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[General] Quiz Salesforce-AI-Specialist - Salesforce Certified AI Specialist Exam Accurate

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【General】 Quiz Salesforce-AI-Specialist - Salesforce Certified AI Specialist Exam Accurate

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:
TopicDetails
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
  • 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 3
  • 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 4
  • 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.
Topic 5
  • 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.

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Salesforce Certified AI Specialist Exam Sample Questions (Q133-Q138):NEW QUESTION # 133
An AI Specialist at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time. UC wants to help prep the sales team for the calls by summarizing past purchases, interests in products shown by the Contact captured via Data Cloud, and a recap of past email and phone conversations for which there are transcripts.
Which approach should the AI Specialist recommend to achieve this use case?
  • A. Deploy UC's own custom foundational model on this data first.
  • B. Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.
  • C. Fine-Tune the standard foundational model due to the complexity of the data.
Answer: B
Explanation:
For no-code implementations, Prompt Builder allows AI Specialists to create prompt templates that dynamically ground responses in Salesforce CRM data (e.g., past purchases) and Data Cloud insights (e.g., product interests) without custom coding. The standard foundation model (e.g., Einstein GPT) can synthesize this data into summaries, leveraging structured and unstructured sources (e.g., email/phone transcripts). Fine- tuning (B) or custom models (C) require code and are unnecessary here, as the use case does not involve unique data patterns requiring model retraining.

NEW QUESTION # 134
The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history.
Why should the team use Einstein Copilot as the solution?
  • A. To send automated emails to all customers
  • B. To generate relevant content when engaging with each customer
  • C. To analyze past campaign performance
Answer: B
Explanation:
Einstein Copilotis designed to assist in generating personalized, AI-driven content based on customer data such as behavior, preferences, and purchase history. For the marketing team atUniversal Containers, this is the perfect solution to create dynamic and relevant email content. By leveragingEinstein Copilot, they can ensure that each customer receives tailored communications, improving engagement and conversion rates.
* Option Ais correct asEinstein Copilothelps generate real-time, personalized content based on comprehensive data about the customer.
* Option Brefers more to Einstein Analytics or Marketing Cloud Intelligence, andOption Cdeals with automation, which isn't the primary focus ofEinstein Copilot.
References:
* Salesforce Einstein Copilot Overview:https://help.salesforce.com/s/articleView?
id=einstein_copilot_overview.htm

NEW QUESTION # 135
An Al Specialist is creating a custom action for Agentforce.
Which setting should the AI Specialist test and iterate on to ensure the action performs as expected?
  • A. Action Input
  • B. Action Instructions
  • C. Action Name
Answer: B
Explanation:
To ensure a custom action in Agentforce performs as expected, the AI Specialist must focus on Action Instructions. Here's why:
* Action Instructions define the logic, parameters, and steps the AI should follow to execute the action.
They include:
* How input data is processed.
* API calls or Apex invocations.
* Conditional logic (e.g., decision trees).Testing and iterating on these instructions ensures alignment with the intended workflow. For example, incorrect API endpoint references or misconfigured parameters in the instructions will cause failures.
* Action Input (Option A) refers to the data provided to the action. While validating input formats is important, inputs are static once defined. The primary issue lies in whether the instructions correctly use the inputs.
* Action Name (Option B) is a descriptive label and does not affect functionality.
Salesforce Documentation Support:
* Salesforce Einstein Bots & Custom Actions Guide highlights that Action Instructions are where the
"core logic" resides, requiring rigorous testing (Source: Einstein Bots Developer Guide).
* Trailhead Module "Build Custom Actions for Einstein Bots" emphasizes refining instructions to handle edge cases and validate outputs (Source: Trailhead).
By iterating on Action Instructions, the AI Specialist ensures the action's logic, integrations, and error handling are robust.

NEW QUESTION # 136
Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information.
In refining its prompt design strategy, which key practices should UC prioritize?
  • A. Enable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback.
  • B. Submit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations.
  • C. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback.
Answer: C
Explanation:
ForUniversal Containers (UC)to refine itsGenerative AIprompt design strategy and improve the accuracy of the generated summaries for the custom objectGuest, the best practice is to focus on craftingconcise, clear, and consistent prompt templates. This includes:
* Effective grounding: Ensuring the prompt pulls data from the correct sources.
* Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
* Clear instructions: Giving unambiguous directions on what to include in the response.
* Iterative feedback: Regularly testing and adjusting prompts based on user feedback.
* Option Bis correct because it follows industry best practices for refining prompt design.
* Option A(prompt test mode) is useful but less relevant for refining prompt design itself.
* Option C(prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.
References:
* Salesforce Prompt Design Best Practices:https://help.salesforce.com/s/articleView?id=sf.
prompt_design_best_practices.htm

NEW QUESTION # 137
Which mechanism within the Einstein Trust Layer helps to ensure that personal data is handled in compliance with data protection regulations like GDPR?
  • A. Toxicity Scoring
  • B. Prompt Defense
  • C. Data Masking
Answer: C

NEW QUESTION # 138
......
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