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質問 # 55
Where should the AI Specialist go to add/update actions assigned to a copilot?
- A. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab
- B. Copilot Actions page or Global Actions
- C. Copilot Detail page, Global Actions, or the record page for the copilot action
正解：A
解説：
To add or update actions assigned to a copilot, an AI Specialist can manage this through several areas:
* Copilot Actions Page: This is the central location where copilot actions are managed and configured.
* Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
* Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
The other options are incorrect:
* Bmisses the Copilot Action Library, which is crucial for managing actions.
* Cincludes the Copilot Detail page, which isn't the primary place for action management.
References:
* Salesforce Documentation onManaging Copilot Actions
* Salesforce AI Specialist Guide onCopilot Action Management
質問 # 56
Universal Containers is considering leveraging the Einstein Trust Layer in conjunction with Einstein Generative AI Audit Data.
Which audit data is available using the Einstein Trust Layer?
- A. Response accuracy and offensiveness score
- B. Masked data and toxicity score
- C. Hallucination score and bias score
正解：B
解説：
Universal Containers is considering the use of the Einstein Trust Layer along with Einstein Generative AI Audit Data. The Einstein Trust Layer provides a secure and compliant way to use AI by offering features like data masking and toxicity assessment.
The audit data available through the Einstein Trust Layer includes information about masked data-which ensures sensitive information is not exposed-and the toxicity score, which evaluates the generated content for inappropriate or harmful language.
Reference:
Salesforce AI Specialist Documentation - Einstein Trust Layer: Details the auditing capabilities, including logging of masked data and evaluation of generated responses for toxicity to maintain compliance and trust.
質問 # 57
Universal Containers wants to implement a solution in Salesforce with a custom UX that allows users to enter a sales order number.
Subsequently, the system will invoke a custom prompt template to create and display a summary of the sales order header and sales order details.
Which solution should an AI Specialist implement to meet this requirement?
- A. Create an autolaunched flow and invoke the prompt template using the standard "Prompt Template" flow action.
- B. Create a screen flow to collect sales order number and invoke the prompt template using the standard
"Prompt Template" flow action. - C. Create a template-triggered prompt flow and invoke the prompt template using the standard "Prompt Template" flow action.
正解：B
解説：
To implement a solution where users enter a sales order number and the system generates a summary, the AI Specialist should create ascreen flowto collect the sales order number and invoke the prompt template. The standard"Prompt Template" flow actioncan then be used to trigger the custom prompt, providing a summary of the sales order header and details.
* Option B, creating a template-triggered prompt flow, is not necessary for this scenario because the requirement is to directly collect input through a screen flow.
* Option C, using an autolaunched flow, would be inappropriate here because the solution requires user interaction (entering a sales order number), which is best suited to a screen flow.
Salesforce AI Specialist References:For further guidance on creating prompt templates with flows:
https://help.salesforce.com/s/articleView?id=sf.prompt_template_flow_integration.htm
質問 # 58
What is the main purpose of Prompt Builder?
- A. A tool for developers to use in Visual Studio Code that creates prompts for Apex programming, assisting developers in writing code more efficiently.
- B. A tool that enables companies to create reusable prompts for large language models (LLMs), bringing generative AI responses to their flow of work
- C. A tool within Salesforce offering real-time Al-powered suggestions and guidance to users, Improving productivity and decision-making.
正解：B
解説：
Prompt Builderis designed to help organizations create and configure reusable prompts for large language models (LLMs). By integratinggenerative AIresponses into workflows,Prompt Builderenables customization of AI prompts that interact with Salesforce data and automate complex processes. This tool is especially useful for creating tailored and consistent AI-generated content in various business contexts, including customer service and sales.
* It is not a tool forApex programming(as in option A).
* It is also not limited to real-time suggestions as mentioned in option C. Instead, it provides a flexible way for companies to manage and customize how AI-driven responses are generated and used in their workflows.
References:
* Salesforce Prompt Builder Overview:https://help.salesforce.com/s/articleView?id=sf.prompt_builder.
htm
質問 # 59
An AI Specialist configured Data Masking within the Einstein Trust Layer.
How should the AI Specialist begin validating that the correct fields are being masked?
- A. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
- B. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.
- C. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
正解：A
解説：
To begin validating that the correct fields are being masked inEinstein Trust Layer, the AI Specialist should request theEinstein Generative AI Audit Datafrom theSecurity sectionof the Salesforce Setup menu. This audit data allows the AI Specialist to see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected.
