesdo not meet
organizational privacy and security standards, the AI Specialist should configure thedata
maskingrules within theEinstein Trust Layer. TheEinstein Trust Layerprovides a secure
and compliant environment where sensitive data can be masked or anonymized to adhere
to privacy policies and regulations.
Option A, enabling data masking for sandbox refreshes, is related to sandbox
environments, which are separate from how AI interacts with production data.
Option C, adding masking rules in the LLM setup, is not appropriate because data
masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the
AI model and ensures compliance with privacy regulations.
Question # 2
Universal Containers is considering leveraging the Einstein Trust Layer in conjunction with Einstein Generative AI Audit Data.
Which audit data is available using the Einstein Trust Layer? | | A. Response accuracy and offensiveness score | | B. Hallucination score and bias score | | C. Masked data and toxicity score |
C. Masked data and toxicity score
Explanation:
Universal Containers is considering the use of the Einstein Trust Layer along with Einstein
Generative AI Audit Data. The Einstein Trust Layer provides a secure and compliant way to
use AI by offering features like data masking and toxicity assessment.
The audit data available through the Einstein Trust Layer includes information about
masked data—which ensures sensitive information is not exposed—and thetoxicity score
, which evaluates the generated content for inappropriate or harmful language.
Question # 3
A data scientist needs to view and manage models in Einstein Studio. The data scientist
also needs to create prompt templates in Prompt Builder.
Which permission sets should an AI Specialist assign to the data scientist? | | A. Data Cloud Admin and Prompt Template Manager | | B. Prompt Template Manager and Prompt Template User | | C. Prompt Template User and Data Cloud Admin |
A. Data Cloud Admin and Prompt Template Manager
Explanation: To allow a data scientist to view and manage models inEinstein Studioand
create prompt templates inPrompt Builder, the AI Specialist should assign theData Cloud
AdminandPrompt Template Managerpermission sets.
Data Cloud Adminprovides access to manage and oversee models withinEinstein
Studio.
Prompt Template Managergives the user the ability to create and manage prompt
templates withinPrompt Builder.
Option Ais correct because it assigns the necessary permissions for both
managing models and creating prompt templates.
Option BandOption Care incorrect as they do not provide the correct combination
of permissions for managing models and building prompts.
Question # 4
Universal Containers wants to use an external large language model (LLM) in Prompt Builder.
What should an AI Specialist recommend? | | A. Use Apex to connect to an external LLM and ground the prompt. | | B. Use BYO-LLM functionality in Einstein Studio, | | C. Use Flow and External Services to bring data from an external LLM. |
B. Use BYO-LLM functionality in Einstein Studio,
Explanation: Bring Your Own Large Language Model (BYO-LLM)functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem. Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.
Option Bis the correct choice as Einstein Studio provides a built-in feature to work with external models.
Option A suggests using Apex, but BYO-LLM functionality offers a more streamlined solution.
Option C focuses on Flow and External Services, which is more about data integration and isn't ideal for working with LLMs.
Question # 5
Universal Containers tests out a new Einstein Generative AI feature for its sales team to
create personalized and contextualized emails for its customers. Sometimes, users find that
the draft email contains place holders for attributes that could have been derived from the
recipient's contact record.
What is the most likely explanation for why the draft email shows these placeholders? | | A. The user does not have Einstein Sales Emails permission assigned. | | B. The user does not have permission to access the fields. | | C. The user's locale language is not supported by Prompt Builder. |
B. The user does not have permission to access the fields.
Explanation: When usingEinstein Generative AIto create personalized emails, if
placeholders appear in the draft email where data from a recipient'sContactrecord should
be, the most likely reason is that theuser lacks permission to access the necessary
fields. Salesforce's field-level security may prevent users from viewing or utilizing certain
data fields, resulting in placeholders being shown instead of the actual values.
Option Bis correct because missing field permissions will cause placeholders in
email drafts.
Option A(missing Einstein Sales Emails permission) is unlikely, as this would
prevent email generation altogether, not just placeholders.
Option C(locale language issues) would more likely affect language-specific
issues, not field placeholders.
Question # 6
| 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 |
C. Prompt Defense
Explanation: Prompt Defenseis a feature in theEinstein Trust Layerthat helps minimize
the risks ofjailbreakingandprompt injection attacks. These attacks occur when malicious
users try to manipulate the AI model by providing unintended inputs.Prompt Defense
ensures 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 documentationon
Prompt Defenseand security features.
Question # 7
| Where should the AI Specialist go to add/update actions assigned to a copilot? | | A. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab | | B. Copilot Actions page or Global Actions | | C. Copilot Detail page, Global Actions, or the record page for the copilot action |
A. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab
Explanation:
To add or update actions assigned to a copilot, an AI Specialist can manage this through several areas:
Copilot Actions Page: This is the central location where copilot actions are managed and configured.
Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
The other options are incorrect:
B) misses the Copilot Action Library, which is crucial for managing actions.
C) includes the Copilot Detail page, which isn't the primary place for action management.
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FAQs of Salesforce-AI-Specialist Exam
What is the Salesforce AI Specialist Exam?
Answer: The Salesforce AI Specialist exam tests your knowledge of integrating AI into Salesforce platforms to enhance customer experiences.
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Answer: Study Guides- Utilize the official Salesforce study guide and practice by taking Practice Questions using reliable sources like RealBraindumps.
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Answer: You must score at least 73% or above to pass the Salesforce AI Specialist Exam.
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Answer: Salesforce-AI-Specialist exam typically costs $200, but it all depends upon the location.
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Answer: There will be 60 multiple-choice questions present in the Salesforce AI Specialist exam.
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Answer: The time for the exam is 90 minutes, so you will have plenty of time to answer all the questions.
Can I attempt the Salesforce AI Specialist Exam again if I fail?
Answer: Yes, you can retake, but you need to wait 14 days and pay a retake fee.
What are the benefits of obtaining a Salesforce AI Specialist certification?
Answer: Gaining such certification enhances career opportunities through the validation of skills in AI and Salesforce; better opportunities come hand in hand with better networking, increased salary rates, and much more in a present job.
Do you need to fulfill any requirements before you take the Salesforce AI Specialist exam?
Answer: While there are no strict prerequisites, hands-on experience with AI and Salesforce is recommended.
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Answer: The exam consists of 60 multiple choice questions, and it lasts 90 minutes. For More information visit: https://trailhead.salesforce.com/en/credentials/aispecialist
What are the key topic areas of the Salesforce AI Specialist Certification?
Answer: The key topic areas include Einstein Trust Layer, Generative AI in CRM Applications, Prompt Builder, Einstein Copilot, and Model Builder.
How does Salesforce Einstein work?
Answer: Salesforce Einstein integrates AI capabilities into Salesforce, offering tools like Sales emails, Service replies, Einstein Copilot, Prompt Builder, and more.
What are the key topic areas covered in the Salesforce AI Specialist exam?
Answer: The Salesforce AI Specialist exam covers the following key areas: 1. Einstein Trust Layer (15%), 2. Generative AI in CRM Applications (17%), 3. Prompt Builder (37%), 4. Einstein Copilot (23%), 5. and Model Builder (8%).
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