NEW SALESFORCE-AI-SPECIALIST TEST FEE - SALESFORCE-AI-SPECIALIST TRAINING TOOLS

New Salesforce-AI-Specialist Test Fee - Salesforce-AI-Specialist Training Tools

New Salesforce-AI-Specialist Test Fee - Salesforce-AI-Specialist Training Tools

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.
Topic 2
  • Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Topic 3
  • Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.
Topic 4
  • Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Topic 5
  • Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.

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Salesforce Certified AI Specialist Exam Sample Questions (Q12-Q17):

NEW QUESTION # 12
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. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
  • B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
  • C. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.

Answer: B

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.
Reference:
Salesforce Einstein Trust Layer Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm


NEW QUESTION # 13
An AI Specialist implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads basedon their interactions and data stored in Salesforce. The AI Specialist needsto 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. Automatic grounding using Draft with Einstein feature
  • C. Ground with Apex Merge Fields

Answer: A

Explanation:
ForEinstein Sales Emailsto 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 isGround 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 Fieldsensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
* Apex Merge Fieldsare typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
* Automatic grounding using Draft with Einsteinis a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data likeRecord Merge Fields.
References:
* Salesforce Einstein Sales Emails Documentation:https://help.salesforce.com/s/articleView?id=release- notes.rn_einstein_sales_emails.htm


NEW QUESTION # 14
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. Data masking
  • B. Zero-data retention policy
  • C. Dynamic grounding with secure data retrieval

Answer: C

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 # 15
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. Prompt Template Manager and Prompt Template User
  • B. Prompt Template User and Data Cloud Admin
  • C. Data Cloud Admin and Prompt Template Manager

Answer: C

Explanation:
To allow a data scientist to view and manage models in Einstein Studio and create prompt templates in Prompt Builder, the AI Specialist should assign the Data Cloud Admin and Prompt Template Manager permission sets.
Data Cloud Admin provides access to manage and oversee models within Einstein Studio.
Prompt Template Manager gives the user the ability to create and manage prompt templates within Prompt Builder.
Option A is correct because it assigns the necessary permissions for both managing models and creating prompt templates.
Option B and Option C are incorrect as they do not provide the correct combination of permissions for managing models and building prompts.
Reference:
Salesforce Permissions Documentation: https://help.salesforce.com/s/articleView?id=sf.perm_sets_overview.htm


NEW QUESTION # 16
Leadership needs to populate a dynamic form field with a summary or description created by a large language model (LLM) to facilitate more productive conversations with customers. Leadership also wants to keep a human in the loop to be considered in their AI strategy.
Which prompt template type should the AI Specialist recommend?

  • A. Sales Email
  • B. Record Summary
  • C. Field Generation

Answer: C

Explanation:
The correct answer is Field Generation because this template type is designed to dynamically populate form fields with content generated by a large language model (LLM). In this scenario, leadership wants a dynamic form field that contains a summary or description generated by AI to aid customer interactions. Additionally, they want to keep a human in the loop, meaning the generated content will likely be reviewed or edited by a person before it's finalized, which aligns with the Field Generation prompt template.
* Field Generation: This prompt type allows you to generate content for specific fields in Salesforce, leveraging large language models to create dynamic and contextual information. It ensures that AI content is available within the record where needed, but it allows human oversight or review, supporting the "human-in-the-loop" strategy.
* Sales Email: This prompt type is mainly used for generating email content for outreach or responses, which doesn't align directly with populating fields in a form.
* Record Summary: While this option might seem close, it is typically used to summarize entire records for high-level insights rather than filling specific fields with dynamic content based on AI generation.
Salesforce AI Specialist References:
* You can explore more about these prompt templates and AI capabilities through Salesforce documentation and official resources on Prompt Builder: https://help.salesforce.com/s/articleView?
id=sf.prompt_builder_templates_overview.htm


NEW QUESTION # 17
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