AI Associate Practice Test 2 — 25 Questions

Question 1

An admin is configuring Einstein Prediction Builder to predict case escalation. Which TWO components must be selected during setup?

Accepted Answer

Prediction field (binary classification target). Einstein Prediction Builder requires a binary classification target field to define the outcome being predicted—in this case, whether a case will escalate. This field must have exactly two distinct values (e.g., 'Yes'/'No' or 0/1) to train the model. Without specifying the prediction field, the builder cannot determine what event to forecast.

Answer

Prediction explanation template

Answer

Data set (records to train on)

Answer

Prediction score field name

Question 2

A sales manager wants to use Einstein Lead Scoring but is concerned about transparency for the sales team. Which TWO features should they enable to provide explainability? (Choose 2)

Accepted Answer

Score Factors on the lead record. Score Factors show why a lead scored as it did, and labeling AI-generated scores helps reps understand that the score is AI-driven.

Answer

Einstein Copilot

Answer

Einstein Activity Capture

Answer

Einstein Trust Layer audit trail

Question 3

A sales rep wants to automatically log emails and events from Outlook to Salesforce without manual work. Which Einstein feature should be enabled?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture (C) is the correct feature because it automatically syncs emails and events from Microsoft Outlook (or Google Workspace) to Salesforce without requiring manual logging. It uses a background sync engine that captures email headers and calendar events based on configured rules, eliminating the need for users to manually log activities via add-ins or plugins.

Answer

Einstein Conversation Insights

Answer

Einstein Email Insights

Answer

Einstein Lead Scoring

Question 4

Which Einstein feature uses strategy builder (flows, Apex) to recommend offers or actions to users at the right moment?

Accepted Answer

Einstein Next Best Action. Einstein Next Best Action is the correct answer because it is the Einstein feature that uses Strategy Builder (which includes flows and Apex) to define decision logic and recommend the most relevant offers or actions to users at the right moment. It evaluates real-time context and business rules to surface the optimal next step, such as a discount or a follow-up task, directly within the Salesforce user interface.

Answer

Einstein Copilot

Answer

Einstein Prediction Builder

Answer

Einstein Recommendation Builder

Question 5

A data scientist notices that a churn prediction model has high variance: small changes in training data cause large changes in predictions. Which technique is BEST to address this?

Accepted Answer

Apply regularization techniques. High variance indicates overfitting. Regularization (e.g., L1/L2) reduces model complexity and variance. Adding more features would increase variance, increasing training data can help but is not always feasible, and reducing training data would worsen the problem.

Answer

Reduce the amount of training data

Answer

Add more features to the model

Answer

Increase the number of training epochs

Question 6

A marketer wants to use Einstein Segment Creation to build a segment for a campaign. Which data source can be used?

Accepted Answer

Data Cloud unified profile data.. Einstein Segment Creation works with Data Cloud unified profiles.

Answer

Standard report snapshots.

Answer

External web analytics.

Answer

Einstein Activity Capture data.

Question 7

A financial services company uses Salesforce AI to detect fraudulent transactions. The dataset has 1 million legitimate transactions and only 1,000 fraudulent ones. The model trained with default parameters achieves 99.9% accuracy but identifies no fraud (precision and recall of 0). The data scientist wants to maximize fraud detection (recall) while minimizing false positives. Which approach is most effective?

Accepted Answer

Use SMOTE to generate synthetic fraud samples to balance the dataset.. With extreme imbalance, oversampling the minority class (e.g., SMOTE) generates synthetic fraud examples, helping the model learn fraud patterns and improve recall without discarding legitimate data.

Answer

Increase the weight of the majority class in the loss function.

Answer

Train multiple models on different random subsets and average predictions.

Answer

Use a simpler model to avoid overfitting on the majority class.

Question 8

A company deploys an AI recommender system that personalizes content. The system is trained on user click data. After deployment, the company notices that the system increasingly recommends sensationalist content, leading to user polarization. Which principle is being violated?

Accepted Answer

Beneficence. The recommender system's shift toward sensationalist content, which polarizes users, violates the principle of beneficence because it causes harm (user polarization) rather than promoting well-being. Beneficence requires AI systems to act in the best interests of users and society, not to optimize for engagement metrics at the expense of ethical outcomes.

Answer

Accuracy

Answer

Privacy

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Transparency

Question 9

A financial services company is deploying Einstein AI and must comply with regulations requiring explainable decisions. Which Einstein capability allows them to understand why an AI model made a specific prediction?

Accepted Answer

Einstein Trust Layer with model explainability features.. The Einstein Trust Layer includes model explainability features that provide insights into why a specific prediction was made, such as highlighting the key input features that influenced the outcome. This directly addresses regulatory requirements for explainable AI decisions by offering transparency into the model's reasoning process.

Answer

Data Mask to protect sensitive information.

Answer

Salesforce Shield with encryption and monitoring.

Answer

Field Audit Trail to track changes to data.

Question 10

A data scientist is using Einstein Vision and Language Platform for text classification. They need to handle custom entities (NER) and classify text into multiple categories. Which THREE capabilities of the Einstein Platform Services API should they use?

Accepted Answer

Sentiment Analysis. Sentiment Analysis is a key capability of the Einstein Platform Services API that allows the data scientist to determine the emotional tone (positive, negative, or neutral) of text, which is essential for understanding customer feedback or social media posts. This complements the other required capabilities—Text Classification for categorizing text into multiple categories and Named Entity Recognition (NER) for extracting custom entities—forming a complete solution for the described text classification and NER tasks.