* Option Bis correct because it allows for the retrieval of audit data that can be used to validate data masking.
* Option A(Flow Debugger) andOption C(Einstein Feedback) do not relate to validating field masking in the context of theEinstein Trust Layer.
References:
* Salesforce Einstein Trust Layer Documentation:https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_audit.htm
質問 # 60
Before activating a custom copilot action, an AI Specialist would like is to understand multiple real-world user utterances to ensure the action being selected appropriately.
Which tool should the AI Specialist recommend?
- A. Einstein Copilot
- B. Copilot Builder
- C. Model Playground
正解：B
解説：
To understand multiple real-world user utterances and ensure the correct action is selected before activating a custom copilot action, the recommended tool isCopilot Builder. This tool allows AI Specialists to design and test conversational actions in response to user inputs, helping ensure the copilot can accurately handle different user queries and phrases.Copilot Builderprovides the ability to test, refine, and improve actions based on real-world utterances.
* Option Cis correct asCopilot Builderis designed for configuring and testing conversational actions.
* Option A(Model Playground) is used for testing models, not user utterances.
* Option B(Einstein Copilot) refers to the conversational interface but isn't the right tool for designing and testing actions.
References:
* Salesforce Copilot Builder Overview:https://help.salesforce.com/s/articleView?id=sf.
einstein_copilot_builder.htm
質問 # 61
Universal Containers is using Einstein Copilot for Sales to find similar opportunities to help close deals faster. The team wants to understand the criteria used by the copilot to match opportunities.
What is one criteria that Einstein Copilot for Sales uses to match similar opportunities?
- A. Matched opportunities were created in the last 12 months.
- B. Matched opportunities have a status of Closed Won from last 12 months.
- C. Matched opportunities are limited to the same account.
正解：B
解説：
When Einstein Copilot for Sales matches similar opportunities, one of the primary criteria used is whether the opportunities have a status of Closed Won within the last 12 months. This is a key factor in identifying successful patterns that could help close current deals. By focusing on opportunities that have been recently successful, Einstein Copilot can provide relevant insights and suggestions to sales reps to help them close similar deals faster.
For more information, review Salesforce Einstein Copilot documentation related to opportunity matching and sales success patterns.
質問 # 62
An AI Specialist built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors.
What is the cause of the random nature of this error?
- A. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
- B. The number of tokens generated by the dynamic nature of the prompt template will vary by record.
- C. The number of tokens that can be processed by the LLM varies with total user demand.
正解：B
解説：
The reason behind the token limit errors lies in the dynamic nature of the prompt template used in Field Generation. In Salesforce's AI generative models, each prompt and its corresponding output are subject to a token limit, which encompasses both the input and output of the large language model (LLM). Since the prompt template dynamically adjusts based on the specific data of each record, the number of tokens varies per record. Some records may generate longer outputs based on their data attributes, pushing the token count beyond the allowable limit for the LLM, resulting in token limit errors.
This behavior explains why users experience random failures-it is dependent on the specific data used in each case. For certain records, the combined input and output may fall within the token limit, while for others, it may exceed it. This variation is intrinsic to how dynamic templates interact with large language models.
Salesforce provides guidance in their documentation, stating that prompt template design should take into account token limits and suggests testing with varied records to avoid such random errors. It does not mention switching to Flex template type as a solution, nor does it suggest that token limits fluctuate with user demand.
Token limits are a constant defined by the model itself, independent of external user load.
References:
* Salesforce Developer Documentation onToken Limits for Generative AI Models
* Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources)
質問 # 63
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?
- A. Predict most popular products from new product catalog.
- B. Predict customer lifetime value of an account.
- C. Predict customer sentiment toward a promotion message.
正解：B
解説：
For improving sales operations efficiency, Einstein Studio is ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predicting customer 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 B is 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, while Option C (product popularity) is more of a marketing analysis use case.
Reference:
Salesforce Einstein Studio Use Case Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_overview
質問 # 64
Universal Containers (UC) is experimenting with using public Generative AI models and is familiar with the language required to get the information it needs. However, it can be timeconsuming for both UC's salesand service reps to type in the prompt to get the information they need, and ensure prompt consistency.
Which Salesforce feature should a Salesforce AI Specialist recommend to address these concerns?
