Deck 1 Flashcards
(40 cards)
- What is the primary purpose of the Einstein Trust Layer in Salesforce AI implementations?
It ensures data privacy and governance by restricting sensitive information from being processed by AI.
- Which Salesforce feature is used to automatically generate personalized customer communications using generative AI?
Einstein Generative AI for CRM Applications.
- In Salesforce, which tool allows the creation of custom prompt templates for AI-generated content?
Prompt Builder.
- What is the function of Agentforce Tools in the Salesforce AI Specialist context?
They integrate AI‐driven insights into customer service and sales processes.
- Which feature should a Salesforce AI Specialist use to develop predictive models based on historical data?
Model Builder.
- What is data grounding in the context of Salesforce AI implementations?
It is the process of integrating real-time, contextual data into AI prompts to improve accuracy.
- How does Einstein Copilot enhance user interactions within Salesforce?
It provides AI-generated suggestions and automates routine tasks based on user input.
- What is a key benefit of using Prompt Builder in Salesforce?
It streamlines the creation of consistent and customizable AI prompt templates.
- Which setting in Einstein Copilot allows for the enrichment of event logs with conversation data?
The ‘Enrich event logs with conversation data’ setting.
- How can Salesforce ensure that sensitive fields are not processed by AI tools?
By using the Einstein Trust Layer to mask or exclude sensitive data.
- What type of Salesforce data is typically integrated into AI prompts for personalized customer interactions?
CRM data, such as customer profiles, transaction history, and recent interactions.
- Which Salesforce feature is designed to automatically log client interactions such as emails and meetings?
Einstein Activity Capture.
- What role does the Salesforce System Administrator play in managing AI tools?
They configure and manage the integration and settings of AI features within Salesforce.
- How does using real-time CRM data improve AI-generated communications?
It ensures that the content is up-to-date and tailored to the customer’s recent activity.
- What is the significance of model compatibility when integrating external AI models into Salesforce?
It ensures seamless integration and optimal performance of the AI features.
- What is the purpose of creating a custom copilot action in Salesforce?
To execute unique business processes that standard AI actions do not cover.
- Which feature allows Salesforce to automatically generate summaries of case details after resolution?
Einstein Case Wrap-Up.
- How does integrating CRM data with AI prompts impact email communications?
It personalizes emails by incorporating recent customer data for more relevant content.
- What is a key consideration when configuring prompt templates that reference related lists from Salesforce records?
Understanding the maximum number of related list merge fields supported.
- What is one potential reason for poor AI prompt performance in Salesforce implementations?
Using incorrect or incomplete grounding data.
- Which Salesforce AI tool provides recommendations for the next best action based on data insights?
Einstein Next Best Action.
- How does a custom generative model differ from the standard generative model in Salesforce?
A custom model is tailored with specific data and configurations to meet unique business needs.
- In Einstein’s toxicity scoring, what does a safety category score of 1 indicate?
It indicates that the content is safe.
- Why is validating pre-training data crucial when building a custom AI model in Salesforce?
Because the quality and relevance of the pre-training data directly affect the model’s accuracy.
