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Salesforce Certified AI Specialist Practice Test - Questions Answers, Page 10

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Question 91

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Universal Containers is evaluating Einstein Generative AI features to improve the productivity of the service center operation.

Which features should the AI Specialist recommend?

Service Replies and Case Summaries
Service Replies and Case Summaries
Service Replies and Work Summaries
Service Replies and Work Summaries
Reply Recommendations and Sales Summaries
Reply Recommendations and Sales Summaries
Suggested answer: A

Explanation:

To improve the productivity of the service center, the AI Specialist should recommend the Service Replies and Case Summaries features.

Service Replies helps agents by automatically generating suggested responses to customer inquiries, reducing response time and improving efficiency.

Case Summaries provide a quick overview of case details, allowing agents to get up to speed faster on customer issues.

Work Summaries are not as relevant for direct customer service operations, and Sales Summaries are focused on sales processes, not service center productivity.

For more information, see Salesforce's Einstein Service Cloud documentation on the use of generative AI to assist customer service teams.

asked 26/09/2024
Haleem SHITOU OGUNGBEMI
42 questions

Question 92

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Amid their busy schedules, sales reps at Universal Containers dedicate time to follow up with prospects and existing clients via email regarding renewals or new deals. They spend many hours throughout the week reviewing past communications and details about their customers before performing their outreach.

Which standard Copilot action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications?

Einstein Copilot Action: Find Similar Opportunities
Einstein Copilot Action: Find Similar Opportunities
Einstein Copilot Action: Draft or Revise Sales Email
Einstein Copilot Action: Draft or Revise Sales Email
Einstein Copilot Action: Summarize Record
Einstein Copilot Action: Summarize Record
Suggested answer: B

Explanation:

For sales reps who need to draft personalized emails based on previous communications, the AI Specialist should recommend the Einstein Copilot Action: Draft or Revise Sales Email. This action uses AI to generate or revise email content, leveraging past successful communications to create personalized and relevant outreach to prospects or clients.

Find Similar Opportunities is used for opportunity matching, not email drafting.

Summarize Record provides a summary of customer data but does not directly help with drafting emails.

For more information, refer to Salesforce's Einstein Copilot documentation on standard actions for sales teams.

asked 26/09/2024
Dustin Roberts
45 questions

Question 93

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An AI Specialist wants to troubleshoot their Agent's performance.

Where should the AI Specialist go to access all user interactions with the Agent, including Agent erro|rs, incorrectly triggered actions, and incomplete plans?

Event Logs

Event Logs

Plan Canvas

Plan Canvas

Agent Settings

Agent Settings

Suggested answer: A

Explanation:

Event Logsin Salesforce capture detailed interaction data, including agent errors, triggered actions, and incomplete plans. These logs provide visibility into user-Agent interactions for troubleshooting performance issues. TheEinstein Bot Analyticsdocumentation highlights Event Logs as the primary source for auditing bot behavior and diagnosing issues like misconfigured actions or plan execution failures.

Plan Canvas(B) is for designing workflows, not auditing.

Agent Settings(C) control configuration but do not store interaction history.

Salesforce Help Article:Einstein Bot Analytics and Logs('Accessing Event Logs' section).

Einstein Bot Developer Guide: 'Monitoring and Debugging Agent Performance.'

asked 11/02/2025
tirou RANGA
34 questions

Question 94

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What is an appropriate use case for leveraging Agentforce Sales Agent in a sales context?

Enable a sates team to use natural language to invoke defined sales tasks grounded in relevant data and be able to ensure company policies are applied. conversationally and in the now or work.

Enable a sates team to use natural language to invoke defined sales tasks grounded in relevant data and be able to ensure company policies are applied. conversationally and in the now or work.

Enable a sales team by providing them with an interactive step-by-step guide based on business rules to ensure accurate data entry into Salesforce and help close deals fatter.

Enable a sales team by providing them with an interactive step-by-step guide based on business rules to ensure accurate data entry into Salesforce and help close deals fatter.

Instantly review and read incoming messages or emails that are then logged to the correct opportunity, contact, and account records to provide a full view of customer interactions and communications.

Instantly review and read incoming messages or emails that are then logged to the correct opportunity, contact, and account records to provide a full view of customer interactions and communications.

Suggested answer: A

Explanation:

Agentforce Sales Agentis designed to let sales teams perform tasks vianatural language commands, leveraging Salesforce data while adhering to policies. For example, agents can ask the AI to 'update the opportunity stage to Closed Won' or 'generate a quote,' with the system enforcing validations and data security. This use case aligns with Salesforce's vision of conversational AI streamlining workflows without compromising compliance.

Step-by-step guides(B) are typically handled by tools like Dynamic Forms or Guided Selling, not Agentforce.

Logging messages/emails(C) is managed by Email-to-Case or Service Cloud, not a sales-specific AI agent.

Salesforce Help Article:Agentforce for Sales('Use Cases and Capabilities' section).

Einstein AI Specialist Trailhead: 'Sales Automation with Agentforce' (Natural Language Task Execution).

asked 11/02/2025
Piroon Dechates
24 questions

Question 95

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An AI specialist wants to leverage Record Snapshots grounding feature in a prompt template.

What preparations are required?

Configure page layout of the master record type

Configure page layout of the master record type

Create a field set for all the fields to be grounded

Create a field set for all the fields to be grounded

Enable and configure dynamic form for the object

Enable and configure dynamic form for the object

Suggested answer: B

Explanation:

To use theRecord Snapshots grounding featurein a prompt template, you mustcreate a field setthat includes all fields required for grounding. Field sets define which fields from an object are accessible to the AI model, ensuring the prompt template has structured data to generate contextually accurate responses. Salesforce documentation emphasizes that grounding relies on explicitly defined field sets to avoid exposing unintended data and to comply with security policies.

