Question # 1
| What should an AI Specialist consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder? | | A. The Activities related list on the Account object is not supported because it is a polymorphic field. | | B. If person accounts have been enabled, merge fields will not be available for the Account object. | | C. Prompt generation will yield no response when there is no related list associated with an Account in runtime. |
A. The Activities related list on the Account object is not supported because it is a polymorphic field.
Explanation:
When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
Option B is incorrect because person accounts do not limit the availability of merge fields for the Account object.
Option C is irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields.
Question # 2
| An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM data. 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. Dynamic grounding with secure data retrieval | | C. Zero-data retention policy |
B. Dynamic grounding with secure data retrieval
Explanation:
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.
Question # 3
| An AI Specialist wants to ground a new prompt template with the User related list. What should the AI Specialist consider? | | A. The User related list should have View All access. | | B. The User related list needs to be included on the record page. | | C. The User related list is not supported in prompt templates. |
C. The User related list is not supported in prompt templates.
Explanation:
An AI Specialist wants to ground a new prompt template with the User related list. Grounding in prompt templates involves using data from related lists to provide context or additional information to the Large Language Model (LLM) when generating responses.
Key Consideration:
Unsupported Related Lists in Prompt Templates:
Limitation: The User related list is not supported in prompt templates for grounding purposes.
Reason: Salesforce restricts certain objects and related lists from being used in prompt templates to maintain data security and integrity. The User object often contains sensitive information and is subject to strict access controls.
Impact: Attempting to use the User related list in a prompt template will not work as expected because the system does not support it.
Why Options A and B Are Incorrect:
Option A (The User related list should have View All access):
Incorrect: Even with View All access, the User related list is still not supported in prompt templates.
Security Concerns: Granting View All access to the User object is a significant security risk and not a recommended practice.
Option B (The User related list needs to be included on the record page):
Incorrect: Including the User related list on the record page does not affect its availability in prompt templates.
Irrelevance: The placement of the related list on the record page does not change the system's ability to access it in a prompt template.
Question # 4
| Universal Containers’ data science team is hosting a generative large language model (LLM) on Amazon Web Services (AWS). What should the team use to access externally-hosted models in the Salesforce Platform? | | A. Model Builder | | B. App Builder | | C. Copilot Builder |
A. Model Builder
Explanation:
To access externally-hosted models, such as a large language model (LLM) hosted on AWS, the Model Builder in Salesforce is the appropriate tool. Model Builder allows teams to integrate and deploy external AI models into the Salesforce platform, making it possible to leverage models hosted outside of Salesforce infrastructure while still benefiting from the platform's native AI capabilities.
Option B, App Builder, is primarily used to build and configure applications in Salesforce, not to integrate AI models.
Option C, Copilot Builder, focuses on building assistant-like tools rather than integrating external AI models.
Model Builder enables seamless integration with external systems and models, allowing Salesforce users to use external LLMs for generating AI-driven insights and automation.
Question # 5
| 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. Data Cloud-triggered flow | | B. Template-triggered prompt flow | | C. Unified-object linking flow |
A. Data Cloud-triggered flow
Explanation:
In this scenario, Universal Containers wants to bring data from unified Data Cloud objects into prompt templates, and the best way to do that is through a Data 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 on Data Cloud-triggered flows and Data Cloud integrations with generative AI solutions.
Question # 6
| An AI Specialist is considering using a Field Generation prompt template type. What should the AI Specialist check before creating the Field Generation prompt to ensure it is possible for the field to be enabled for generative AI? | | A. That the field chosen must be a rich text field with 255 characters or more. | | B. That the org is set to API version 59 or higher | | C. That the Lightning page layout where the field will reside has been upgraded to Dynamic Forms |
B. That the org is set to API version 59 or higher
Explanation:
Before creating a Field Generation prompt template, the AI Specialist must ensure that the Salesforce org is set to API version 59 or higher. This version of the API introduces support for advanced generative AI features, such as enabling fields for generative AI outputs. This is a critical technical requirement for the Field Generation prompt template to function correctly.