- A. Einstein Prompt Builder and Prompt Templates
- B. Einstein Copilot Action: Query Records
- C. Einstein Recommendation Builder
正解：A
解説：
ForUniversal Containers (UC), to reduce the time and ensure prompt consistency when using public generative AI models, the recommended feature isEinstein Prompt Builder and Prompt Templates. This feature allows teams to createreusable and consistent promptsfor generative AI tasks, ensuring that all users receive uniform responses without having to type in detailed prompts manually every time.
* Einstein Prompt Buildersimplifies the creation of prompts, andPrompt Templatesstandardize the inputs, saving time for sales and service reps.
* Option A (Einstein Recommendation Builder)is more focused on recommendations, not prompt standardization.
* Option B (Einstein Copilot Action: Query Records)is for querying records, not generating AI-driven prompts.
References:
* Salesforce Prompt Builder Overview:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_overview.htm
質問 # 65
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?
- A. Email generation prompt template
- B. Record summary prompt template
- C. Flex prompt template
正解：C
解説：
Universal Containers (UC) wants to enable its sales team to leverage AI to recommend products from its catalog. The best option for this use case is a Flex prompt template.
A Flex prompt template is designed to provide flexible, customizable AI-driven recommendations or responses based on specific data points, such as product information, customer needs, or sales history. This template type allows the AI to consider various inputs and parameters, making it ideal for generating product recommendations dynamically.
In contrast:
* A Record summary prompt template (Option A) is used to summarize data related to a specific record, such as generating a quick summary of a sales opportunity or account, but not for recommending products.
* An Email generation prompt template (Option B) is tailored for crafting email content and is not suitable for suggesting products based on a catalog.
Given the need for dynamic recommendations that pull from a product catalog and potentially other sales data, the Flex prompt template is the correct approach.
Salesforce References:
* Salesforce Prompt Templates Overview: https://help.salesforce.com/s/articleView?
id=000391407&type=1
* Flex Prompt Template Usage: https://developer.salesforce.com/docs/atlas.en-us.salesforce_ai.meta
/salesforce_ai/prompt_flex_template
質問 # 66
An administrator wants to check the response of the Flex prompt
template they've built, but the preview button is greyed out.
What is the reason for this?
- A. The prompt has not been saved and activated,
- B. A merge field has not been inserted in the prompt.
- C. The records related to the prompt have not been selected.
正解：C
解説：
When the preview button is greyed out in a Flex prompt template, it is often because the records related to the prompt have not been selected. Flex prompt templates pull data dynamically from Salesforce records, and if there are no records specified for the prompt, it can't be previewed since there is no content to generate based on the template.
Option B, not saving or activating the prompt, would not necessarily cause the preview button to be greyed out, but it could prevent proper functionality.
Option C, missing a merge field, would cause issues with the output but would not directly grey out the preview button.
Ensuring that the related records are correctly linked is crucial for testing and previewing how the prompt will function in real use cases.
Salesforce AI Specialist Reference:
Refer to the documentation on troubleshooting Flex templates here: https://help.salesforce.com/s/articleView?id=sf.flex_prompt_builder_troubleshoot.htm
質問 # 67
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?
- A. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights.
- B. Execute tasks based on available actions, answering questions using information from accessible Knowledge articles.
- C. Invoke a flow which makes a call to external data to create a Knowledge article.
正解：A
解説：
In this scenario, the Einstein Copilot capability that best helps the agent is its ability to execute tasks based on available actions and answer questions using data from Knowledge articles. Einstein Copilot can assist the service agent by providing relevant Knowledge articles on canceling and rebooking flights, ensuring that the agent has access to the correct steps and procedures directly within the workflow.
This feature leverages the agent's existing context (the travel itinerary) and provides actionable insights or next steps from the relevant Knowledge articles to help the agent quickly resolve the customer's needs.
The other options are incorrect:
B refers to invoking a flow to create a Knowledge article, which is unrelated to the task of retrieving existing Knowledge articles.
C focuses on generating Knowledge articles, which is not the immediate need for this situation where the agent requires guidance on existing procedures.
Reference:
Salesforce Documentation on Einstein Copilot
Trailhead Module on Einstein for Service
質問 # 68
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. Create a flow that sends an email to a specified address each time the toxicity score from the response exceeds a predefined threshold.
- B. Access the Toxicity Detection log in Setup and export all entries where isToxicityDetected is true.
- 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.
