Salesforce Salesforce-AI-Specialist Exam With Confidence Using Practice Dumps

Einstein Copilot currently supports various actions like creating and updating records but does not support theDelete Recordaction. Therefore, the user's request to delete activities from the past 7 days cannot be fulfilled using Einstein Copilot.

Unsupported Action:The inability to delete records is due to the current limitations of Einstein Copilot's supported actions. It is designed to assist with tasks like data retrieval, creation, and updates, but for security and data integrity reasons, it does not facilitate the deletion of records.

User Permissions:Even if the user has the necessary permissions to delete records within Salesforce, Einstein Copilot itself does not have the capability to execute delete operations.

References:

Salesforce AI Specialist Documentation -Einstein Copilot Supported Actions:

Lists the actions that Einstein Copilot can perform, noting the absence of delete operations.

Salesforce Help -Limitations of Einstein Copilot:

Highlights current limitations, including unsupported actions like deleting records.

For Field Generation prompt templates to display the Sparkle icon (indicating AI-generated content), the target field must be explicitly associated with the prompt template on the Lightning page layout. Even if the prompt template is activated, failing to add the field to the page layout and link it to the templatewill result in the field behaving as a standard field. Salesforce documentation emphasizes that page layout configuration is mandatory to enable AI-driven field interactions.

Reactivating the layout (A) is unnecessary unless the layout itself was modified after activation.

Case objects are supported for Field Generation (B is incorrect).

To integrate inferences from an XGBoost model into Salesforce's Data Cloud as a stand-alone Data Model Object (DMO):

Create the Serving Endpoint in Databricks:

The serving endpoint is necessary to make the trained model available for real-time inference. Databricks provides tools to host and expose the model via an endpoint.

Configure the Model Using Model Builder:

After creating the endpoint, the AI Specialist should configure it within Einstein Studio'sModel Builder, which integrates external endpoints with Salesforce Data Cloud for processing and storing inferences as DMOs.

Option B: Serving endpoints are not created in Einstein Studio; they are set up in external platforms like Databricks before integration.

Option C: A Python SDK connector is not used to bring model inferences into Salesforce Data Cloud; Model Builder is the correct tool.