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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

Topic
Details

Topic 1

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.

Topic 2

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.

Topic 3

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.

Topic 4

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.

Topic 5

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.

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Salesforce Certified AI Specialist Exam Sample Questions (Q98-Q103):

NEW QUESTION # 98
What is an AI Specialist able to do when the "Enrich event logs with conversation data" setting in Einstein Copilot is enabled?

A. View the user click path that led to each copilot action.
B. View session data including user Input and copilot responses for sessions over the past 7 days.
C. Generate details reports on all Copilot conversations over any time period.

Answer: B

Explanation:
When the"Enrich event logs with conversation data"setting is enabled inEinstein Copilot, it allows an AI Specialist or admin to view session data, including both theuser inputandcopilot responsesfrom interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs.
* This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helping AI specialists track AI behavior and user engagement.
* Option A, viewing the user click path, focuses on navigation but is not part of the conversation data enrichment functionality.
* Option C, generating detailed reports over any time period, is incorrect because this specific feature is limited to data for the past 7 days.
Salesforce AI Specialist References:You can refer to this documentation for further insights:https://help.
salesforce.com/s/articleView?id=sf.einstein_copilot_event_logging.htm

NEW QUESTION # 99
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. Flex prompt template
C. Record summary prompt template

Answer: B

Explanation:
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

NEW QUESTION # 100
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 number of tokens that can be processed by the LLM varies with total user demand.
B. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding.
C. The number of tokens generated by the dynamic nature of the prompt template will vary by record.

Answer: C

Explanation:
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.
Reference:
Salesforce Developer Documentation on Token Limits for Generative AI Models Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources)

NEW QUESTION # 101
Universal Containers is evaluating Einstein Generative AI features to improve the productivity of the service center operation.
Which features should the AI Specialist recommend?

A. Service Replies and Work Summaries
B. Reply Recommendations and Sales Summaries
C. Service Replies and Case Summaries

Answer: C

Explanation:
To improve the productivity of the service center, the AI Specialist should recommend theService Repliesand Case Summariesfeatures.
* Service Replieshelps agents by automatically generating suggested responses to customer inquiries, reducing response time and improving efficiency.
* Case Summariesprovide a quick overview of case details, allowing agents to get up to speed faster on customer issues.
* Work Summariesare not as relevant for direct customer service operations, andSales Summariesare focused on sales processes, not service center productivity.
For more information, seeSalesforce's Einstein Service Cloud documentationon the use of generative AI to assist customer service teams.

NEW QUESTION # 102
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

Answer: A

Explanation:
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 References:
* 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

NEW QUESTION # 103
......

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