AI Associate Salesforce-AI-Specialist Updated Exam

For improvingsales operations efficiency,Einstein Studiois ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predictingcustomer lifetime value, which helps sales teams focus on high-value accounts and make more informed decisions.Customer lifetime value (CLV)predictions can optimize strategies around customer retention, cross-selling, and long-term engagement.

Option Bis the correct choice as predicting customer lifetime value is a well-established use case for AI in sales.

Option A(customer sentiment) is typically handled through NLP models, whileOption C(product popularity) is more of a marketing analysis use case.

References:

Salesforce Einstein Studio Use Case Overview:

The primary function of theplanner servicein theEinstein Copilotsystem is toidentify copilot actionsthat should be taken in response to user utterances. This service is responsible for analyzing the conversation and determining the appropriate actions (such as querying records, generating a response, or taking another action) that theEinstein Copilotshould perform based on user input.

To enableUniversal Containersservice agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is tocreate a custom copilot action that calls the flow. This action will allowEinstein Copilotto interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.

Option Bis correct because it enables integration betweenEinstein Copilotand the flow that connects to Oracle ERP.

Option A(Flex prompt template) is more suited for static responses and not for invoking flows.

Option C(Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.

References:

Salesforce Einstein Copilot Actions:

Universal Containers needs to generate a sales proposal using data from multiple unrelated standard and custom objects within a prompt template. The most effective way to achieve this is by using aFlex template.

Flex templates in Salesforce allow AI specialists to create prompt templates that can accept inputs from multiple sources, including various standard and custom objects. This flexibility enables the direct use of data from unrelated objects without the need to create intermediary custom objects or complex flows.

References:

Salesforce AI Specialist Documentation - Flex Templates:Explains how Flex templates can be utilized to incorporate data from multiple sources, providing a flexible solution for complex data requirements in prompt templates.