THE BEST LATEST SALESFORCE-AI-SPECIALIST GUIDE FILES & RELIABLE VCE SALESFORCE-AI-SPECIALIST DUMPS & COMPLETE SALESFORCE-AI-SPECIALIST TRAINING COURSES

The Best Latest Salesforce-AI-Specialist Guide Files & Reliable VCE Salesforce-AI-Specialist Dumps & Complete Salesforce-AI-Specialist Training Courses

The Best Latest Salesforce-AI-Specialist Guide Files & Reliable VCE Salesforce-AI-Specialist Dumps & Complete Salesforce-AI-Specialist Training Courses

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Salesforce Certified AI Specialist Exam Sample Questions (Q113-Q118):

NEW QUESTION # 113
Universal Containers (UC) is looking to improve its sales team's productivity by providing real-time insights and recommendations during customer interactions.
Why should UC consider using Agentforce Sales Agent?

  • A. To automate the entire sales process for maximum efficiency
  • B. To streamline the sales process and increase conversion rates
  • C. To track customer interactions for future analysis

Answer: B

Explanation:
Agentforce Sales Agent provides real-time insights and AI-powered recommendations, which are designed to streamline the sales process and help sales representatives focus on key tasks to increase conversion rates.
It offers features like lead scoring, opportunity prioritization, and proactive recommendations, ensuring that sales teams can interact with customers efficiently and close deals faster.
* Option A: While tracking customer interactions is beneficial, it is only part of the broader capabilities offered by Agentforce Sales Agent and is not the primary objective for improving real-time productivity.
* Option B: Agentforce Sales Agent does not automate the entire sales process but provides actionable recommendations to assist the sales team.
* Option C: This aligns with the tool's core purpose of enhancing productivity and driving sales success.


NEW QUESTION # 114
An account manager is preparing for an upcoming customer call and wishes to get a snapshot of key data points from accounts, contacts, leads, and opportunities in Salesforce.
Which feature provides this?

  • A. Work Summaries
  • B. Sales Summaries
  • C. Sales Insight Summary

Answer: C

Explanation:
Sales Insight Summary aggregates key data points from multiple Salesforce objects (accounts, contacts, leads, opportunities) into a consolidated view, enabling account managers to quickly access relevant information for customer calls.
* Option A (Sales Summaries): Typically refers to Einstein-generated summaries of specific interactions (e.g., emails, calls), not multi-object snapshots.
* Option C (Work Summaries): Focuses on summarizing customer service interactions (e.g., chat transcripts), not sales data.
* Option B (Sales Insight Summary): Directly provides a holistic snapshot of sales-related objects, aligning with the scenario.
References:
* Salesforce Help: Sales Insight Overview
* Describes Sales Insight Summary as "a unified view of account, contact, and opportunity data for sales readiness."


NEW QUESTION # 115
Universal Containers has a strict change management process that requires all possible configuration to be completed in a sandbox which will be deployed to production. The AI Specialist is tasked with setting up Work Summaries for Enhanced Messaging. Einstein Generative AI is already enabled in production, and the Einstein Work Summaries permission set is already available in production.
Which other configuration steps should the AI Specialist take in the sandbox that can be deployed to the production org?

  • A. From the Epstein setup menu, select Turn on Einstein: create custom fields to store Issue, Resolution, and Summary: create a Quick Action that updates these fields: and add the wrap up componert to the Messaging session record page layout.
  • B. create custom fields to store Issue, Resolution, and Summary; create a Quick Action that updates these fields: add the Wrap Up component to the Messaging Session record paae layout: and create Permission Set Assignments for the intended Agents.
  • C. Create custom fields to store issue, Resolution, and Summary; create a Quick Action that updates these fields: and ado the Wrap up component to the Messaging session record page lavcut.

Answer: C

Explanation:
* Context of the Question
* Universal Containers (UC) has a strict change management process that requires all possible configuration be completed in a sandbox and deployed to Production.
* Einstein Generative AI is already enabled in Production, and the "Einstein Work Summaries" permission set is already available in Production.
* The AI Specialist needs to configureWork Summaries for Enhanced Messagingin the sandbox.
* What Can Actually Be Deployed from Sandbox to Production?
* Custom Fields: Metadata that is easily created in sandbox and then deployed.
* Quick Actions: Also metadata-based and can be deployed from sandbox to production.
* Layout Components: Page layout changes (such as adding the Wrap Up component) can be added to a change set or deployment package.
* Why Option C is Correct
* No Need to Turn on Einstein in Sandbox for Deployment: Einstein Generative AI is already enabled in Production; turning it on in the sandbox is typically a manual step if you want to test, but that step itself is not "deployable" in the sense of metadata.
* Permission Set Assignments(as in Option A) are not deployable metadata. You can deploy the Permission Set itself but not the specific user assignments. Since the question specifically asks
"Which other configuration steps should be takenin the sandboxthatcanbe deployed to the production org?", user assignment is not one of them.
* Why Not Option A or B?
* Option A: Mentions creating permission set assignments for agents. This cannot be directly deployed from sandbox to Production, as permission set assignments are user-specific and considered "data," not metadata.
* Option B: Mentions "Turn on Einstein." But Einstein Generative AI is already enabled in Production. Additionally, "Turning on Einstein" is typically an org-level setting, not a deployable metadata item.
* ConclusionThe main deployable items you can reliably create and test in a sandbox, and then migrate to Production, are:
* Custom Fields(Issue, Resolution, Summary).
* A Quick Actionthat updates those fields.
* Page Layout Changeto include the Wrap Up component.
Therefore,Option Cis correct and focuses on actions that are truly deployable as metadata from a sandbox to Production.
Salesforce AI Specialist References & Documents
* Salesforce Trailhead:Work Summaries with Einstein GPTProvides an overview of how to configure Work Summaries, including the need for custom fields, quick actions, and UI components.
* Salesforce Documentation:Deploying Metadata Between OrgsExplains what can and cannot be deployed via change sets (e.g., custom fields, page layouts, quick actions vs. user permission set assignments).
* Salesforce AI Specialist Study GuideOutlines which Einstein Generative AI and Work Summaries configurations are deployable as metadata.


NEW QUESTION # 116
Universal Containers (UC) plans to automatically populate the Description field on the Account object.
Which type of prompt template should UC use?

  • A. Sales Email prompt template
  • B. Field Generation prompt template
  • C. Flex Prompt template

Answer: B


NEW QUESTION # 117
Which feature in the Einstein Trust Layer helps to minimize the risks of jailbreaking and prompt injection attacks?

  • A. Prompt Defense
  • B. Data Masking
  • C. Secure Data Retrieval and Grounding

Answer: B

Explanation:
The Einstein Trust Layer is designed to ensure responsible and compliant AI usage. Data Masking (B) is the mechanism that directly addresses compliance with data protection regulations like GDPR byobscuring or anonymizing sensitive personal data (e.g., names, emails, phone numbers) before it is processed by AI models. This prevents unauthorized exposure of personally identifiable information (PII) and ensures adherence to privacy laws.
Salesforce documentation explicitly states that Data Masking is a core component of the Einstein Trust Layer, enabling organizations to meet GDPR requirements by automatically redacting sensitive fields during AI interactions. For example, masked data ensures that PII is not stored or used in AI model training or inference without explicit consent.
In contrast:
* Toxicity Scoring (A) identifies harmful or inappropriate content in outputs but does not address data privacy.
* Prompt Defense (C) guards against malicious prompts or injection attacks but focuses on security rather than data protection compliance.


NEW QUESTION # 118
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