Question # 1
Universal Containers recently launched a pilot program to integrate conversational AI into its CRM business operations with Einstein Copilot.
How should the AI Specialist monitor Copilot's usability and the assignment of actions? | | A. Run a report on the Platform Debug Logs. | | B. Query the Copilot log data using the metadata API. | | C. Run Einstein Copilot Analytics. |
C. Run Einstein Copilot Analytics.
Explanation: To monitor Einstein Copilot's usability and the assignment of actions, the AI
Specialist should run Einstein Copilot Analytics. This feature provides insights into how often Copilot is used, the types of actions it is handling, and overall user engagement with the system. It’s the most effective way to track Copilot's performance and usage patterns.
Platform Debug Logs are not relevant for tracking user behavior or the assignment of Copilot actions.
Querying the Copilot log data via the Metadata API would not provide the necessary insights in a structured manner.
For more details, refer to Salesforce's Copilot Analytics documentation for tracking AI driven
interactions.
Question # 2
| Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates. Which type of flow should UC use? | | A. Data Cloud-triggered flow | | B. Template-triggered prompt flow | | C. Unified-object linking flow |
A. Data Cloud-triggered flow
Explanation:
In this scenario, Universal Containers wants to bring data from unified Data Cloud objects into prompt templates, and the best way to do that is through a Data Cloud-triggered flow. This type of flow is specifically designed to trigger actions based on data changes within Salesforce Data Cloud objects.
Data Cloud-triggered flows can listen for changes in the unified data model and automatically bring relevant data into the system, making it available for prompt templates. This ensures that the data is both real-time and up-to-date when used in generative AI contexts.
For more detailed guidance, refer to Salesforce documentation on Data Cloud-triggered flows and Data Cloud integrations with generative AI solutions.
Question # 3
| Universal Containers wants to be able to detect with a high level confidence if content generated by a large language model (LLM) contains toxic language. Which action should an Al Specialist take in the Trust Layer to confirm toxicity is being appropriately managed? | | A. Access the Toxicity Detection log in Setup and export all entries where is Toxicity Detected is true. | | B. Create a flow that sends an email to a specified address each time the toxicity score from the response exceeds a predefined threshold. | | C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores. |
C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores.
Explanation:
To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the AI Specialist should create a Trust Layer audit report with in Data Cloud. By using the toxicity detector type filter, the report can display toxic responses along with their respective toxicity scores, allowing Universal Containers to monitor and manage any toxic content generated with a high level of confidence.
Option C is correct because it enables visibility into toxic language detection with in the Trust Layer and allows for auditing responses for toxicity.
Option A suggests checking a toxicity detection log, but Salesforce provides more comprehensive options via the audit report.
Option B involves creating a flow, which is unnecessary for toxicity detection monitoring.
Question # 4
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? | | A. Call Summaries | | B. Einstein Sales Insights | | C. Call Explorer |
C. Call Explorer
Explanation: For analyzing voice and video call records to gain insights into competitor
mentions, coaching opportunities, and other key information,Call Exploreris the most
suitable feature.Call Explorer, a part ofEinstein Conversation Insights, enables sales
teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, includingcompetitor
mentionsand moments for coaching. These insights are vital for improving sales
performance by providing a clear understanding of the interactions during calls.
Call Summariesoffer a quick overview of a call but do not delve deep into
competitor mentions or coaching insights.
Einstein Sales Insightsfocuses more on pipeline and forecasting insights rather
than call-based analysis.
Question # 5
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? | | A. When the goal is to streamline customer support processes and improve response times | | B. When the main objective is to enhance data security and compliance measures | | C. When the focus is on optimizing marketing campaigns and strategies |
A. When the goal is to streamline customer support processes and improve response times
Explanation: Einstein Copilot implementation would be most advantageous in Salesforce
Service Cloud when the goal is to streamline customer support processes and improve response times. Einstein Copilot can assist agents by providing real-time suggestions, automating repetitive tasks, and generating contextual responses, thus enhancing service efficiency.
