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AI Associate AI Fundamentals Practice Question

Exhibit

{
  "policy": {
    "dataMask": {
      "enabled": true,
      "fields": ["Email", "Phone", "SSN"]
    },
    "insights": {
      "featureImportance": true
    }
  }
}

Refer to the exhibit. A Salesforce admin configured the Einstein Trust Layer policy shown. What is the effect of this policy on AI model usage?

⚠ Common exam trap

Many candidates assume masking blocks all AI functionality, but feature importance insights are still available because they rely on patterns in the masked data, not the original values.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

AI models receive masked data for those fields, but feature importance insights are still available.

The Einstein Trust Layer policy configured to mask specific fields ensures that sensitive data is replaced with masked values before being sent to the AI model. This preserves data privacy while still allowing the model to generate predictions and insights. Feature importance insights remain available because they are computed from the masked data, not the original values.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
All fields in the org will be masked to protect customer privacy.
Why it's wrong here
Only specified fields are masked.
✗
AI models will not be able to use the configured fields, and model insights are disabled.
Why it's wrong here
Insights are enabled, and masking still allows model to use data? Actually, masking hides the raw values but the model can still use features? In Einstein, masking replaces with dummy values, so model can use them. So statement is false.
✗
AI models can still use the fields but feature importance insights are blocked.
Why it's wrong here
Feature importance is enabled.
✓
AI models receive masked data for those fields, but feature importance insights are still available.
Why this is correct
Masking hides actual values; insights are independent.

Go deeper

1 more way this is tested on AI Associate

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A Salesforce admin wants to use Einstein GPT to generate personalized email content for a marketing campaign. To ensure the AI does not produce responses that include sensitive customer data or violate company policies, which Salesforce feature should the admin configure?

medium

A.Prompt Builder
B.Data Cloud
C.Einstein Studio
✓ D.Einstein Trust Layer

Why D: Einstein Trust Layer is the correct feature because it acts as a governance and security layer between Salesforce and the large language model (LLM). It automatically masks sensitive customer data (e.g., personally identifiable information) before the prompt is sent to the LLM and then unmasks the response, ensuring the AI never sees or exposes sensitive information. This directly addresses the admin's need to prevent responses containing sensitive data or violating company policies.

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.

AI Associate AI Fundamentals Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question

1 more way this is tested on AI Associate