Answer

Object Detection

Answer

Image Classification

Question 11

An AI system is used to approve loan applications. The model uses income, zip code, and credit score as features. What is a potential ethical concern?

Accepted Answer

Zip code may act as a proxy for race, leading to discrimination. Using zip code as a feature can introduce proxy discrimination. Zip codes are strongly correlated with race and socioeconomic status due to historical redlining and residential segregation. When the model learns patterns from zip code, it may inadvertently deny loans to applicants from certain racial or ethnic groups, violating fair lending laws and ethical AI principles.

Answer

The model should be a black box to avoid bias

Answer

Credit scores are rarely accurate

Answer

Income is not a reliable predictor of repayment

Question 12

A company uses an NLP model to detect intent in customer messages. The model works well for English but fails for Spanish messages. What is the most likely cause?

Accepted Answer

The training data is predominantly English. If the training data lacks Spanish examples, the model cannot learn Spanish patterns.

Answer

The model is overfitted to English

Answer

The inference threshold is too high

Answer

The model uses the wrong algorithm

Question 13

Which Einstein feature provides AI-powered call recording analysis that tracks keywords, talk-time metrics, and next steps?

Accepted Answer

Einstein Conversation Insights. Einstein Conversation Insights analyzes call recordings and provides metrics and action items.

Answer

Einstein Email Insights

Answer

Einstein Activity Capture

Answer

Einstein Voice

Question 14

A company wants to use customer purchase history to train a recommendation model. Which action is essential to comply with data privacy regulations?

Accepted Answer

Obtain explicit consent from customers.. Data privacy regulations such as GDPR and CCPA require a lawful basis for processing personal data, and explicit consent is a primary lawful basis when using customer purchase history for training a recommendation model. Without obtaining explicit consent, the company would be processing personal data without a valid legal ground, violating regulations that mandate transparency and user control over their data.

Answer

Use only publicly available data.

Answer

Ignore regulations because data is internal.

Answer

Anonymize the data after training.

Question 15

A company is designing an AI system to screen job applicants. To ensure fairness, which practice should be implemented?

Accepted Answer

Conduct regular fairness audits on model outcomes. Regular fairness audits are essential because they systematically evaluate model outcomes for bias across demographic groups, using metrics like disparate impact or equal opportunity difference. This practice aligns with responsible AI frameworks (e.g., NIST AI Risk Management Framework) and helps detect subtle biases that may emerge from proxy variables or data drift, ensuring the screening process remains equitable over time.

Answer

Use only one data source for consistency

Answer

Maximize the model's accuracy on historical hiring decisions

Answer

Remove all demographic data from the training set

Question 16

A company wants to deploy an AI system that makes hiring decisions. To comply with ethical guidelines, what should they do before deployment?

Accepted Answer

Conduct an ethics review and perform bias testing on diverse datasets.. Conducting an ethics review and performing bias testing on diverse datasets are essential steps to identify and mitigate potential discriminatory outcomes in AI-driven hiring systems. This aligns with ethical AI frameworks that require fairness, accountability, and transparency before deployment, ensuring the model does not perpetuate historical biases or violate anti-discrimination laws.

Answer

Ensure the system achieves high accuracy and ignore other metrics.

Answer

Deploy immediately and monitor for issues.

Answer

Test the system only on a small dataset to expedite launch.

Question 17

A company wants to build an autonomous AI agent in Salesforce that can handle customer returns, refunds, and exchanges without human intervention. Which THREE components are required to build this agent using Agentforce?

Accepted Answer

Topics and Actions. To build an autonomous AI agent in Salesforce that handles customer returns, refunds, and exchanges without human intervention, you need Topics and Actions to define the specific business processes (e.g., 'Process Return') and the corresponding API calls or flows, Agent Builder to configure the agent's behavior and link it to those topics, and Testing in Agent Builder to validate the agent's responses and ensure it operates correctly before deployment.

Answer

Prompt Builder

Answer

Einstein Copilot

Question 18

A team is labeling text data for a sentiment analysis model. To ensure consistency and quality, which practice should they prioritize?

Accepted Answer

Use majority voting among multiple labelers.. Majority voting among multiple labelers reduces individual bias and errors, improving label consistency and quality for training data. This approach is standard in supervised learning for sentiment analysis because it aggregates diverse judgments, leading to more reliable ground truth labels.

Answer

Use a single expert labeler for all data.

Answer

Label all data by a single expert labeler.

Answer

Allow each labeler to interpret guidelines freely.

Question 19

According to Salesforce's AI ethics principles, which three pillars should guide the development of AI applications?

Accepted Answer

Accountability.. Accountability is one of Salesforce's core AI ethics principles, requiring that organizations take responsibility for the outcomes of their AI systems. This principle ensures that there is human oversight and that AI applications are designed with mechanisms for redress and governance, aligning with Salesforce's commitment to ethical AI development.

Answer

Profitability.

Answer

Scalability.

Question 20

A company is deploying an AI model that recommends next best actions for sales reps. They notice that the model's recommendations are biased towards high-revenue opportunities. Which data-related action can help reduce this bias?

Accepted Answer

Oversample the underrepresented segments in the training data. Oversampling underrepresented segments in the training data directly addresses the class imbalance that causes the model to favor high-revenue opportunities. By increasing the frequency of low-revenue examples, the model learns to treat all segments more equally, reducing bias in its recommendations. This is a standard data-level technique for mitigating bias in AI models.

Answer

Use a larger neural network model

Answer

Encrypt the data before training

Answer

Remove all low-revenue opportunities from the training data