Page Layout configuration(A) controls UI organization but does not directly enable grounding.

Dynamic Forms(C) customize record pages dynamically but are unrelated to data grounding for prompts.

Salesforce Help Article:Grounding with Record Snapshots('Configuring Field Sets for Grounding' section).

Einstein GPT Implementation Guide: 'Preparing Data for AI Prompts' (Field Set requirements).

asked 11/02/2025
Juan Carlos Delgado
37 questions

Question 96

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

Action Instructions tell the user how to call this action in a conversation

Action Instructions tell the user how to call this action in a conversation

Action Instructions tell the large language model (LLM) which action to use.

Action Instructions tell the large language model (LLM) which action to use.

Action Instructions define the expected user experience of an action.

Action Instructions define the expected user experience of an action.

Suggested answer: C

Explanation:

Action Instructionsare 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.

Arefers to user invocation, which is handled by dialogue flows, not instructions.

Bis incorrect because the LLM selects actions based on context/intent, not instructions.

Salesforce Help Article:Custom Action Configuration('Defining Action Instructions' section).

Einstein Bot Developer Guide: 'Designing User-Centric Actions with Instructions' (User Experience alignment).

asked 11/02/2025
Akram Abou Soultan
32 questions

Question 97

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Universal Containers (UC) wants to leverage Generative AI Salesforce functionality to reduce Service Agent handling time by providing recommended replies based on the existing Knowledge articles.

On which AI capability should UC train the service agents?

Case Replies

Case Replies

Knowledge Replies

Knowledge Replies

Service Replies

Service Replies

Suggested answer: B

Explanation:

Knowledge Repliesis the Einstein Generative AI capability that generates recommended responses for service agents by grounding responses in the organization'sKnowledge articles. This reduces handling time by providing contextually accurate suggestions sourced directly from approved content. Salesforce documentation states that Knowledge Replies leverage natural language processing (NLP) to match customer inquiries with relevant articles and draft replies, ensuring consistency and compliance.

Case Replies(A) focus on generating responses based on case data (e.g., case fields, history) but do not explicitly ground responses in Knowledge articles.

Service Replies(C) is not a standard Einstein capability tied to Knowledge-driven responses.

Salesforce Help Article:Einstein for Service -- Knowledge Replies('How Knowledge Replies Work' section).

Einstein for Service Implementation Guide: 'Reducing Handle Time with Knowledge-Driven Responses.'

asked 11/02/2025
Yuwadee Srisathan
40 questions

Question 98

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Which part of the Einstein Trust Layer architecture leverages an organization's own data within a large language model (LLM) prompt to confidently return relevant and accurate responses?

Prompt Defense

Prompt Defense

Data Masking

Data Masking

Dynamic Grounding

Dynamic Grounding

Suggested answer: C

Explanation:

Dynamic Groundingin the Einstein Trust Layer architecture ensures that large language model (LLM) prompts are enriched withorganization-specific data(e.g., Salesforce records, Knowledge articles) to generate accurate and relevant responses. By dynamically injecting contextual data into prompts, it reduces hallucinations and aligns outputs with trusted business data.

Prompt Defense(A) focuses on blocking malicious inputs or prompt injections but does not enhance responses with organizational data.

Data Masking(B) redacts sensitive information but does not contribute to grounding responses in business context.

Salesforce Help Article:Einstein Trust Layer -- Dynamic Grounding('How Dynamic Grounding Works' section).

Einstein Trust Layer Technical Overview: 'Contextual Accuracy with Dynamic Grounding.'

asked 11/02/2025
Mellisa Stroman
38 questions

Question 99

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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?

Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.

Use a prompt template grounded on CRH and Data Cloud data using standard foundation model.

Fine-Tune the standard foundational model due to the complexity of the data.

Fine-Tune the standard foundational model due to the complexity of the data.

Deploy UC's own custom foundational model on this data first.

Deploy UC's own custom foundational model on this data first.

Suggested answer: A

Explanation:

For no-code implementations,Prompt Builderallows AI Specialists to createprompt templatesthat 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.

Salesforce Help Article:Prompt Builder for No-Code AI('Grounding in CRM and Data Cloud' section).

Einstein GPT Implementation Guide: 'Generating Summaries with Pre-Built Models.'

asked 11/02/2025
Lyboth Ntsana
43 questions

Question 100

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Universal Containers aims to streamline the sales team's daily tasks by using AI.

When considering these new workflows, which improvement requires the use of Prompt Builder?

Populate an Al-generated time-to close estimation to opportunities

Populate an Al-generated time-to close estimation to opportunities

Populate an AI generated summary field for sales contracts.

Populate an AI generated summary field for sales contracts.

Populate an Al generated lead score for new leads.

Populate an Al generated lead score for new leads.

Suggested answer: B

Explanation:

Prompt Builderis explicitly required to createAI-generated summary fieldsvia prompt templates. These fields use natural language instructions to extract or synthesize information (e.g., summarizing contract terms). Time-to-close estimations (A) and lead scores (C) are typically handled by predictive AI (e.g., Einstein Opportunity Scoring) or analytics tools, which do not require Prompt Builder.

Salesforce Help Article:Create AI-Generated Fields with Prompt Builder('Summary Field Generation' example).

Einstein GPT for Sales Guide: 'Automating Contract Summaries.'

asked 11/02/2025
Robbie Shen
34 questions
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