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Free Salesforce-AI-Specialist Exam Braindumps (page: 14)

Page 13 of 39
PDF with 152 Questions

Universal Containers (UC) wants to enable its sales reps to explore opportunities that are similar to previously won opportunities by entering the utterance, "Show me other opportunities like this one."
How should UC achieve this in Einstein Copilot?

  1. Use the standard Copilot action.
  2. Create a custom Copilot action calling a flow.
  3. Create a custom Copilot action calling an Apex class.

Answer(s): A

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.



Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests.
What should an AI Specialist recommend to generate this email?

  1. Standard email marketing template using Apex or flows for matching interest in products
  2. Custom sales email template which is grounded with interest and product information
  3. Standard email draft with Einstein and choose standard email template

Answer(s): B

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.



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?

  1. Apex trigger
  2. SOQL
  3. Flows

Answer(s): C

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.



Universal Containers (UC) wants to assess Salesforce's generative features but has concerns over its company data being exposed to third- party large language models (LLMs). Specifically, UC wants the following capabilities to be part of Einstein's generative AI service. No data is used for LLM training or product improvements by third- party LLMs.
No data is retained outside of UC's Salesforce org.
The data sent cannot be accessed by the LLM provider.
Which property of the Einstein Trust Layer should the AI Specialist highlight to UC that addresses these requirements?

  1. Prompt Defense
  2. Zero-Data Retention Policy
  3. Data Masking

Answer(s): B

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






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