正解：C
解説：
To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the AI Specialist should create aTrust Layer audit reportwithinData Cloud. By using thetoxicity detector type filter, the report can displaytoxic responsesalong with their respective toxicity scores, allowing Universal Containersto monitor and manage any toxic content generated with a high level of confidence.
* Option Cis correct because it enables visibility into toxic language detection within theTrust Layerand allows for auditing responses for toxicity.
* Option Asuggests checking a toxicity detection log, butSalesforceprovides more comprehensive options via the audit report.
* Option Binvolves creating a flow, which is unnecessary for toxicity detection monitoring.
References:
* Salesforce Trust Layer Documentation:https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_audit.htm
質問 # 69
Universal Containers (UC) wants to assess Salesforce's generative features but has concerns over its company data being exposed to third- party large language models (LLMs). Specifically, UC wants the followingcapabilities to be part of Einstein's generative AI service.
No data is used for LLM training or product improvements by third- party LLMs.
No data is retained outside of UC's Salesforce org.
The data sent cannot be accessed by the LLM provider.
Which property of the Einstein Trust Layer should the AI Specialist highlight to UC that addresses these requirements?
- A. Data Masking
- B. Prompt Defense
- C. Zero-Data Retention Policy
正解：C
解説：
Universal Containers (UC)has concerns about data privacy when usingSalesforce's generative AIfeatures, particularly around preventing third-party LLMs from accessing or retaining their data. TheZero-Data Retention Policyin theEinstein Trust Layeris designed to address these concerns by ensuring that:
* No data is used for trainingor product improvements by third-party LLMs.
* No data is retainedoutside of the customer's Salesforce organization.
* The LLM provider cannot access any customer data.
This policy aligns perfectly with UC's requirements for keeping their data safe while leveraging generative AI capabilities.
* Prompt DefenseandData Maskingare also security features, but they do not directly address the concerns related to third-party data access and retention.
References:
* Salesforce Einstein Trust Layer Documentation:https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer.htm
質問 # 70
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?
- A. Field Generation
- B. Sales Email
- C. Record Summary
正解：A
解説：
The correct answer is Field Generation because this template type is designed to dynamically populate form fields with content generated by a large language model (LLM). In this scenario, leadership wants a dynamic form field that contains a summary or description generated by AI to aid customer interactions. Additionally, they want to keep a human in the loop, meaning the generated content will likely be reviewed or edited by a person before it's finalized, which aligns with the Field Generation prompt template.
Field Generation: This prompt type allows you to generate content for specific fields in Salesforce, leveraging large language models to create dynamic and contextual information. It ensures that AI content is available within the record where needed, but it allows human oversight or review, supporting the "human-in-the-loop" strategy.
Sales Email: This prompt type is mainly used for generating email content for outreach or responses, which doesn't align directly with populating fields in a form.
Record Summary: While this option might seem close, it is typically used to summarize entire records for high-level insights rather than filling specific fields with dynamic content based on AI generation.
Salesforce AI Specialist Reference:
You can explore more about these prompt templates and AI capabilities through Salesforce documentation and official resources on Prompt Builder: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_templates_overview.htm
質問 # 71
An AI Specialist needs to create a Sales Email with a custom prompt template. They need to ground on the following data.
Opportunity Products Events near the customer Tone and voice examples
How should the AI Specialist obtain related items?
- A. Utilize a standard email template and manually insert the required data fields.
- B. Create a flex template that takes the records in question as inputs.
- C. Call prompt initiated flow to fetch and ground the required data.
正解：C
解説：
To ground a sales email onOpportunity Products, Events near the customer, and Tone and voice examples, the AI Specialist should use aprompt-initiated flow. This flow can dynamically fetch the necessary data from related records in Salesforce and ground the generative AI output with contextually accurate information.
* Option B (flex template)does not provide the ability to fetch dynamic data from Salesforce records automatically.
* Option C (manual insertion)would not allow for the dynamic and automated grounding of data required for custom prompts.
Refer toSalesforce documentation on flowsand grounding for more details on integrating data into custom prompt templates.
質問 # 72
The sales team at a hotel resort would like to generate a guest summary about the guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page.
Which AI capability should the team use?
- A. Prompt Builder
- B. Einstein Copilot
- C. Model Builder
正解：A
解説：
The sales team at a hotel resort wants to generate a guest summary about guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They require the summary to be availableonly on the contact record page.
Solution:
* UsePrompt Builderto create a prompt template that generates the desired summary and displays it on the contact record page.
