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HZ SPEC AI Description: HZ SPEC AI Author: Khalid Kareem Other tests from this author Creation Date: 24/12/2024 Category: Others Number of questions: 28 |
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Which use case is best supported by Salesforce Einstein Copilot's capabilities? Bring together a conversational interface for interacting with AI for all Salesforce users, such as developers and ecommerce retailers. Enable data scientists to train predictive AI models with historical CRM data using built-in machine learning capabilities. Enable Salesforce admin users to create and train custom large language models (LLMs) using CRM data. What is the correct process to leverage Prompt Builder in a Salesforce org? Enable the target object for generative prompting, develop the prompt within the prompt workspace, select records to fine-tune and ground the response, enable the Trust Layer, and associate the prompt to an action. Select the appropriate prompt template type to use, select one of Salesforce's standard prompts, determine the object to associate the prompt, select a record to validate against, and associate the prompt to an action. Select the appropriate prompt template type to use, develop the prompt within the prompt workspace, select resources to dynamically insert CRM-derived grounding data, pick the model to use, and test and validate the generated responses. An AI Specialist is tasked with creating a prompt template for a sales team. The template needs to generate a summary of all related opportunities for a given Account. Which grounding technique should the AI Specialist use to include data from the related list of opportunities in the prompt template? Use formula fields to reference the Einstein related list of opportunities. Use merge fields to reference the default related list of opportunities. Use the merge fields to reference a custom related list of opportunities. Universal Containers (UC) uses Salesforce Service Cloud to support its customers and agents handling cases. UC is considering implementing Einstein Copilot and extending Service Cloud to mobile users. When would Einstein Copilot implementation be most advantageous? When the goal is to streamline customer support processes and improve response times When the main objective is to enhance data security and compliance measures When the focus is on optimizing marketing campaigns and strategies. How does the Einstein Trust Layer ensure that sensitive data Is protected while generating useful and meaningful responses? Masked data will be de-masked during response journey. Responses that do not meet the relevance threshold will be automatically rejected. Masked data will be de-masked during request journey. An AI Specialist needs to create a prompt template to fill a custom field named Latest Opportunities Summary on the Account object with information from the three most recently opened opportunities. How should the AI Specialist gather the necessary data for the prompt template? Create a flow to retrieve the opportunity information. Select the Account Opportunity object as a resource when creating the prompt template. Select the latest Opportunities related list as a merge field. Universal Containers (UC) recently rolled out Einstein Generative Al capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information. What is a possible explanation for the poor prompt performance? The data being used for grounding Is incorrect or incomplete. The prompt template version is incompatible with the chosen LLM. The Einstein Trust Layer is incorrectly configured. What is best practice when refining Einstein Copilot custom action instructions? Provide examples of user messages that are expected to trigger the action. Use consistent introductory phrases and verbs across multiple action instructions. Specify the persona who will request the action. Universal Containers (UC) has a legacy system that needs to integrate with Salesforce. UC wishes to create a digest of account action plans using the generative API feature. Which API service should UC use to meet this requirement? REST API SOAP API Metadata API. An AI Specialist has created a copilot custom action using flow as the reference action type. However, it is not delivering the expected results to the conversation preview, and therefore needs troubleshooting. What should the AI Specialist do to identify the root cause of the problem? In Copilot Builder within the Dynamic Panel, confirm selected action and observe the values in Input and Output sections. In Copilot Builder, verify the utterance entered by the user and review session event logs for debug information. In Copilot Builder within the Dynamic Panel, turn on dynamic debugging to show the inputs and outputs. Universal Containers (UC) wants to enable its sales team to use Al to suggest recommended products from its catalog. Which type of prompt template should UC use? Record summary prompt template Email generation prompt template Flex prompt template. A sales rep at Universal Containers is extremely busy and sometimes will have very long sales calls on voice and video calls and might miss key details. They are just starting to adopt new generative AI features. Which Einstein Generative AI feature should an AI Specialist recommend to help the rep get the details they might have missed during a conversation? Call Summary Call Explorer Sales Summary. A service agent Is looking at a custom object that stores travel information. They recently received a weather alert and now need to cancel flights for the customers that are related with this itinerary. The service agent needs to review the Knowledge articles about canceling and rebooking the customer flights. Which Einstein Copilot capability helps the agent accomplish this? Execute tasks based on available actions, answering questions using information from accessible Knowledge articles. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights. Invoke a flow which makes a call to external data to create a Knowledge article. 