Option A (rich text field requirement) is not necessary for generative AI functionality.
Option C (Dynamic Forms) does not impact the ability of a field to be generative AI-enabled, although it might enhance the user interface.
Question # 7
| Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes. What is a consideration for this requirement? | | A. Storing this data requires Data Cloud to be provisioned. | | B. Storing this data requires a custom object for data to be configured. | | C. Storing this data requires Salesforce big objects. |
A. Storing this data requires Data Cloud to be provisioned.
Explanation:
When implementing Einstein Generative AI for improved customer insights and interactions, the Data Cloud is a key consideration for storing and managing large-scale audit and feedback data. The Salesforce Data Cloud (formerly known as Customer 360 Audiences) is designed to handle and unify massive datasets from various sources, making it ideal for storing data required for AI-powered insights and reporting. By provisioning Data Cloud, organizations like Universal Containers (UC) can gain real-time access to customer data, making it a central repository for unified reporting across various systems.
Audit and feedback data generated by Einstein Generative AI needs to be stored in a scalable and accessible environment, and the Data Cloud provides this capability, ensuring that data can be easily accessed for reporting, analytics, and further model improvement.
Custom objects or Salesforce Big Objects are not designed for the scale or the specific type of real-time, unified data processing required in such AI-driven interactions. Big Objects are more suited for archival data, whereas Data Cloud ensures more robust processing, segmentation, and analysis capabilities.
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FAQs of Salesforce-AI-Specialist Exam
What is the Salesforce AI Specialist Exam?
Answer: The Salesforce AI Specialist exam tests your knowledge of integrating AI into Salesforce platforms to enhance customer experiences.
How do I Prepare for Salesforce AI Specialist Certification?
Answer: Study Guides- Utilize the official Salesforce study guide and practice by taking Practice Questions using reliable sources like RealBraindumps.
What is the passing percentage for the Salesforce AI Specialist exam?
Answer: You must score at least 73% or above to pass the Salesforce AI Specialist Exam.
How much does the Salesforce AI Specialist exam cost?
Answer: Salesforce-AI-Specialist exam typically costs $200, but it all depends upon the location.
How many questions will I get in my Salesforce AI Specialist exam?
Answer: There will be 60 multiple-choice questions present in the Salesforce AI Specialist exam.
What is the time duration of the Salesforce AI Specialist exam?
Answer: The time for the exam is 90 minutes, so you will have plenty of time to answer all the questions.
Can I attempt the Salesforce AI Specialist Exam again if I fail?
Answer: Yes, you can retake, but you need to wait 14 days and pay a retake fee.
What are the benefits of obtaining a Salesforce AI Specialist certification?
Answer: Gaining such certification enhances career opportunities through the validation of skills in AI and Salesforce; better opportunities come hand in hand with better networking, increased salary rates, and much more in a present job.
Do you need to fulfill any requirements before you take the Salesforce AI Specialist exam?
Answer: While there are no strict prerequisites, hands-on experience with AI and Salesforce is recommended.
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Answer: The exam covers AI fundamentals, Salesforce integration, data modeling, and customer engagement through AI.
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Answer: The exam consists of 60 multiple choice questions, and it lasts 90 minutes. For More information visit: https://trailhead.salesforce.com/en/credentials/aispecialist
What are the key topic areas of the Salesforce AI Specialist Certification?
Answer: The key topic areas include Einstein Trust Layer, Generative AI in CRM Applications, Prompt Builder, Einstein Copilot, and Model Builder.
How does Salesforce Einstein work?
Answer: Salesforce Einstein integrates AI capabilities into Salesforce, offering tools like Sales emails, Service replies, Einstein Copilot, Prompt Builder, and more.
What are the key topic areas covered in the Salesforce AI Specialist exam?
Answer: The Salesforce AI Specialist exam covers the following key areas: 1. Einstein Trust Layer (15%), 2. Generative AI in CRM Applications (17%), 3. Prompt Builder (37%), 4. Einstein Copilot (23%), 5. and Model Builder (8%).
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