Salesforce-AI-Specialist: Salesforce Certified AI Specialist Exam Dumps & PassGuide Salesforce-AI-Specialist Examen

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Salesforce Salesforce-AI-Specialist Prüfungsplan:

Thema	Einzelheiten
Thema 1	Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Thema 2	Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.
Thema 3	Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.
Thema 4	Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Thema 5	Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.

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Salesforce-AI-Specialist Online Test & Salesforce-AI-Specialist Exam Fragen

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Salesforce Certified AI Specialist Exam Salesforce-AI-Specialist Prüfungsfragen mit Lösungen (Q120-Q125):

120. Frage
An AI Specialist created a custom Agent action, but it is not being picked up by the planner service in the correct order.
Which adjustment should the Al Specialist make in the custom Agent action instructions for the planner service to work as expected?

A. Specify the dependent actions with the reference to the action API name.
B. Specify the profiles or custom permissions allowed to invoke the action.
C. Specify the LLM model provider and version to be used to invoke the action.

Antwort: A

Begründung:
When a custom Agent action is not being prioritized correctly by the planner service, the root cause is often missing or improperly defined action dependencies. The planner service determines the execution order of actions based on dependencies defined in the action instructions. To resolve this, the AISpecialist must explicitly specify dependent actions using their API names in the custom action's configuration. This ensures the planner understands the sequence in which actions must be executed to meet business logic requirements.
Salesforce documentation highlights that dependencies are critical for orchestrating workflows in Einstein Bots and Agentforce. For example, if Action B requires data from Action A, Action A's API name must be listed as a dependency in Action B's instructions. The Einstein Bot Developer Guide states that failing to define dependencies can lead to race conditions or incorrect execution order.
In contrast:
* Profiles or custom permissions (B) control access to the action but do not influence execution order.
* LLM model provider and version (C) determine the AI model used for processing but are unrelated to the planner's sequencing logic.

121. Frage
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. Template-triggered prompt flow
B. Data Cloud-triggered flow
C. Unified-object linking flow

Antwort: B

Begründung:
In this scenario,Universal Containerswants to bring data fromunified Data Cloud objectsinto prompt templates, and the best way to do that is through aData 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 onData Cloud-triggered flowsandData Cloud integrationswith generative AI solutions.

122. Frage
When configuring a prompt template, an AI Specialist previews the results of the prompt template they've written. They see two distinct text outputs: Resolution and Response.
Which information does the Resolution text provide?

A. It shows which sensitive data is masked before it is sent to the LLM.
B. It shows the full text that is sent to the Trust Layer.
C. It shows the response from the LLM based on the sample record.

Antwort: C

Begründung:
When previewing a prompt template in Salesforce, the Resolution text provides the response from the LLM (Large Language Model) based on the data from a sample record. This output shows what the AI model generated in response to the prompt, giving the AI Specialist a chance to review and adjust the response before finalizing the template.
Option B is correct because Resolution displays the actual response generated by the LLM.
Option A refers to sending the text to the Trust Layer, but that's not what Resolution represents.
Option C relates to data masking, which is shown elsewhere, not under Resolution.
Reference:
Salesforce Prompt Builder Overview: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm

123. Frage
An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM dat a. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?

A. Data masking
B. Zero-data retention policy
C. Dynamic grounding with secure data retrieval

Antwort: C

Begründung:
Dynamic grounding with secure data retrieval is a key feature in Salesforce's Einstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allows relevant Salesforce data to be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
Data masking refers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
Zero-data retention policy ensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.
Reference:
Salesforce Developer Documentation on Einstein Trust Layer
Salesforce Security Documentation for AI and Data Privacy

124. Frage
An AI Specialist wants to use the related lists from an account in a custom prompt template.
What should the AI Specialist consider when configuring the prompt template?

A. The text encoding (for example, UTF-8, ASCII) option
B. The maximum number of related list merge fields
C. The choice between XML and JSON rendering formats for the list

Antwort: B

Begründung:
When configuring a custom prompt template to use related lists, the AI Specialist must be aware of the maximum number of related list merge fields that can be included. Salesforce enforces limits to ensure prompt templates perform efficiently and do not overload the system with too much data. As a best practice, it's important to monitor and optimize the number of merge fields used.
Option B is correct because there is a limit on how many related list merge fields can be included in a prompt template.
Option A (text encoding) and Option C (XML/JSON rendering) are not key considerations in this context.
Reference:
Salesforce Prompt Builder Documentation: https://help.salesforce.com/s/articleView?id=sf.prompt_builder.htm

125. Frage
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