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Salesforce Certified AI Specialist Exam 認定 Salesforce-AI-Specialist 試験問題 (Q45-Q50):

質問 # 45
Universal Containers implements three custom actions to get three distinct types of sales summaries for its users. Users are complaining that they are not getting the right summary based on their utterances. What should the AI Specialist investigate as the root cause?

A. Review the action Instructions to ensure they are unique.
B. Review that the custom action Is assigned to an Agent.
C. Ensure the input and output types are correctly chosen.

正解：A

解説：
The root cause of users receiving incorrect sales summaries lies in non-unique action instructions (Option B). In Einstein Bots, custom actions are triggered based on how well user utterances align with the action instructions defined for each action. If the instructions for the three custom actions overlap or lack specificity, the bot's natural language processing (NLP) cannot reliably distinguish between them, leading to mismatched responses.
Steps to Investigate:
* Review Action Instructions: Ensure each custom action has distinct, context-specific instructions. For example:
* Action 1: "Summarize quarterly sales by region."
* Action 2: "Generate a product-wise sales breakdown for the current fiscal year."
* Action 3: "Provide a comparison of sales performance between online and in-store channels." Ambiguous or overlapping instructions (e.g., "Get sales summary") cause confusion.
* Test Utterance Matching: Use Einstein Bot's training tools to validate if user utterances map to the correct action. Overlap indicates instruction ambiguity.
* Refine Instructions: Incorporate keywords or phrases unique to each sales summary type to improve intent detection.
Why Other Options Are Incorrect:
* A. Assigning actions to an agent is irrelevant, as custom actions are automated bot components.
* C. Input/output types relate to data formatting, not intent routing. While important for execution, they don't resolve utterance mismatches.
References:
* Einstein Bot Developer Guide: Stresses the need for unique action instructions to avoid intent conflicts.
* Trailhead Module: "Build AI-Powered Bots with Einstein" highlights instruction specificity for accurate action triggering.
* Salesforce Help Documentation: Recommends testing and refining action instructions to ensure clarity in utterance mapping.

質問 # 46
Which configuration must an AI Specialist complete for users to access generative Al-enabled fields in the Salesforce mobile app?

A. Enable Mobile Prompt Responses.
B. Enable Dynamic Forms on Mobile.
C. Enable Mobile Generative AI.

正解：B

解説：
* Context of the Question
* Universal Containers (UC) has generative AI-enabled fields that users can access in the desktop experience.
* The AI Specialist needs these same fields to be visible and usable in the Salesforce Mobile App.
* Why Dynamic Forms on Mobile?
* Dynamic Formsallow you to configure record pages so that fields and sections can appear or be hidden based on certain criteria.
* When you enable "Dynamic Forms for Mobile," any generative AI-enabled fields placed on the dynamic layout become accessible in the Salesforce mobile experience.
* There is no standard Setup option labeled "Enable Mobile Generative AI" or "Enable Mobile Prompt Responses" as a universal toggle; the existing official approach is to ensure dynamic forms (and the relevant fields) are supported on mobile.
* Conclusion
* Ensuring that these AI-driven fields are visible on mobile is accomplished by turning onDynamic Forms on Mobileand adding those fields to the dynamic layout. Therefore,Option Cis correct.
Salesforce AI Specialist References & Documents
* Salesforce Documentation:Dynamic Forms OverviewExplains how to enable Dynamic Forms for both desktop and mobile UIs, allowing newly added fields (including generative AI-enabled ones) to display in the Salesforce Mobile App.
* Salesforce AI Specialist Study GuideReiterates that to expose generative AI fields or components in mobile, you must configure dynamic forms and ensure compatibility on mobile layouts.

質問 # 47
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

正解：B

解説：
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.

質問 # 48
What is a Salesforce AI Specialist able to configure in Data Masking within the Einstein Trust Layer?

A. The encryption keys for masking
B. The profiles exempt from masking
C. The privacy data entities to be masked

正解：C

解説：
In the Einstein Trust Layer, the Salesforce AI Specialist can configure privacy data entities to be masked (Option C). This ensures sensitive or personally identifiable information (PII) is obfuscated when processed by AI models.
* Data Masking Configuration:
* The AI Specialist defines which fields or data types (e.g., email, phone number, Social Security Number) should be masked. For example, masking the Email field in a prompt response to protect user privacy.
* This is done through declarative settings in Salesforce, where entities (standard or custom fields) are flagged for masking.
* Why Other Options Are Incorrect:
* A. Profiles exempt from masking: Exemptions are typically managed via permissions (e.g., field-level security), not directly within Einstein Trust Layer's Data Masking settings.
* B. Encryption keys for masking: Encryption is separate from masking. Masking involves obfuscation (e.g., replacing "john@example.com" with "@"), not encryption, which uses keys to secure data.
References:
* Einstein Trust Layer Documentation: States that Data Masking allows admins to "define which fields should be masked to protect sensitive data."
* Trailhead Module: "Einstein Trust Layer Basics" explains configuring privacy entities for masking.
* Salesforce Help Article: "Secure AI with Einstein Trust Layer" details masking configurations for privacy compliance.

質問 # 49
What is the importance of Action Instructions when creating a custom Agent action?

A. Action Instructions tell the user how to call this action in a conversation
B. Action Instructions define the expected user experience of an action.
C. Action Instructions tell the large language model (LLM) which action to use.

正解：B

解説：
Action Instructions are critical for defining how a custom Agent action should be executed, ensuring alignment with the intended user experience. They provide step-by-step guidance to the bot or LLM on logic, data handling, and integration workflows, directly impacting how users interact with the action. For example, clear instructions prevent errors in API calls or data processing, ensuring seamless interactions.
Salesforce documentation states that poorly defined instructions lead to mismatched expectations, while well- structured instructions ensure the action behaves predictably. This aligns with delivering a consistent user experience.
* A refers to user invocation, which is handled by dialogue flows, not instructions.
* B is incorrect because the LLM selects actions based on context/intent, not instructions.

質問 # 50
......

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