* Prompt Builder:
* Purpose:Allows the creation of custom prompt templates that leverage AI to generate content based on Salesforce data.
* Functionality:
* Field Generation Templates:Can be used to populate fields on records with AI-generated summaries.
* Customization:Enables the AI Specialist to design prompts that utilize data from the guest profiles to produce personalized summaries and recommendations.
* Relevance to the Use Case:
* The sales team wants the summary to be available on the contact record page, which aligns with the capabilities of Prompt Builder to generate and display content on specific record pages.
* Implementation Steps:
* Create a Field Generation Prompt Template:
* Use Prompt Builder to create a new prompt template of typeField Generation.
* Design the prompt to instruct the AI to generate a summary based on the guest's interests and activity preferences.
* Include Relevant Data:
* Use merge fields to include data from the guest profile in the prompt.
* Ensure that the prompt accesses the necessary fields to generate accurate recommendations.
* Configure the Contact Page Layout:
* Add the field that will display the AI-generated summary to the contact record page layout.
* Ensure that the field is only visible where appropriate, adhering to the requirement of availability only on the contact record page.
* Why Not Einstein Copilot or Model Builder:
* Option A (Einstein Copilot):
* Purpose:Einstein Copilot is a conversational AI assistant designed to interact with users through natural language.
* Mismatch with Requirements:
* The team wants a static summary displayed on the contact record page, not an interactive conversational experience.
* Option C (Model Builder):
* Purpose:Model Builder is used to create custom AI models for predictions and classifications.
* Inapplicability:
* Building a custom model is unnecessary for generating text summaries based on existing data.
* Model Builder does not directly provide functionality to generate and display summaries on record pages.
References:
* Salesforce AI Specialist Documentation -Prompt Builder Overview:
* Provides an introduction to Prompt Builder and its capabilities.
* Salesforce Help -Creating Field Generation Prompt Templates:
* Guides on creating prompt templates that generate content for fields on records.
* Salesforce Trailhead -Customize AI Content with Prompt Builder:
* Offers hands-on experience in building and customizing prompt templates.
Conclusion:
By utilizing Prompt Builder, the sales team can create a customized prompt template that generates personalized guest summaries and recommendations based on activity preferences. This solution meets the requirement of displaying the summary only on the contact record page, enhancing the team's ability to engage with guests effectively.
質問 # 73
What is the primary function of the planner service in the Einstein Copilot system?
- A. Identifying copilot actions to respond to user utterances
- B. Generating record queries based on conversation history
- C. Offering real-time language translation during conversations
正解：A
解説：
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.
質問 # 74
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?
- A. Email generation prompt template
- B. Record summary prompt template
- C. Flex prompt template
正解：C
解説：
Universal Containers (UC) wants to enable its sales team to leverage AI to recommend products from its catalog. The best option for this use case is a Flex prompt template.
A Flex prompt template is designed to provide flexible, customizable AI-driven recommendations or responses based on specific data points, such as product information, customer needs, or sales history. This template type allows the AI to consider various inputs and parameters, making it ideal for generating product recommendations dynamically.
In contrast:
A Record summary prompt template (Option A) is used to summarize data related to a specific record, such as generating a quick summary of a sales opportunity or account, but not for recommending products.
An Email generation prompt template (Option B) is tailored for crafting email content and is not suitable for suggesting products based on a catalog.
Given the need for dynamic recommendations that pull from a product catalog and potentially other sales data, the Flex prompt template is the correct approach.
Salesforce Reference:
Salesforce Prompt Templates Overview: https://help.salesforce.com/s/articleView?id=000391407&type=1 Flex Prompt Template Usage: https://developer.salesforce.com/docs/atlas.en-us.salesforce_ai.meta/salesforce_ai/prompt_flex_template
質問 # 75
Where should the AI Specialist go to add/update actions assigned to a copilot?
- A. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab
- B. Copilot Actions page or Global Actions
- C. Copilot Detail page, Global Actions, or the record page for the copilot action
正解：A
解説：
To add or update actions assigned to a copilot, an AI Specialist can manage this through several areas:
Copilot Actions Page: This is the central location where copilot actions are managed and configured.
Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
The other options are incorrect:
B misses the Copilot Action Library, which is crucial for managing actions.
C includes the Copilot Detail page, which isn't the primary place for action management.
Reference:
Salesforce Documentation on Managing Copilot Actions
Salesforce AI Specialist Guide on Copilot Action Management
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