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? Sales Email Field Generation Record Summary. A Salesforce Administrator is exploring the capabilities of Einstein Copilot to enhance user interaction within their organization. They are particularly interested in how Einstein Copilot processes user requests and the mechanism it employs to deliver responses. The administrator is evaluating whether Einstein Copilot directly interfaces with a large language model (LLM) to fetch and display responses to user inquiries, facilitating a broad range of requests from users. How does Einstein Copilot handle user requests In Salesforce? Einstein Copilot will trigger a flow that utilizes a prompt template to generate the message. Einstein Copilot will perform an HTTP callout to an LLM provider. Einstein Copilot analyzes the user's request and LLM technology is used to generate and display the appropriate response. How does the Einstein Trust Layer ensure that sensitive data Is protected while generating useful and meaningful responses? Masked data will be de-masked during response journey. Masked data will be de-masked during request journey. Responses that do not meet the relevance threshold will be automatically rejected. Universal Containers (UC) wants to enable its sales team to get insights into product and competitor names mentioned during calls. How should UC meet this requirement? Enable Einstein Conversation Insights, assign permission sets, define recording managers, and customize insights with up to 50 competitor names.. Enable Einstein Conversation Insights, connect a recording provider, assign permission sets, and customize insights with up to 25 products. Enable Einstein Conversation Insights, enable sales recording, assign permission sets, and customize insights with up to 50 products. A service agent is looking at a custom object that stores travel information. They recently received a weather alert and now need to cancel flights for the customers that are related with this itinerary. The service agent needs to review the Knowledge articles about canceling and rebooking the customer flights. Which Einstein Copilot capability helps the agent accomplish this? Execute tasks based on available actions, answering questions using information from accessible Knowledge articles. Invoke a flow which makes a call to external data to create a Knowledge article. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights. An AI Specialist has created a copilot custom action using flow as the reference action type. However, it is not delivering the expected results to the conversation preview, and therefore needs troubleshooting. What should the AI Specialist do to identify the root cause of the problem? In Copilot Builder within the Dynamic Panel, turn on dynamic debugging to show the inputs and outputs. In Copilot Builder within the Dynamic Panel, confirm selected action and observe the values in Input and Output sections. In Copilot Builder, verify the utterance entered by the user and review session event logs for debug information. A support team handles a high volume of chat interactions and needs a solution to provide quick, relevant responses to customer inquiries. Responses must be grounded in the organization's knowledge base to maintain consistency and accuracy. Which feature in Einstein for Service should the support team use? Einstein Service Replies Einstein Reply Recommendations Einstein Knowledge Recommendations. Universal Containers wants to reduce overall agent handling time by minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields. Which combination of Einstein for Service features enables this effort? Einstein Service Replies and Work Summaries Einstein Reply Recommendations and Case Summaries Einstein Reply Recommendations and Case Classification. Universal Containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, Competitor Analysis. All sales users have the same profile but one user cannot see the generative Al-enabled field icon next to the summary field. What is the most likely cause of the issue? The user does not have the Prompt Template User permission set assigned. The prompt template associated with summary field is not activated for that user. The user does not have the field Generative AI User permission set assigned. Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. The goal is to enhance the team's performance by identifying areas for improvement and competitive intelligence. Which feature provides insights about competitor mentions and coaching opportunities? Call Summaries Einstein Sales Insights Call Explorer. An AI Specialist at Universal Containers (UC) Is tasked with creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements. Which prompt template type should the AI Specialist use and which consideration should they review? Flex, and that Dynamic Fields is enabled Field Generation, and that Dynamic Fields is enabled Field Generation, and that Dynamic Forms is enabled. Universal Containers (UC) has a mature Salesforce org with a lot of data in cases and Knowledge articles. UC is concerned that there are many legacy fields, with data that might not be applicable for Einstein AI to draft accurate email responses. Which solution should UC use to ensure Einstein AI can draft responses from a defined data source? Service AI Grounding Work Summaries Service Replies. Universal Containers (UC) is using Einstein Generative AI to generate an account summary. UC aims to ensure the content is safe and inclusive, utilizing the Einstein Trust Layer's toxicity scoring to assess the content's safety level. What does a safety category score of 1 indicate in the Einstein Generative Al Toxicity Score? Not safe Safe Moderately safe. Universal Containers is interested in improving the sales operation efficiency by analyzing their data using Al-powered predictions in Einstein Studio. Which use case works for this scenario? Predict customer sentiment toward a promotion message. Predict customer lifetime value of an account. Predict most popular products from new product catalog. What is the correct process to leverage Prompt Builder in a Salesforce org? Select the appropriate prompt template type to use, select one of Salesforce's standard prompts, determine the object to associate the prompt, select a record to validate against, and associate the prompt to an action. Select the appropriate prompt template type to use, develop the prompt within the prompt workspace, select resources to dynamically insert CRM-derived grounding data, pick the model to use, and test and validate the generated responses. Enable the target object for generative prompting, develop the prompt within the prompt workspace, select records to fine-tune and ground the response, enable the Trust Layer, and associate the prompt to an action. |
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