Option B (data security)is not the primary focus of Einstein Copilot, which is more about improving operational efficiency.
Option C (marketing campaigns)falls outside the scope of Service Cloud and Einstein Copilot’s primary benefits, which are aimed at improving customer service and case management.
For further reading, refer to Salesforce documentation on Einstein Copilot for Service Cloud and how it improves support processes.
Question # 6
| What is the role of the large language model (LLM) in executing an Einstein Copilot Action? | | A. Find similar requests and provideactions that need to be executed | | B. Identify the best matching actions and correct order of execution | | C. Determine a user's access and sort actions by priority to be executed |
B. Identify the best matching actions and correct order of execution
Explanation: In Einstein Copilot, the role of the Large Language Model (LLM) is to analyze user inputs and identify the best matching actions that need to be executed. It uses natural language understanding to break down the user’s request and determine the correct
sequence of actions that should be performed.
By doing so, the LLM ensures that the tasks and actions executed are contextually relevant
and are performed in the proper order. This process provides a seamless, AI-enhanced experience for users by matching their requests to predefined Salesforce actions or flows.
The other options are incorrect because:
A mentions finding similar requests, which is not the primary role of the LLM in this context.
C focuses on access and sorting by priority, which is handled more by security models and
governance than by the LLM.
Question # 7
| A data scientist needs to view and manage models in Einstein Studio. The data scientist also needs to create
prompt templates in Prompt Builder.
Which permission sets should an AI Specialist assign to the data scientist? | | A. Data Cloud Admin and Prompt Template Manager | | B. Prompt Template Manager and Prompt Template User | | C. Prompt Template User and Data Cloud Admin |
A. Data Cloud Admin and Prompt Template Manager
Explanation
To allow a data scientist to view and manage models in Einstein Studio and create prompt templates in
Prompt Builder, the AI Specialist should assign the Data Cloud Admin and Prompt Template Manager
permission sets.
Data Cloud Admin provides access to manage and oversee models within Einstein Studio.
Prompt Template Manager gives the user the ability to create and manage prompt templates within
Prompt Builder.
Option A is correct because it assigns the necessary permissions for both managing models and
creating prompt templates.
Option B and Option C are incorrect as they do not provide the correct combination of permissions for
managing models and building prompts.
References:
Salesforce Permissions Documentation: https://help.salesforce.com/s/articleView?id=sf.
perm_sets_overview.htm
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FAQs of Salesforce-AI-Specialist Exam
What is the Salesforce AI Specialist Exam?
Answer: The Salesforce AI Specialist exam tests your knowledge of integrating AI into Salesforce platforms to enhance customer experiences.
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Answer: Study Guides- Utilize the official Salesforce study guide and practice by taking Practice Questions using reliable sources like RealBraindumps.
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Answer: The time for the exam is 90 minutes, so you will have plenty of time to answer all the questions.
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Answer: Yes, you can retake, but you need to wait 14 days and pay a retake fee.
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Answer: Gaining such certification enhances career opportunities through the validation of skills in AI and Salesforce; better opportunities come hand in hand with better networking, increased salary rates, and much more in a present job.
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Answer: The exam consists of 60 multiple choice questions, and it lasts 90 minutes. For More information visit: https://trailhead.salesforce.com/en/credentials/aispecialist
What are the key topic areas of the Salesforce AI Specialist Certification?
Answer: The key topic areas include Einstein Trust Layer, Generative AI in CRM Applications, Prompt Builder, Einstein Copilot, and Model Builder.
How does Salesforce Einstein work?
Answer: Salesforce Einstein integrates AI capabilities into Salesforce, offering tools like Sales emails, Service replies, Einstein Copilot, Prompt Builder, and more.
What are the key topic areas covered in the Salesforce AI Specialist exam?
Answer: The Salesforce AI Specialist exam covers the following key areas: 1. Einstein Trust Layer (15%), 2. Generative AI in CRM Applications (17%), 3. Prompt Builder (37%), 4. Einstein Copilot (23%), 5. and Model Builder (8%).
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